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Location: New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Prague, Czechia; Lisbon, Portugal; Madrid, Spain CloudLinux is a global remote-first company. We are driven by our principles: do the right thing, employees first, we are remote first, and we deliver high-volume, low-cost Linux infrastructure and security products that help companies to increase the efficiency of their operations. Every person on our team supports each other and does what we can to ensure we all are successful. Check out our website for more information: cloudlinux.com We are currently hiring Staff Engineers for various projects within the Imunify360 product. Imunify360 is CloudLinux's multi-layer security suite for Linux web servers: antivirus and malware cleanup, WAF, IDS/IPS, Proactive Defense, patch management (KernelCare/Patchman), and IP/domain reputation. It runs on hundreds of thousands of shared, VPS and dedicated hosting servers, under cPanel, Plesk, DirectAdmin and standalone. The engineering org is 60+ engineers in squads covering backend, core, server agent, malware research, WAF/WebShield, and Patchman. Core services are Python; agents and performance-critical paths are Go and Rust. We run on Hetzner and our own bare metal. Check out our website for more information: https://imunify360.com/ Role Mission & Scope Most complex technical challenges in Imunify360 go beyond individual squads. A single detection change can impact the scanner, agent, UI, reputation backend, and release process. While squad leads own delivery within their teams, the Staff Engineer ensures technical alignment across the product. As a Staff Engineer, you'll be a hands-on technical leader working across the entire product , focusing on the most critical and high-impact challenges as priorities evolve. You'll drive technical decisions, improve architecture, establish engineering standards, and help teams build sustainable solutions. This is an individual contributor role , without direct people management responsibilities. You'll remain actively involved in development, spending approximately 30–50% of your time writing production code , rather than focusing solely on architectural design. While deep expertise in a particular area is valued, this role requires the flexibility to work across different components, collaborate with multiple squads, and tackle challenges wherever your expertise can make the greatest impact. What you will own Architecture and technical direction Own the end-to-end architecture of Imunify360 as a product: agent ↔ server ↔ cloud backends, data flows, and the contracts between them. Write and drive ADRs and RFCs for cross-squad changes. Run the Wed/Fri architecture sync together with the Technical Director. Keep a living tech-debt and risk register (security / compliance / uptime) with owners and dates, and get the top items funded on the roadmap. Hard cross-cutting problems (examples of what lands on your desk) Agent resource footprint on dense shared hosts: CPU, memory and I/O budgets for scanning, file monitoring (inotify/fanotify) and WAF, measured on real kernels, not benchmarks from elsewhere. Detection pipeline quality: false positive / false negative rates, signature and ML model rollout with staged gates and rollback. Upgrade and release safety across a large, heterogeneous fleet (CentOS/AlmaLinux/CloudLinux/Ubuntu, multiple control panels, old kernels). Backend scale and cost of reputation, ThreatIntel and telemetry services. Migrating hot paths from Python to Go/Rust where the data shows it pays off, and saying no where it doesn't. Engineering standards Set the bar for design reviews, code review, testing strategy, observability (Prometheus/Grafana/Sentry) and secure SDLC (OWASP ASVS, CIS Benchmarks as relevant). Lead or co-lead SEV1/SEV2 incidents when the cause is unclear or cross-squad; make sure the blameless post-mortem ships within 24 h and its actions get closed. Drive the AI-augmented SDLC in practice: show what good agentic coding looks like (prompt specificity, context provision, review quality, tool boundaries) on real changes, not slides. People multiplier (no direct reports) Mentor senior engineers and squad leads toward staff-level scope. Act as the technical bar-raiser in hiring loops for senior and lead roles. Be the engineering voice in product and sales discussions: estimates, feasibility, and no dated customer commitment without a written squad-lead estimate. Key Milestones 30 days: Shipped at least one non-trivial change to production. Can explain the full request path from agent to backend. Has a personal list of top 10 technical risks. 90 days: Owns one cross-squad initiative with an approved ADR, a measured baseline, and a staged rollout plan. Published risk register reviewed in arch sync. 6 months: That initiative is in production with before/after metrics. At least one engineering standard (e.g. release gating, agent perf budget, design review template) is adopted by 3+ squads. 12 months: Recognized by squad leads as the default escalation point for cross-cutting technical decisions. At least one senior engineer grown into broader scope with your mentorship. Requirements Must have 10+ years building and operating production software, with 3+ years in a Staff/Principal/Tech Lead scope spanning several teams. Strong production experience in Python and at least one of Go or Rust . Deep Linux internals : processes, filesystems, networking, kernel interfaces (inotify/fanotify, eBPF or similar), packaging (RPM/DEB), systemd. Track record of designing and running distributed systems at scale: async backends, queues, databases, caching, failure modes. You have owned systems that run on customer machines (agents, daemons, on-prem software) and know what upgrade safety, backward compatibility and resource budgets mean there. Security mindset: threat modeling, secure coding, handling of untrusted input (files, HTTP traffic, user content). Writes clear, short technical documents and drives decisions in async, remote teams across time zones. Uses AI coding tools (Cursor, Claude, MCP-based tooling) daily and can judge their output critically. Nice to have Experience in server security: AV/malware detection, WAF (ModSecurity/Coraza), IDS/IPS, rootkit detection, CVE/patch management. Experience with WordPress and Node.JS web application hosting at scale ML in production for classification/detection, including evaluation and safe model rollout. Observability at scale: Prometheus, Grafana, Sentry, ClickHouse or similar. CI/CD ownership: GitLab CI, Jenkins, build systems for multi-distro packaging. Open-source contributions in security or systems tooling. Benefits What's in it for you? Stay hands-on technically while owning complex, high-impact engineering work. Work on challenging Linux, automation, and cybersecurity problems across mature and newer products. Influence technical direction and make meaningful architectural decisions. Work independently with a high level of ownership and autonomy. Fully remote work with flexible working hours. 24 paid vacation days, 10 national holidays, and unlimited sick leave. Private medical insurance compensation. Co-working and gym/sports reimbursement. Education budget. Opportunity to receive a reward for innovative ideas that the company can patent. By applying for this position, you consent to the processing of your personal data as described in our Privacy Policy ( https://cloudlinux.com/candidate-privacy-notice ), which provides detailed information on how we maintain and handle your data.