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Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Location: Brazil; Peru; Sweden; Colombia; Argentina; Romania; Malta; Slovenia; Lithuania; Czech Republic; Estonia; Hungary; Mexico; Chile; Poland; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Pro Verifications team decides whether a business signing up on the Pro side is who it says it is, and whether we're allowed to onboard it. That means figuring out who actually owns the business, running it against sanctions and watchlists, and doing all of it fast enough that a real customer doesn't lose patience and leave. Every Pro customer hits these systems, so slow or wrong is very visible — and the team is early, which means whoever joins gets to decide how a lot of it works instead of inheriting it. How We Work - We deploy constantly, almost always behind a flag, in pieces small enough to pull back fast. - Security and compliance show up at design time, not as a gate at the end. - Every story is tied to a metric it's meant to move — if work isn't on the board, it doesn't get staffed. - At this level, you're expected to shape these standards, not just work inside them.   THE OPPORTUNITY As a Staff Engineer on Pro Verifications, you'll own the technical direction for how verification is built here — the architecture, the patterns other engineers work inside, and the calls about what we own versus what we lean on a vendor for. You'll be hands-on across the stack, drive out entire classes of recurring failure rather than patching them one at a time, and design the fail-closed and audit behavior that keeps regulators satisfied. This is a high-impact, hands-on technical leadership role for engineers who've built where being wrong has real consequences, and who want to shape a system that stays fast, safe, and defensible as it grows. - Set the shape of the verification services and their contracts across the KYC/KYB flow. - Decide how we abstract KYC and KYB vendors so a bad provider day doesn't turn into an outage. - Design fail-closed behavior and audit trails that hold up under regulatory scrutiny. - Identify the classes of failure that keep recurring and remove them for good. - Write and drive architecture decisions (ADRs), and hold the line on security and compliance at design time, not as a late gate. - Mentor and raise the bar for senior engineers through design reviews, code, and direct feedback. - Be measured on whether verification gets faster, more of it decides itself, fewer decisions are wrong, and the systems stay up — and on whether the team got stronger for you being on it.   WHAT YOU BRING - Around eight years building and running production systems, with a track record of owning a domain's technical direction, not just delivering inside one. - Deep, fluent expertise in Rust, with the versatility to work across TypeScript and React where verification meets the customer. - You've set architecture other people build on, and it held up — you can point to specific classes of failure you designed out, not just incidents you fixed. - You've made teams faster through patterns, tooling, or mentoring — engineers around you got better and shipped more because of calls you made. - You've built where being wrong had real consequences: compliance, payments, security, or anywhere a bad call costs more than a rough user experience. - Strong on distributed systems, service contracts, and secure design — you've integrated third-party APIs that couldn't be trusted, with real timeouts, retries, idempotency, circuit breakers, and backup paths that actually get tested. - Comfortable with, or able to quickly ramp on, gRPC, Temporal, Docker, Kubernetes, Terraform, MySQL/MariaDB, Redis, and GitLab CI.   NICE TO HAVES - Direct experience with KYC, KYB, or fraud work, including integrating providers like Trulioo, Persona, or ComplyAdvantage. - Comfort building with AI in the loop. - Time spent in crypto, fintech, or another space regulators pay close attention to.         Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

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: The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. And we build for scale: serving thousands of ML classifiers, for all requests on the token generation path, and for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond. We’re growing the team and looking for engineers who have deep expertise in productionizing ML systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. And your tooling and infrastructure will be used for every model launch, which are becoming more complex, and more frequent. Responsibilities: Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards Implement automated testing, deployment, and rollback systems for ML models in production safety applications Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs Contribute to the development of internal tools and frameworks that accelerate safety research and deployment You may be a good fit if you: Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads Have built automated or self-service deployment pipelines and eval infrastructure allowing researchers to roll out classifiers and models independently Have implemented A/B