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is hiring a Staff Electrical R&D Lead to drive the advanced development of next-generation wearable sensing technologies. As part of the Hardware Engineering team, you will lead the exploration, design, characterization, and validation of novel sensing systems, developing a deep understanding of the complete signal chain - from the underlying physiological signals and sensor interfaces through analog and digital electronics to downstream system requirements. You will combine strong electrical engineering fundamentals, hands-on experimentation, and advanced data analysis to translate complex system behavior into architecture and design improvements that optimize sensing performance. This is a hands-on technical leadership role for an engineer who combines deep electrical expertise with exceptional systems thinking, analytical rigor, and technical judgment. You will guide and mentor engineers while working closely with Electrical, Mechanical, Firmware, Signal Processing, and WHOOP Labs teams to evaluate emerging technologies, define system requirements, identify performance limitations, and drive technical decisions. You will help establish the technical direction for advanced electrical development, balancing innovation with product feasibility, performance, and development timelines. RESPONSIBILITIES: - Lead advanced electrical development initiatives, driving technical direction from early-stage technology exploration and sensor evaluation through feasibility, prototyping, system characterization, and design validation - Develop a deep understanding of the complete sensing signal chain, including sensor behavior, analog front-end performance, electrical interfaces, physiological characteristics, and downstream system requirements, to inform electrical architecture decisions and optimize end-to-end sensing performance. - Define and execute experiments to characterize sensor and system behavior, isolate variables, identify performance limitations, and evaluate interactions across electrical, mechanical, physiological, and environmental conditions - Execute data analysis to translate experimental findings into actionable electrical design improvements, technical recommendations, and quantitative performance requirements. - Drive the evaluation, integration, and validation of new sensing technologies, establishing test methodologies, performance criteria, and system-level requirements that support reliable operation across real-world use cases - Partner closely with Electrical, Mechanical, Firmware, Signal Processing, and WHOOP Labs teams to understand system dependencies, evaluate technical tradeoffs, and ensure electrical designs support broader sensing system performance objectives - Lead complex technical investigations and root-cause analysis, combining first-principles engineering, bench measurements, system telemetry, and structured experimentation to identify risks and drive effective design solutions - Guide and mentor engineers across advanced development projects, setting technical priorities, providing design review and technical direction, and driving cross-functional alignment while maintaining strong hands-on engineering contributions - Translate ambiguous technical challenges into actionable development plans, proactively communicating technical risks, recommendations, and progress while balancing engineering rigor with product and schedule objectives - Remain hands-on with circuit design and simulation, prototype bring-up, hardware debugging, and design iteration, directly contributing to critical technical investigations and design decisions QUALIFICATIONS: - Bachelor's degree or higher in Electrical Engineering or a related technical field, or equivalent practical experience - 8+ years of relevant electrical engineering, hardware R&D, or sensing systems development experience, with demonstrated technical leadership and ownership of complex engineering projects - Deep electrical engineering fundamentals across analog and digital circuit design, sensor interfaces, signal integrity, noise analysis, and system-level electrical architecture - Strong systems-level understanding of sensing technologies - Exceptional hands-on experimentation, hardware characterization, and debugging skills, with the ability to apply first-principles engineering and structured analysis to complex technical challenges - Proficiency in Python or equivalent tools - Demonstrated ability to lead ambiguous, cross-functional technical initiatives, guide engineering decisions, mentor other engineers, and drive technical challenges to resolution - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Applied AI team helps the world’s largest organizations put Claude to work. As a Cybersecurity Specialist on Applied AI, you’ll be part of an overlay team of domain experts who sit alongside our enterprise account teams and bring deep security expertise to the accounts where it matters most. You won’t own an account. You’ll be the security expert the account team pulls in to win and grow the most important security conversations: helping CISOs and security leaders see where Claude can take on real security work, then guiding them from early pilots to durable, production workloads. You’ll cover a portfolio of enterprise accounts across regulated industries like financial services, insurance, and healthcare, strategic accounts like semiconductors (IP protection, industrial control systems, export controls), and digital natives and public sector agencies, each with its own threat model. How this team works You partner with account executives, account architects, and generalist Applied AI engineers, who own the customer relationship and the broader technical engagement. You bring the security depth they don’t have time to build. You work across many accounts at once, so the playbooks, reference implementations, and evaluation approaches you build are reused across the field, not just for one customer. You are the connection point between the field and Anthropic’s Product, Research, and Engineering teams, turning what you see in customer security programs into product feedback. You work alongside ISVs, systems integrators, and managed security providers who already serve these customers, enabling them where they own the engagement rather than competing with them. Responsibilities Join account teams to understand a customer’s security program, identify where Claude can do meaningful security work, and turn that into a technical plan and business case Serve as the security-domain technical advisor on strategic enterprise accounts, from discovery through deployment Move customers from one-time code scanning to sustained security workloads: application security in the SDLC, continuous automated penetration testing, alert triage and investigation, and threat intelligence that answers “does this new vulnerability affect us, and where” Build and maintain reference implementations, harnesses, and evaluation approaches, and help customers adapt them to their own environments and controls Run workshops and hands-on sessions where customer security teams use Claude on their own code and workflows Equip partners to deliver Claude-powered security outcomes, with a clear line between what Anthropic delivers and what partners deliver Speak credibly to every audience, from appsec engineers to CISOs and executives, including how to explain the value and risk of security work in business terms Define and track adoption depth for each security workload across your accounts, and work with Product and Engineering on the telemetry to measure it Write the playbooks and best practices the rest of the field can reuse, including how Claude complements the security tooling customers already own Develop reference customers who can speak to the value they’re realizing Stay current on frontier LLM capabilities and the new classes of vulnerabilities and attacks they surface Travel occasionally to customer sites for workshops and technical deep dives You may be a good fit if you have 5+ years in security roles, with hands-on depth in at least two of: application security and secure SDLC, offensive security and penetration testing, detection and response, or threat intelligence and vulnerability management Experience in a technical customer-facing role (Solutions Architect, Sales Engineer, security consultant, TAM), or on a security team where you had to win investment from leadership Experience with large enterprise customers and complex, multi-stakeholder buying cycles, including working alongside the vendors and partners already in the account The ability to translate between security teams, engineering teams, and executives Comfort with Python, CI/CD, and cloud environments, plus hands-on experience using LLMs for security work such as code review, vulnerability discovery, triage, or investigation A love of teaching and a collaborative approach to working across teams and balancing competing priorities The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 — $400,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Distributed; Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations: Austin TX, San Francisco CA, NYC, Atlanta GA OR Denver CO About the role The GTM Intelligence team helps Cloudflare's go-to-market organization make faster, better decisions with trusted data. We work with Sales, Technical Sales, Services, Finance, and our central Data teams to make sure the people who sell, deploy, and support Cloudflare get consistent, reliable answers to the questions that matter most. We're looking for a Senior GTM Analytics Manager to set and execute the vision for how information scales across Cloudflare's technical customer-facing teams. You'll support Pre- and Post-Sales Operations, Solutions Engineering, Forward Deployed Engineering, and Professional Services. This role is less about building more dashboards or doing one-off deep dives and more about building the foundations to support true self-serve analytics.  You will focus on single source of truth artifacts, strategic alignment of metrics to actions, and the data models, metric definitions, and context layers that let anyone in these organizations get a trustworthy answer that fits their needs. That person might be an executive, a frontline manager, an engineer in the field, or an AI agent working for any of them. You'll be a technical expert and a strategic partner in one. You'll be as comfortable reviewing a dimensional model with Data Engineering as you are agreeing a metric definition with a VP of Professional Services. And you'll be our go-to voice on how analytics should change now that more and more questions get answered through AI. This is a senior individual contributor role with wide influence and no direct reports. What you'll do Define and drive a multi-year strategy for how Pre-Sales, Post-Sales, Solutions Engineering, FDE, and Professional Services find, trust, and use data, including a maturity model and a phased roadmap. Act as a thought leader on scaling information in an AI-first world, working out how semantic layers, governed metrics, and well-built context let AI assistants and agents give accurate, consistent answers grounded in our business. Review the current mix of dashboards, reports, and tools across these teams. Create a plan to consolidate them, retire duplicates, and move toward a single source of truth. Define, document, and carry out the official metrics for the teams you support. Keep metric definitions aligned with corporate definitions from Finance and Data, and resolve conflicts between teams with clear, defensible logic. Act as the main business and technical partner to the central Data team for the stakeholders you support. Influence and review the design of data models across systems such as Salesforce, professional services tools, product usage and telemetry, support, and finance. Design how people get answers: self-serve access, natural-language and AI-assisted querying, embedded insights in daily workflows, and curated metric catalogs. Set up a formal intake and governance process for new metric and data requests, including prioritization, ownership, certification, and change management. Build trusted relationships with leaders in Sales, Solutions Engineering, FDE, Professional Services, Customer Success, Operations, Finance, and Data. Explain complex technical and analytical ideas clearly to executives so they can make decisions. Desirable Skills, Knowledge, and Experience: 8+ years in analytics, business intelligence, analytics engineering, or GTM/Services operations at a high-growth B2B SaaS or technology company. Direct experience supporting at least one of the following: Pre- or Post-Sales Operations, Solutions/Sales Engineering, Forward Deployed Engineering, Professional Services, or Customer Success. You understand how these teams work, how they're measured, and how their data is created. Deep data modeling expertise, including dimensional modeling, entity design, and metric layer design. You can review and challenge a data model, not just consume one. Expert SQL skills and hands-on experience with modern data stack tools such as BigQuery, dbt, or a semantic/metrics layer (for example dbt Semantic Layer, LookML, or Cube). Strong working knowledge of GTM and services systems data, such as Salesforce, professional services automation tools, and product usage or telemetry data. A clear, informed view on how AI changes analytics, including semantic layers, retrieval and context design for LLMs, text-to-SQL, and agent-based access to governed data, plus the data foundations those need to be accurate. A track record of defining and rolling out source-of-truth metrics across multiple stakeholder groups, including handling disagreements over definitions. Proven ability to lead complex, cross-functional programs without formal authority, and to influence executives and engineers alike. Excellent written and verbal communication skills, including turning ambiguous business questions into precise technical requirements and back again. BA/BS in a quantitative, technical, or business field. A Master's in Data Science, Analytics, Computer Science, or an MBA is a plus. Compensation Compensation may be adjusted depending on work location. Compensation may be adjusted depending on work location. For San Francisco Bay Area based hires: Estimated annual salary of $167,000 - $230,000. For New York City based hires: Estimated annual salary of $160,000 - $220,000. For Colorado - Remote based hires: Estimated annual salary of $146,000 - $200,000. Application Deadline: ~January 2027 Equity This role is eligible to participate in Cloudflare’s equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

About the role: The Global Alliance Lead is a senior individual contributor role reporting to the Global Head of GSI Relationships. The role involves owning the relationship with a leading technology and transformation partner end-to-end, from C-suite engagement to practitioner enablement and joint pipeline creation. The candidate will architect how the GSI and NewCo go to market together, ensuring the platform becomes the trusted data foundation inside the GSI’s agentic AI delivery practice globally. The role requires orchestration across sales, partner solution architecture, marketing, and partner operations. What You'll Do: - Own the global GSI relationship at partner and C-suite level, building trusted relationships with client, practice, and delivery team leads. - Define and execute a multi-year joint strategy positioning dbt + Fivetran as the default open data infrastructure layer within the GSI’s enterprise AI and agentic workflow delivery. - Represent NewCo at GSI’s internal forums, client briefings, and industry events. - Drive adoption of the dbt + Fivetran platform within GSI delivery teams, ensuring certification and active recommendation. - Embed NewCo's platform into GSI business groups, delivery architectures, RFP responses, and client proposals. - Design and execute enablement programs including certifications, reference architectures, use case playbooks, and joint delivery assets. - Partner with GSI marketing and alliances teams to develop joint go-to-market campaigns. - Support GSI in building client-facing agentic AI value accelerators with NewCo platform as the foundational data layer. - Source and develop new pipeline opportunities through the GSI relationship. - Drive co-sell motions alongside GSI account teams. - Maintain rigorous tracking of GSI-engaged pipeline. - Define and track signals indicating a healthy, high-performing GSI relationship. - Report regularly on alliance health, pipeline contribution, and strategic progress. - Identify risks and gaps early and mobilize resources to address them. What you will bring: - 15+ years of experience in strategic alliances, enterprise sales, or partner management within data, cloud, or enterprise software. - Experience managing complex global relationships with major consulting firms or GSIs at senior level. - Deep understanding of modern data stack and business value of open data infrastructure; experience with dbt, Fivetran, or equivalent preferred. - Ability to engage credibly at C-suite and partner level within global consulting organizations. - Strong commercial instincts to identify and develop joint pipeline opportunities. - Track record as a cross-functional orchestrator influencing sales, engineering, marketing, and operations. - Exceptional communication and storytelling skills. - Familiarity with AI, agentic workflows, data governance, and GSI operating models. - Willingness to travel globally. What Success Looks Like in Year One: - Defined joint strategy with GSI signed off at executive level. - Increased GSI practitioner certifications and platform deployments. - GSI-sourced pipeline contributing to revenue. - At least two joint go-to-market campaigns live. - Client-facing agentic value accelerators delivered. - Telemetry framework tracking alliance health and pipeline influence. Perks and Benefits: - 100% employer-paid medical insurance. - Generous paid time off including vacation, sick time, parental leave, holidays, and volunteer days. - RSU stock grants. - Professional development and training. - Company virtual happy hours, free food, and team-building activities. - Monthly cell phone stipend. - Access to mental health support platform. Additional Information: - The role qualifies for Fivetran’s incentive plan with total on-target earnings. - Compensation range for Denver location: $165,739 to $280,000 USD per year including OTE. - Remote work from Denver, Colorado, United States. - Commitment to diversity, equity, inclusion, and accommodations during interview process. To apply: https://weworkremotely.com/remote-jobs/fivetran-global-alliance-lead-capgemini