testing frameworks and experimentation infrastructure for ML systems Are results-oriented, with a bias towards reliability and impact in safety-critical systems Enjoy collaborating with researchers and translating cutting-edge research into production systems Care deeply about AI safety and the societal impacts of your work Strong candidates may also have experience with: Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment Working with large language models and modern transformer architectures Developing monitoring and alerting systems for ML model performance and data drift Experience in trust & safety, fraud prevention, or content moderation domains Knowledge of privacy-preserving ML techniques and compliance requirements 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. 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: 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: The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down. What you'll do: Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines. Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through. Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow. Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization. You may be a good fit if you: Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation. Have a strong foundation in distributed systems: replication, consistency tradeoffs, failure modes, and SLO management under load. Design systems for graceful degradation: you plan for a slow dependency, a dropped stream, or a half-rolled-out deploy before it happens, and build so the system degrades predictably instead of failing. Have successfully shipped broad or all-encompassing changes to mission critical systems (e.g., database migrations, interface changes, rewrites). Strong candidates may also have: 8+ years of industry software engineering experience. Familiarity with LLM inference systems and transformer-based models (not required, but a plus). 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. 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: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior or Staff Backend Engineer with the Database Excellence group , you'll build and evolve database automation and PostgreSQL as a service capabilities for GitLab. The level will be determined during the hiring process. You'll use Go to automate the full lifecycle of PostgreSQL across GitLab's infrastructure, making database operations safer, more consistent, and easier to scale for databases that sit behind high-throughput, always-on internet services. You'll work closely with partner teams to shape how GitLab provisions and manages PostgreSQL in a fully remote, highly collaborative environment. Some examples of our projects: SQL Traffic Replay Tooling , which validates upgrades and changes against real production workloads. PostgreSQL as a Service Platform , which provides standardized, automated provisioning and lifecycle management for internal product databases. PostgreSQL Major Version Upgrade Automation , which supports safe, repeatable major upgrades at GitLab.com scale. What you’ll do Design, build, and maintain Go-based automation that manages the full PostgreSQL lifecycle, including provisioning, configuration, upgrades, failover, scaling, and decommissioning, reducing reactive operational work that currently takes more than 80% of the team's time. Build automation that works across infrastructure-as-code tooling and cloud infrastructure, and evaluate operator-based approaches as the platform evolves. Use AI agents as a regular part of building and operating services, including implementation, review, and reducing repetitive work, while keeping the context agents need in the repository so the whole team can build on it. Build for internet scale by designing automation and services for high-throughput, always-on production workloads, where GitLab.com traffic sets the bar for correctness, latency, and availability. Integrate compute, storage, networking, identity and access management, and managed data services across cloud providers into one coherent PostgreSQL platform instead of creating bespoke setups for each database. Build GitLab's PostgreSQL as a service platform to replace bespoke database setups with standardized, automated provisioning and lifecycle management, so supporting more databases doesn't require growing the operations team at the same rate. Collaborate closely with product management, infrastructure, software delivery, and other engineering teams to design and ship high-performing solutions. Research, design, and implement improvements to PostgreSQL performance, scalability, and data health, helping maintain more than 8 months of operational runway for all critical database saturation points. Review database automation and Go changes from other engineers and contributors, with attention to safety, maintainability, and performance. Document automation practices, PostgreSQL operational patterns, and guidance that helps engineers use and contribute to the platform. Build safe, repeatable automation for PostgreSQL major version upgrades at GitLab.com scale, validating changes against real production traffic before rollout. Operate what you build in production from end to end, using production feedback to guide each iteration. What you’ll bring Professional software engineering experience working with PostgreSQL in large, complex production environments, including experience building or operating a database-as-a-service product. Proficiency with Go, including designing, implementing, testing, and reviewing backend services. Experience developing Kubernetes operators, controllers, or similar automation for the lifecycle of stateful services, especially databases. Kubernetes experience is one way to demonstrate this skill, but isn't required; comparable experience building database or infrastructure automation is welcome. Comfort with infrastructure as code and core database operations concepts such as high availability, replication, backups, and system-level performance trade-offs. Familiarity with Ruby is a plus but isn't required. Much of GitLab's application codebase uses Ruby on Rails, and being able to read it helps when designing automation that application teams depend on. We’ll expect you to become comfortable with it on the job, not on day one. Strong written communication skills and comfort working asynchronously in an all-remote, distributed team. Self-directed work style with effective organizational skills, the ability to manage priorities as a "manager of one," and alignment with GitLab's values of transparency, collaboration, inclusion, and open source contribution, as well as its operating principles . Ownership of the technical direction for a major initiative such as the PostgreSQL as a service platform, turning an ambiguous problem into an architecture and a sequenced plan that several engineers can execute in parallel. Influence beyond the team, setting the patterns other engineers follow, partnering with sibling database, infrastructure, and platform teams, and growing engineers through design reviews and mentorship. About the team The Database Excellence group keeps GitLab’s databases running reliably through proactive health management, operational excellence, and strategic enablement. We maintain operational runway by identifying and addressing saturation points, operate infrastructure through automated and scalable processes, and provide tools and frameworks that help teams build features sustainably. Our primary focus is GitLab.com, and we're expanding our scope to provide database health frameworks and tooling that benefit self-managed customers as well. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

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 Staff Machine Learning Operations Engineer to join our Platform Engineering team . This role will report to the VP of Platform Engineering . As Garner's foundational dedicated MLOps Engineer, you will assume responsibility for the reliability, performance, and cost-efficiency of our production machine learning systems. You will lead the development of a robust platform designed to facilitate the secure and consistent deployment of models by our machine learning and data science teams. Given that these models directly influence health outcomes and cost-effectiveness for millions of patients, maintaining the highest standards of production quality is imperative. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Own the reliability, performance, functionality, and cost-efficiency of Garner's production ML systems, including establishing SLOs, observability, and on-call responsibilities. Architect Garner's ML platform including required data infrastructure (including feature store, model registry and CI/CD for models), and standardized service patterns. Implement ML-specific CI/CD pipelines: Transition our deployment process from manual notebook hand-offs to automated, PR-driven CI/CD workflows that include automated data quality checks and statistical model validation prior to deployment. Drive down cost and latency through improved architecture, hardware choices, and model optimization as appropriate. Lay the foundation for a future Garner MLOps team, including workflows, standards, and KPIs that enables rapid teammate onboarding and helps stakeholders and teammates quickly identify the health of the team’s products, allowing engineers to focus on areas where issues reside Establish Drift Monitoring: Design and implement automated data drift and concept drift monitoring systems that alert the team when models degrade, laying the groundwork for future Continuous Training (CT) architectures The ideal candidate has: 7+ years of software engineering experience, with significant time spent operating ML or data-intensive systems in production at scale. Deep experience with the modern ML production stack: model serving (e.g., Sagemaker, Triton, or equivalent), feature stores, model registries, and CI/CD for ML. Strong infrastructure and platform engineering fundamentals: Kubernetes, containerization, cloud (AWS preferred), Terraform/IaC, observability, and incident response. Experience designing ML platforms or significant components of one (not strictly consuming SaaS) and the judgment to know when to build vs. buy. Strong collaboration with ML, data, platform engineers, data scientists, and product engineering teams, with the ability to set technical direction as the most senior MLOps voice in the org. Healthcare, regulated-data, or other high-stakes production ML experience is a plus but not required. 