Location: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development. _______________________________________________________________________ WHAT YOU’LL DO - Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane - Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement - Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting - Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol - Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows - Lead architectural decisions and mentor engineers as the team scales - Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load - Contribute to roadmap planning, technical strategy, and cross-functional alignment KEY PROBLEMS YOU’LL HELP SOLVE - Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience - Making credential and identity handling for tool access both airtight and fast - Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed - Keeping latency low and reliability high as traffic scales from early adopters to production fleets - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ WHO YOU ARE Required Qualifications: - 6+ years of backend engineering experience with production-grade systems - Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design - Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines) - Fluency in Go, and/or Rust (both preferred) - Familiarity with AI/ML platforms or model serving infrastructure - A strong product mindset—you're excited about building developer-facing tools - Ownership mentality with a bias for shipping, learning, and iterating - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience Bonus Qualifications: - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture _______________________________________________________________________ WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $160,900 – $260,700 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: Remote - US Role Overview This is a senior individual contributor role with significant architectural ownership. You will set the technical direction for how Backblaze detects, correlates, and responds to infrastructure incidents across our data centers, and you will mentor other engineers on the team as that platform matures. If you have a passion for making complex distributed systems visible, you are comfortable making architecture decisions that will outlive your tenure, and you are excited about applying AI and agentic automation to infrastructure operations, this role was built for you.. Key Responsibilities Technical Leadership Set technical direction and standards for observability across the organization, including instrumentation conventions, alerting philosophy, and dashboard design patterns. Mentor engineers on the Observability team and act as a technical resource for SRE, Storage Engineering, and Network Engineering on observability practice. Lead design reviews for observability work and represent the team in cross-functional architecture discussions. Evaluate build-versus-buy decisions for observability and AIOps tooling, including data sovereignty and compliance considerations. Produce and maintain design documentation, runbooks, and architectural decision records that make the platform operable and extensible by future contributors. Observability Platform Own and evolve our metrics pipeline, including VictoriaMetrics, Prometheus, and the Consul-based service discovery layer that keeps scrape targets current as infrastructure scales. Own and expand our logging stack (OpenSearch, Logstash, and Filebeat) across all Backblaze data centers. Architect and expand distributed tracing with Jaeger and OpenTelemetry, extending coverage beyond the current application instrumentation to new services. Define and maintain Grafana dashboard standards for infrastructure, storage, and application performance visibility. Drive expansion of internal application telemetry in partnership with application teams to improve visibility. Define capacity and retention strategy for the telemetry stack as the fleet grows. Infrastructure & Automation Own infrastructure-as-code for observability stack deployments across multiple Kubernetes clusters. Write and review automated playbooks for configuration management and automation across Debian-based bare metal servers. Partner with the SRE team on Consul-based service discovery for VictoriaMetrics scrape target automation. Lead Ceph storage observability, including OSD health, performance metrics, and integration with alerting. Collaborate with the Network Engineering team on BGP, routing, and network-level observability. Required Qualifications 8+ years in a systems engineering, SRE, DevOps, or observability-focused role, including demonstrated technical leadership on a platform or infrastructure team. Deep hands-on experience with Prometheus, VictoriaMetrics, or equivalent metrics platforms, including PromQL, Alertmanager, and operating these systems at scale. Experience designing and operating log aggregation pipelines such as Elasticsearch/OpenSearch, Logstash, Filebeat, or similar. Working knowledge of distributed tracing (Jaeger, OpenTelemetry, or equivalent), including instrumentation strategy, not just operation. Proficiency in Python and/or Go for automation and tooling. Experience with Kubernetes, including deploying workloads and understanding pod networking and storage. Experience with infrastructure-as-code tooling and configuration management. Strong understanding of Linux internals, with Debian/Ubuntu preferred. Demonstrated experience mentoring engineers and raising the technical bar on a team. Excellent written and verbal communication skills. You'll work across engineering, SRE, security, and leadership, and you'll be expected to write design documents that drive decisions. Preferred Qualifications Experience leading the evaluation or deployment of AIOps tooling, including alert correlation, deduplication, or automated root cause analysis. Experience building, deploying, or operating AI agents or agentic AI systems. This is a strong differentiator. Familiarity with LLM APIs (Anthropic, OpenAI) or self-hosted LLM inference in an infrastructure context. Familiarity with Ceph storage, including OSD management, pool configuration, and CRUSH maps. Experience with incident management platforms. Familiarity with BGP, network observability, or working in multi-DC environments. Experience with secrets management in production environments. Experience operating in a regulated or compliance-driven environment. Prior experience in a storage-focused company or hyperscale infrastructure environment. What You'll Work On A telemetry stack spanning several data centers with exabytes of storage under observation. Real infrastructure at scale: Kubernetes, Ceph, Vitess, KVM, and a custom storage platform serving hundreds of thousands of customers. A collaborative team that values engineering excellence, transparency, and operational rigor. Pay Transparency To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The expected salary range for this role is $178,000 - $200,000 plus 10% target annual bonus and RSUs. At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer.

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Data Engineer II to join our Engineering team, with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS. Where you will work: This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Build, optimize, and maintain data pipelines that power our business Define and build out abstracted reusable data sets to be used for Business Intelligence, Marketing, and Data Science Research Design, build, and evangelize a federated data validation framework to be used to monitor potential data inconsistencies Protect our users’ privacy and security through best practices The ideal candidate has: 2+ years of software/data engineering experience (distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality). Expertise in SQL and Python Expertise in building scalable data pipelines, query optimization, data modeling, and defining reusable datasets Experience working with orchestration tools (especially Airflow), databases (especially PostgreSQL), data warehouses (especially Snowflake) Familiarity with SQL tuning, medallion/event-driven architectures, and telemetry. Familiarity with healthcare or insurance Familiarity with data security and HIPPA compliance A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. What you'll get here: You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Postgres/SQL, Snowflake, Python, AWS, Terraform, Argo, Airflow, Spark, DuckDB, Iceberg, Airbyte, DBT, ElasticSearch (aka OpenSearch), OpenTelemetry, Looker This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare. Compensation Transparency: The target salary range for this position is $ 138,000 - $160,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: Vancouver, BC Senior Analytics Engineer The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call . As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Vancouver office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . What you’ll achieve Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, and where to find it. Partner with peers across DS&A to keep KPI definitions consistent where domains overlap. Author data contracts and SLAs at the Silver→Gold boundary, partnering with Horizontal Data Engineering on the inputs you depend on, and owning data quality, freshness, and oncall for Gold/metric-mart failures in your domain. Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products rather than one-off builds. Partner directly with Product & Business, Data Science, and Engineering to turn ambiguous, underspecified questions into scalable datasets — anticipating downstream reporting impacts before they become incidents, and raising the data-model quality bar across the domains you touch. About you Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making . 4+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions . Advanced SQL and strong data modeling fundamentals: dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design. Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred). Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning. Demonstrated domain fluency in at least one business area (e.g. PLG funnels, SLG pipeline, marketing attribution, Product telemetry, revenue/ARR) and the judgment to translate "I don't trust this number" into a specific, durable model fix. Strong cross-functional partnership skills: requirement gathering, prioritization, documentation and enablement, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical partners . Curiosity about AI-native a nalytics — NL2SQL, metadata/semantic layers for self-serve, and using tools like Claude and Genie to multiply your reach rather than replace rigor. Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation (Salesforce, Marketo, Gainsight) is a plus At A sana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission . If you're interested in this role and don't meet every listed requirement, we still encourage you to apply . What we’ll offer Generous, transparent and fair compensation system (base salary and RSUs) Health insurance with dental Breakfast and lunch catering on the da ys that you work from the office Home office setup budget Gym/Fitness card Fertility healthcare and family-forming support with Carrot Mental Health Support in Modern Health Group life insurance MacBo oks with all necessary accessories For this role, the estimated base salary range is between $106,000 - $120,000 CAD annually . The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process . The listed range above is a guideline, and the base salary range for this role may be modified . In addition to base salary, your compensation package may include additional components such as equity and sales incentive pay (for most sales roles), and benefits . If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role . #LI-Hybrid About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: US, San Diego, CA Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE As an Autonomy Engineer focused in VLA Pre-training, you will work on all aspects of training capable policies. You'll pre-train base models on a diverse, multi-embodiment corpus of trajectories, fine-tune policies to excel at specific tasks, shape data collection processes, and explore effective ways to generate and use synthetic data. This is primarily a deep learning role, so we're looking for experience solving real-world problems with modern neural networks. Robotics experience isn't strictly required, but if you're coming from outside the field, be prepared to get up to speed on a new domain quickly.   WHAT YOU'LL DO - Post-train policies via behavior cloning and RL; own the full loop from data to deployment. - Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage. - Work closely with external partners to ensure steady supply of high-quality pretraining-scale data. - Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes. - Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining. - Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‑time edge inference. WHAT WE'RE LOOKING FOR - 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it. - Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference. - Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies. - Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. - Familiarity with modern software engineering practices. - You document experiments clearly and communicate trade‑offs crisply. NICE TO HAVE - Robotics or autonomous driving experience. - Experience applying RL to LLMs or robotics. - Experience with VLA (vision-language-action) models. - Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization). - Publications at top-tier deep learning conferences or equivalent open‑source contributions. - Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks. WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with employer match. - Equity included–we believe builders should share in what they build. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives. For this role in California, the expected base salary range is $180,000–$300,000 USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Location: San Francisco, California; New York, New York Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE: Notion is looking for an experienced Lifecycle Marketing Manager, Campaign Strategy & Execution to develop and execute campaigns that help users discover value, adopt key workflows, and deepen their use of Notion. You'll own campaigns end to end: translating business and customer opportunities into clear strategies, defining audiences and journeys, coordinating creative and technical production, launching across email and in-product channels, and measuring incremental impact. This role combines strategic judgment with hands-on execution. You'll partner closely with Lifecycle Marketing, Product Marketing, Product Growth, Data Science, Marketing Operations, and creative partners. You should be equally comfortable shaping a campaign brief, building a journey in Customer.io http://Customer.io, resolving execution details, and interpreting results. Scope guardrails: this role owns campaign strategy, hands-on execution, cross-functional delivery, and performance analysis. It is not the primary Customer.io http://Customer.io architect or incident-response owner, a general intake coordinator, or a production-only role receiving prewritten briefs. The person should operate as an independent campaign owner who can take work from an ambiguous opportunity to a high-quality, measured launch. This role may be based in either our San Francisco or New York City offices. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. WHAT YOU'LL ACHIEVE: - Own the campaign portfolio. Independently lead a portfolio of launch, one-off, and evergreen lifecycle campaigns with clear prioritization and predictable delivery. - Turn opportunities into strategies. Translate product launches, lifecycle moments, and business priorities into clear objectives, audiences, journeys, channel plans, and success metrics. - Build high-impact lifecycle programs. Develop campaigns across onboarding, activation, adoption, collaboration, monetization, retention, and resurrection. - Execute from brief to measurement. Own audience creation, build, QA, localization, launch readiness, and post-campaign analysis across email and in-product messaging. - Improve foundational journeys. Audit existing programs and recommend which should be maintained, improved, rebuilt, or retired; lead the rebuild of priority onboarding or adoption journeys. - Raise the experimentation bar. Develop testable hypotheses and use segmentation, personalization, holdouts, and A/B tests to understand incremental impact. - Measure customer and business outcomes. Connect campaigns to activation, product adoption, collaboration, conversion, retention, or qualified sales outcomes—not only opens and clicks. - Lead cross-functional delivery. Coordinate dependencies across Product, Engineering, Data Science, Product Marketing, Marketing Operations, Demand Generation, Sales, and external partners. - Create repeatable systems. Turn recurring campaign work into templates, playbooks, and reusable operating patterns that improve quality and velocity. - Enable safe self-service. Help cross-functional partners execute effectively while maintaining Lifecycle's strategic, customer-experience, and quality standards. SKILLS YOU'LL NEED TO BRING: - Significant experience owning lifecycle, CRM, growth, or product-marketing campaigns from strategy through execution. - A track record of independently leading complex, cross-functional campaigns at meaningful scale. - Strong customer-journey thinking across activation, adoption, engagement, conversion, and retention. - Hands-on experience with a lifecycle platform such as Customer.io http://Customer.io, Braze, Iterable, or Salesforce Marketing Cloud. - Strong audience segmentation, personalization, experimentation, and campaign-measurement skills. - Ability to use data to prioritize opportunities, evaluate results, and change strategy; working knowledge of SQL or self-serve analytics is a plus. - Excellent project leadership: clear briefs, dependable execution, proactive risk management, and crisp stakeholder communication. - Strong editorial and customer judgment—you care about sending useful, relevant messages rather than maximizing message volume. - Comfort operating in a product-led, highly cross-functional environment with incomplete information. - Experience with B2B or product-led growth, product telemetry, in-product messaging, or AI-assisted campaign workflows is a plus. - 8+ total years relevant + transferrable experience. WHAT SUCCESS LOOKS LIKE IN THE FIRST SIX MONTHS: - Establish a clear operating rhythm for launch, one-off, and evergreen campaigns. - Independently own a meaningful portfolio from strategy through performance analysis. - Launch a materially improved onboarding, activation, or adoption journey with a defined experiment and measurement plan. - Establish consistent briefs, segmentation standards, QA, launch-readiness checks, and post-campaign readouts. - Demonstrate credible incremental movement in a product or business outcome. - Create meaningful capacity for senior Lifecycle teammates to focus on systems architecture, journey strategy, personalization, and modernization. Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco or New York City, the estimated base salary range for this role is $150,000 – $220,000 per year. By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy https://notion.notion.site/Notion-Global-Recruiting-Privacy-Policy-fc3eb4e829354a26a2bb6fd5e289b550?pvs=74 and NYLL 144 https://notion.notion.site/Ashby-AI-Bias-Audit-2b0efdeead05803bbbfae159ec86c528. #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: Cambridge / Hybrid Workplace: hybrid Frontier is an independent video game developer and publisher, crafting immersive gaming experiences with fun gameplay and unparalleled artistic quality. Renowned for its iconic creative management simulation games, Frontier captivates players worldwide with immersive and authentic game worlds. The modern studio is located in the vibrant technology hub of Cambridge (UK). The talented team at Frontier are dedicated to nurturing our existing portfolio and delivering our exciting future roadmap.    This role is offered on a full in-studio basis or a hybrid basis (minimum 3 days per week in the studio). We can provide a comprehensive relocation support package as part of any offer, should you need to relocate.  WHAT'S THE ROLE? We’re looking for a Senior Game Designer to join our teamandbring their expertise in game designto help create engaging, player first experiences for our creative management simulation titles.  As a Senior Game Designer, you will take ownership of significant game features, and work collaboratively with other disciplines to turn great ideas into compelling experiences that players love. Interview Process Please note that candidates invited to interview may be asked to complete a role-related assessment in their own time as part of the selection process. Further details regarding the expected time commitment will be provided in advance. WHAT YOU'LL BE DOING Design and iteration of complex game features Implementing and refining game content using in-house tools Building alignment and understanding of game features with clear verbal and written communication Ensuring games systems are balanced using analytical methods and incorporating game telemetry Driving quality using playtests, player feedback, QA reporting, and your own insights WHAT YOU'LL BRING Deep game knowledge across a range of genres Strong commercial game design experience throughout the product lifecycle on PC & console Solid understanding of player psychology and gamer motivations Excellent communications skills; ability to present your ideas clearly in verbal and written form Effective collaboration with both team members and external stakeholders BONUS IF YOU HAVE Good knowledge of simulation and management games Knowledge of UI/UX design principles Experience developing tutorials and first-time user flows Experience in coaching and mentoring team members WHAT WE CAN OFFER YOU You will work with talented and passionate people to support, develop or publish our sophisticated and enduring games, in a creative, collaborative and inclusive environment. We love what we do, and we work hard to provide outstanding experiences for our players.  Wellbeing is a big focus at Frontier, and we are continually evolving how we can support our people. We encourage a healthy work/life balance and provide a range of wellbeing activities, initiatives and sessions to support both mental and physical health.   We offer a competitive salary and benefits package, which includes a success-based annual bonus, share option schemes, life assurance, private family healthcare, flexitime working hours, enhanced maternity/paternity leave, in-house subsidised catering, support with relocation, a Cycle to Work scheme, free bike servicing, and social activities and events.  We strive to create an environment where everyone can fully demonstrate their capability and potential. If you therefore need any reasonable adjustments to support you during the recruitment process, please speak to your Talent Acquisition representative.   For queries, please email: recruitment@frontier.co.uk