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 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: Python, Kubernetes, AWS, Sagemaker, Terraform, S3, Snowflake, Airflow, Datadog 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 $298,000 - $351,000. 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), 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: United Kingdom (Hybrid); United Kingdom (Remote); Spain Workplace: Hybrid Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 MEET THE TEAM 👥 Here at Cleo, we have ~200 Engineers organised into Pillars. ✨ Our stack spans a Ruby on Rails monolith, a single React Native (TypeScript) app frontend, Python for machine learning services, and PostgreSQL, all hosted on AWS and shipped through Kubernetes - backend goes out multiple times a week, app releases to Google and Apple at least weekly. To thrive here, our engineers proactively use our Engineering Principles to guide daily decisions, take ownership of problems beyond their own squad to drive broader impact, and actively drive their own learning, development, and growth. ABOUT THE ROLE ✍️ We're hiring a Staff Backend Engineer for our Financial Assistant Pillar. You'll shape technical direction and drive delivery across multiple functional product squads. Key responsibilities for this role include: - Partnering with senior peers to define architecture and lead complex, high-impact initiatives - Bringing teams together to ship ambitious product work that improves users’ financial health - Building shared systems, patterns, and tooling that raise the bar across engineering - Staying hands-on in our Ruby on Rails monolith -- designing APIs, data models, and scalable services - Anticipating risks and opportunities early, influencing plans and technical strategy - Mentoring engineers and TLs, growing the next generation of technical leaders   WHAT WE'RE LOOKING FOR 🕵️ - You’re excited by the opportunity to own and influence technical direction at a pillar level - You’ve operated at senior/staff level across multiple teams or complex domains - You bring strong technical judgment and think in long-term, scalable solutions - You’re comfortable leading without authority and aligning teams around a shared direction - You have a track record of building systems and practices used beyond your immediate team - You enjoy mentoring and raising the bar for others - You have strong, hands-on experience with Ruby on Rails (essential) WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Location: Remote 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 Staff Software Engineer to join our organization. Garner’s Engineering team tackles incredibly hard technical problems for a mission that truly matters. Our systems analyze billions of medical records to rank healthcare providers across the country. We are an AWS + Kubernetes shop, and we are constantly introducing new technologies as our system load doubles every year. We expect our engineers to champion cutting-edge industry practices as we aggressively embrace AI in every facet of our operations and norms. We are seeking teammates who take pride in delivering their best work while fostering a strong team culture. Where you will work: Garner is headquartered in NYC, but this position is available for individuals who are comfortable with remote work and occasional travel to HQ. What you will do: Lead team-level technical strategy and execution on multi-quarter time horizons Use AI to build, optimize, and maintain software systems Uplevel engineers across the organization by raising the technical bar Collaborate across disciplines to understand our domain and iterate on projects Protect our users’ privacy and security through best practices The ideal candidate has: 6+ years of software engineering experience Experience leading teams of engineers with demonstrated impact on technical strategy A generalist software engineering mindset ready to learn new languages, frameworks, and techniques required for a fast paced startup environment Demonstrated ability to build complex systems using AI coding agents (we use Claude Code) Able to learn quickly and mentor others Familiarity with data security and HIPAA 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 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: Claude Code, Kubernetes, AWS, Airflow, DBT, Python, TypeScript, React, Go 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 $275,000 - $300,000. 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), 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: Almaty, Kazakhstan; Tbilisi, Georgia; Yerevan, Armenia; Belgrade, Serbia; Minsk, Belarus; Tashkent, Uzbekistan The Vault is an MPC-based crypto custody platform for institutional and retail clients, running threshold signing across HSM and Ledger hardware. We're scaling toward Series A, launching our productized platform in 2026, and publishing original cryptographic research alongside the product. We're hiring a Staff Engineer to design and ship the custody platform's hardest backend code. This is a hands-on IC role with real technical leadership — no people management — where you drive non-trivial initiatives through code, RFCs, and mentorship. You'll shape architecture in your area of ownership; platform-wide decisions sit with technical leadership. We're AI-forward (Claude Code, Cursor, Codex), and we need engineers who can read AI-generated code critically and catch what it misses — not just prompt it. You'll naturally gravitate toward either the security-critical core (MPC, threshold signing, HSM/Ledger integration, key lifecycle) or the faster-moving periphery (chain adapters, integrations, APIs/SDKs). What you'll do Design, write, and ship critical platform components: policy engine, signing orchestration, key lifecycle workflows, recovery flows, approvals, audit trails, multi-tenant wallet and account services. Lead non-trivial cross-cutting initiatives in your area — through written RFCs, design reviews, and code, not through hierarchy. Build high-load, multi-tenant SaaS systems: tenant isolation, quotas, rate limits, backpressure, concurrency control, predictable latency under spikes. Distributed systems & reliability: idempotency, retries, outbox/inbox, event-driven workflows, sagas and state machines, replay, graceful degradation. Security-by-design: least privilege, secret handling, mTLS/JWT, tamper-evident logs, audit-ready data models — designed for SOC 2, ISO 27001, and DORA scope from day one. Performance & data: profiling, load testing, benchmarking, contention analysis, GC tuning; strong relational modelling (Postgres or equivalent), migrations, indexing, clear consistency boundaries. AI-assisted development as a core competency: ship production code with Claude Code, Cursor, and Codex; build the prompt and agent patterns that work for your area; contribute to the company's AI engineering practices; know when to use AI heavily (periphery, integrations, tests, docs) and when not to (cryptographic core, signing paths) where blind generation is unsafe. Set patterns and shared libraries for the services your area touches; raise the bar through code review and example. Own features end-to-end: design notes / RFCs, code, tests, observability, rollout, on-call. No "throw it over the wall" handoffs. Mentor senior engineers: your reviews and your written designs are the strongest signal to the rest of the team. Requirements Must-have experience Strong CS fundamentals — our primary screening criterion. You can reason from first principles about concurrency, distributed systems, consistency models, networking, and OS behaviour. You know not just what locks and channels do, but why and when. You understand what's happening under the hood, not only at the API level. Ownership mindset. You've owned non-trivial production systems end-to-end — design, ship, measure, improve, on-call. You don't wait to be told what to do, and you don't ship code you don't understand. 10+ years backend engineering, including 3+ years operating at Staff level (or equivalent senior IC scope). Strong production experience in a modern systems language — Go, Rust, Java, C++, or comparable. Hands-on Go experience, or genuine readiness to ramp on Go in the first month. Track record of Staff-level technical leadership through code, RFCs, and influence — without formal authority over teams. You can point to RFCs you wrote that the team adopted, initiatives you drove without being the manager, patterns you set that outlasted you. Proven track record building high-load, multi-tenant SaaS in production (HA, incident response, SLOs). Hands-on with modern backend stacks: gRPC/HTTP, queues/streams, caching, relational databases, Kafka/NATS or equivalent. Strong testing discipline: unit/integration/contract tests, testability-first design, deterministic CI. Strong observability habits: structured logging, metrics, tracing, end-to-end production debugging. REQUIRED: production-grade use of modern AI coding tools (Claude Code, Cursor, Codex, or comparable). You can point at what you've built with them. You read AI-generated code as a hostile reviewer, not a grateful recipient — you have instincts for what AI tends to get wrong, and you don't ship code you couldn't have written yourself. Nice to have Exposure to custody, wallets, or signing systems (MPC, HSM, TEE, key management, approvals). Hardware wallet integration (Ledger). Multiple blockchain ecosystems (EVM and Bitcoin minimum; Cosmos, Solana, others a plus). Built custom agents, MCP integrations, or in-repo AI workflows that compounded a team's productivity. Designed and run evals for AI-generated code (correctness, security, style). Kubernetes and service mesh in production; SRE practices. Regulated-environment experience (fintech, security audits, compliance-driven engineering). Threat modelling and security review participation. Familiarity with SOC 2, ISO 27001, and DORA — enough to design for them. What this role is NOT A people management role. A pure architecture / whiteboard role. You write production code in this codebase every week, and platform-wide architectural ownership sits elsewhere. A research-only cryptography role. You collaborate with our Cryptography Researcher; your focus is platform engineering, not protocol design. Pure feature ticket execution. If you wait to be told what to do, this won't work. Benefits A Staff IC role with real technical leadership — no people management, no sprint mechanics gauntlet, no architecture-by-committee. An AI-forward engineering culture with budget and autonomy for the tooling, models, and agents you need. Direct peers in cryptography research, security architecture, product, and delivery — you're not the only senior voice in the room. Fully remote, any time zone with reasonable overlap with EU/CIS hours. Competitive comp at the Staff engineer band; equity participation; full benefits. A product approaching Series A with paying institutional customers and a published cryptographic research line

Location: Oakland, California, United States From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. ​ During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About The Role Fivetran is building data pipelines to power the modern data stack for thousands of companies. We're looking for a Senior Staff Software Engineer to join our Systems Engineering team and lead the engineering behind our internal AI-powered application ecosystem. This is a high-leverage, high-visibility role with three interlocking mandates. First, you will own the development and governance of a code library and set of agent rules that will serve as the architectural foundation for multiple internal AI-enabled webapps at Fivetran.  Second, you will work with stakeholders to develop, productionalize, and enhance custom apps built on this foundation.  Third, you will act as a trusted advisor to engineering leadership, shaping policy and governance for how non-engineers should use AI to safely develop, productionalize, and deploy apps. This position sits at the crossroads of software engineering, platform architecture, and AI-assisted development. You will partner closely with business stakeholders and engineering platform teams across the company, translating a fast-moving, experimental "everyone builds" culture into production software held to a high standard of security, reliability, and maintainability. This is a full-time position based out of our Oakland, CA office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Python, TypeScript/React Kubernetes, GCP Cloud SQL (PostgreSQL) BigQuery data sources, Claude API, Agent SDK GTM systems -  Salesforce, Outreach, Gong, and Zendesk What You’ll Do Independently design and implement features and performance improvements to create highly scalable distributed data pipelines on the cloud Develop, maintain, and test code Conduct design and code reviews Collaborate with peers, product managers, customer support, and other stakeholders to deliver the best product with high quality, performance, and scalability Understand and fix challenges related to performance and scalability. Participate periodically in on-call rotation Participate in the hiring process Mentor Junior developers Make Fivetran the most reliable and secure component of our customers’ data infrastructure Skills We’re Looking For 10+ years of experience in the software industry with a passion for solving complex software engineering problems - experience designing and developing reusable libraries and experimentation platforms for backend and frontend from scratch leveraging industry best practices Experience working with distributed systems and cloud security concepts Demonstrated ability to write well-structured and performant code Ability to independently lead software and infrastructure design to satisfy project requirements Can identify design flaws in existing systems and come up with improvements Experience in code reviews, design, troubleshooting and testing Experience programming in an object oriented / systems language such as Java, C++, C# etc Hands-on experience working with any cloud technologies(AWS, GCP, Azure) and containerization methodologies like Docker, K8s Experience interacting with continuous integration tools like BuildKite Knowledge of observability tools like New Relic/Grafana is a plus Understand how to use AI code assist and coding agents to automatically generate code for features, bugs, testing, and investigation Ability to use conversational AI systems (like Claude, ChatGPT, and internal chatbots) to support researching, authoring, reviewing, and synthesizing various SDLC artifacts such as TDDs, PRDs, Postmortems, Test Plans, and Proposals Bonus Skills​ Experience in data processing (ETL, ELT) and/or cloud-based platforms #LI-HYBRID #LI-VA1 The compensation range displayed on this job posting reflects the minimum and maximum target for new hire compensation for the target position and level, and may include sales incentives or target bonuses depending on the role.  Our compensation ranges are determined by role, level, and location. Our job titles may span more than one career level. Within the range, individual compensation is determined by additional factors, including job-related skills, experience, relevant education or training, business need, market demands. The compensation range is subject to change and may be modified in the future. Your recruiter can share more about the specific compensation range for your location during