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. The Opportunity: Grafana Labs is seeking a Senior Partner Solutions Engineer to join its high growth startup environment and help scale cloud partnerships, with a dedicated focus on joint go to market activities with Cloud Service Providers (CSP) including Amazon Web Services (AWS) and Google Cloud (GCP). The successful candidate will be instrumental in enabling partner success through education, enablement, direct engagement, support of events, and build content that helps our CSP’s position and demonstrate Grafana capabilities. What You’ll Be Doing: Partnering with Channel Sales and Field Sales to convey Grafana’s vision, value, and technical strategy to cloud partners Leading technical engagement with partners to drive deal progression and close opportunities Delivering product demos, technical presentations, and hands-on enablement sessions Develop and deliver training, onboarding, and ongoing education for solutions architects, and technical teams Represent Grafana Labs through technical presentations, live demos, webinars, conference sessions, and regional partner events Create reference architectures, demo environments, solution guides, and presentations that explain the value of Grafana Cloud alongside cloud provider services. Track partner readiness, reuse of technical assets, and progress of joint opportunities, and bring partner insights back to product and GTM teams Shaping and expanding the reach of Grafana Partner University across multiple partner personas Collaborating with internal teams to provide product and competitive feedback Support selling motions like Sell-To, Embedded, and PoweredBy, either directly or jointly with partners Run high impact workshops and 1:1 training to generate and progress pipeline Travelling up to 50% to support cloud partner events, workshops, and field activities What Makes You a Great Fit: Located: United States (Remote) 6+ years in pre-sales or solution architecture, ideally within the observability space Strong experience selling SaaS software across the NORAM region Proven use of MEDDIC or similar qualification frameworks Excellent communication and interpersonal skills, especially in remote, global teams Demonstrated ability to operate in a fast-paced, ambiguous, startup environment Strong judgement, leadership, and problem-solving abilities Passion for education, enablement, and helping others succeed technically Bonus Points For: Experience with CSP’s and a strong understanding of their core infrastructure services. Experience with cloud marketplaces, co-selling, or joint solution launches. Solid understanding of observability and cloud native tooling Background in OSS first companies Experience with Grafana, Prometheus, and Loki Hands-on experience deploying and operating Kubernetes Bachelor’s degree in CS, IT, Math, or related field (or equivalent experience) Compensation & Rewards: In the United States, the OTE (On-Target Earnings) compensation range for this role is $204,000 - $244,000 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we're interested in candidates based in the US or Canada. Residents of Quebec are not eligible for this role. Senior Full-Stack Software Engineer, Grafana Data Source Plugins The Opportunity: As a Senior Full-Stack Engineer in the Grafana Data Source Plugins squad, you will take a leading role in developing and enhancing a diverse portfolio of data source plugins that retrieve the data powering Grafana dashboards used by teams worldwide. Our team focuses on continuously improving data source plugins, ensuring seamless experience for human and agent users alike. A key aspect of this role is guaranteeing the smooth operation and reliability of our plugins in the Grafana Cloud, helping us deliver on our commitment to world-class observability tools. What You’ll Be Doing: Some data source plugins we own: Prometheus, Loki, Infinity, MySQL, PostgreSQL, AWS Cloudwatch, and Clickhouse.  The full catalog is listed here . A typical “day in the life” could include: Building or improving Grafana plugins to integrate third party services or databases into Grafana Supporting the operations and reliability of our plugins in Grafana Cloud Coming up with suggestions for process improvements Integrating data sources with agentic workflows such as Grafana Assistant Providing technical support in customer escalations Working closely with the rest of the Grafana Division What Makes You a Great Fit: You know how to transform ideas into working code, you are able to design a solution, get feedback and deliver large projects. You are a self-driven individual who understands the power of feedback loops in making roadmap decisions and driving our product forward. You are a motivated self starter with a bias towards action, and willing to take on any challenge You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You are an excellent communicator and you enjoy collaboration You are comfortable working in a remote-first company Requirements: Solid experience with Golang & Typescript Experience with Kubernetes & microservices Experience writing clean, robust, and performant software that is easily maintained by others Experience participating in an on-call rotation and performing operations/SRE tasks Bonus Points For: You have been a user of Grafana and Grafana Data Sources You have expertise in one of the underlying databases we support You have strong experience working with a Product Manager or external stakeholders In the United States, the Base compensation range for this role is CAD 170,247 - $204,297 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . #LI-Remote #LI-Remote *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote position. We are seeking candidates in US and Canada. The Opportunity: We build Tempo , the open-source distributed tracing backend behind Grafana Cloud Traces and Grafana Enterprise Traces (GET). Tempo makes it easy to search traces, generate metrics from spans, and connect tracing data with logs, metrics, and profiles across the Grafana stack. 2026 is an inflection point for Tempo. After a major architectural upgrade and the launch of TraceQL metrics, we are shifting from foundational work to product and operational excellence, and evolving Tempo from a SaaS database into a platform that powers Grafana’s next generation of observability products (App Observability, Asserts, Traces Drilldown, and AI-driven assistants). Over the next year, you will help us: Make Grafana Cloud Traces “just work” for customers by eliminating rough edges, confusing limits, and hidden failure modes. Achieve operational excellence at scale as we grow from close to 50 cells today into triple digits this year, with autoscaling, parameterized rollouts, and aggressive toil reduction. Evolve Tempo into a platform enabler: higher-density APIs, trace aggregation, TraceQL metrics math, and machine/LLM-friendly interfaces that downstream products and agents can build on. Push performance further: faster query latency at hundreds of MB/s ingestion and performant 30-day query ranges to match competitors. Prepare Tempo for an agent-driven world: larger, burstier, higher-cardinality workloads, and new categories of AI-powered workflows, such as assistant-driven triage and “why is this slow?”- style investigations. What You’ll Be Doing: As a Senior Engineer on Tempo, you will own technical direction on the hardest problems in our roadmap and raise the bar across the team. Deliver significant technical projects. Take well-scoped, multi-month initiatives from problem framing through rollout, e.g., trace aggregation APIs, Limitless Tempo, autoscaling cells and customer limits, or query engine improvements. Partner with Staff engineers and the tech lead on broader, cross-team direction. Own major components of Tempo. Contribute to and own parts of ingestion, storage, query, and metrics generation. Write and present design docs, participate in design reviews, make sound trade-offs on performance, cost, and complexity, and document the “why” for the team. Build APIs for humans and agents. Help shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably. Contribute to operational excellence. Own outcomes for the areas you build against concrete SLOs (P99 write latency, incident recurrence, TCO per ingested GB), and help move the team toward Zero Ops through automation, parameterized rollouts, and actionable alerts. Collaborate with Product and sibling teams. Work with PMs and with App Observability, Asserts, Drilldown, and Grafana Assistant teams to understand how Tempo gets consumed and to ship what unblocks them. Mentor and support engineers. Raise the bar through thorough code review, constructive design feedback, and pairing, especially with junior and mid-level engineers. Participate in on-call for the services you help build, and contribute to incident response and post-incident learning. Contribute to open source. Tempo is OSS. You will engage the community, review external contributions, and contribute to the project in the open. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. Example problems you could work on These are the kinds of projects landing in 2026: Trace aggregation and higher-density APIs: extend TraceQL metrics, design LLM-friendly response types, and make Tempo a first-class data source for Grafana’s AI assistant. Autoscaling end-to-end: customer limits and Tempo cells, with hysteresis, predictive scaling for spikes, and safe scale-down. Agent-scale ingestion and query: guardrails for bursty, high-cardinality, agent-generated workloads. Query performance: new data formats, smarter query pipelines, targeted optimizations for common Drilldown and Traces workflows, and 30-day query ranges. Rollouts and multi-cell operations: parameterized rollouts, push-button deploys, and the tooling to grow safely into triple-digit cell counts without a proportional increase in alert noise. Limits and self-service: drive customer-facing configuration and observability so escalations trend toward zero. What Makes You a Great Fit: Technical ownership. A track record of delivering complex, multi-month projects that spanned design, delivery, and operations, and of helping the teammates around you grow. Solid systems experience. Significant hands-on experience building and operating distributed data systems in production: ingestion pipelines, storage engines, query execution, or similar. Strong software craftsmanship. You write clean, robust, performant software that others can maintain, and you know when to optimize vs. when to ship. Strong Go, or a path to it. We write Tempo in Go. Solid experience in other systems languages (Rust, C, C++) translates well. Operational mindset. You’ve owned production services, carried a pager, reduced toil, and treated SLOs as a product feature, not a chore. Customer focus and pragmatism. You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. Collaboration and clear writing. You contribute through design docs, reviews, and shipped code, and you communicate clearly in a fully remote, asynchronous environment. Bonus Points For: Experience with tracing, OpenTelemetry, or large-scale observability systems. Experience designing query languages, SQL/TraceQL-like engines, or APIs intended to be consumed programmatically (by services or agents). Experience with columnar storage formats (e.g., Parquet) or purpose-built on-disk formats for analytical workloads. Experience operating multi-tenant, multi-cell SaaS infrastructure at scale on Kubernetes. Experience building for AI/LLM consumers: structured APIs, metadata/discovery endpoints, deterministic outputs, evaluation harnesses. Open-source contribution or maintainership, and comfort engaging a community in the open. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. How we work We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our senior engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. In US, the OTE (On-Target Earnings)/Base compensation range for this role is USD $167,143 - $200,572. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote position. We are seeking candidates in US and Canada. The Opportunity: We build Tempo , the open-source distributed tracing backend behind Grafana Cloud Traces and Grafana Enterprise Traces (GET). Tempo makes it easy to search traces, generate metrics from spans, and connect tracing data with logs, metrics, and profiles across the Grafana stack. 2026 is an inflection point for Tempo. After a major architectural upgrade and the launch of TraceQL metrics, we are shifting from foundational work to product and operational excellence, and evolving Tempo from a SaaS database into a platform that powers Grafana’s next generation of observability products (App Observability, Asserts, Traces Drilldown, and AI-driven assistants). Over the next year, you will help us: Make Grafana Cloud Traces “just work” for customers by eliminating rough edges, confusing limits, and hidden failure modes. Achieve operational excellence at scale as we grow from close to 50 cells today into triple digits this year, with autoscaling, parameterized rollouts, and aggressive toil reduction. Evolve Tempo into a platform enabler: higher-density APIs, trace aggregation, TraceQL metrics math, and machine/LLM-friendly interfaces that downstream products and agents can build on. Push performance further: faster query latency at hundreds of MB/s ingestion and performant 30-day query ranges to match competitors. Prepare Tempo for an agent-driven world: larger, burstier, higher-cardinality workloads, and new categories of AI-powered workflows, such as assistant-driven triage and “why is this slow?”- style investigations. What You’ll Be Doing: As a Senior Engineer on Tempo, you will own technical direction on the hardest problems in our roadmap and raise the bar across the team. Deliver significant technical projects. Take well-scoped, multi-month initiatives from problem framing through rollout, e.g., trace aggregation APIs, Limitless Tempo, autoscaling cells and customer limits, or query engine improvements. Partner with Staff engineers and the tech lead on broader, cross-team direction. Own major components of Tempo. Contribute to and own parts of ingestion, storage, query, and metrics generation. Write and present design docs, participate in design reviews, make sound trade-offs on performance, cost, and complexity, and document the “why” for the team. Build APIs for humans and agents. Help shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably. Contribute to operational excellence. Own outcomes for the areas you build against concrete SLOs (P99 write latency, incident recurrence, TCO per ingested GB), and help move the team toward Zero Ops through automation, parameterized rollouts, and actionable alerts. Collaborate with Product and sibling teams. Work with PMs and with App Observability, Asserts, Drilldown, and Grafana Assistant teams to understand how Tempo gets consumed and to ship what unblocks them. Mentor and support engineers. Raise the bar through thorough code review, constructive design feedback, and pairing, especially with junior and mid-level engineers. Participate in on-call for the services you help build, and contribute to incident response and post-incident learning. Contribute to open source. Tempo is OSS. You will engage the community, review external contributions, and contribute to the project in the open. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. Example problems you could work on These are the kinds of projects landing in 2026: Trace aggregation and higher-density APIs: extend TraceQL metrics, design LLM-friendly response types, and make Tempo a first-class data source for Grafana’s AI assistant. Autoscaling end-to-end: customer limits and Tempo cells, with hysteresis, predictive scaling for spikes, and safe scale-down. Agent-scale ingestion and query: guardrails for bursty, high-cardinality, agent-generated workloads. Query performance: new data formats, smarter query pipelines, targeted optimizations for common Drilldown and Traces workflows, and 30-day query ranges. Rollouts and multi-cell operations: parameterized rollouts, push-button deploys, and the tooling to grow safely into triple-digit cell counts without a proportional increase in alert noise. Limits and self-service: drive customer-facing configuration and observability so escalations trend toward zero. What Makes You a Great Fit: Technical ownership. A track record of delivering complex, multi-month projects that spanned design, delivery, and operations, and of helping the teammates around you grow. Solid systems experience. Significant hands-on experience building and operating distributed data systems in production: ingestion pipelines, storage engines, query execution, or similar. Strong software craftsmanship. You write clean, robust, performant software that others can maintain, and you know when to optimize vs. when to ship. Strong Go, or a path to it. We write Tempo in Go. Solid experience in other systems languages (Rust, C, C++) translates well. Operational mindset. You’ve owned production services, carried a pager, reduced toil, and treated SLOs as a product feature, not a chore. Customer focus and pragmatism. You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. Collaboration and clear writing. You contribute through design docs, reviews, and shipped code, and you communicate clearly in a fully remote, asynchronous environment. Bonus Points For: Experience with tracing, OpenTelemetry, or large-scale observability systems. Experience designing query languages, SQL/TraceQL-like engines, or APIs intended to be consumed programmatically (by services or agents). Experience with columnar storage formats (e.g., Parquet) or purpose-built on-disk formats for analytical workloads. Experience operating multi-tenant, multi-cell SaaS infrastructure at scale on Kubernetes. Experience building for AI/LLM consumers: structured APIs, metadata/discovery endpoints, deterministic outputs, evaluation harnesses. Open-source contribution or maintainership, and comfort engaging a community in the open. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. How we work We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our senior engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. In Canada, the OTE (On-Target Earnings)/Base compensation range for this role is CAD $170,247 - $204,297. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .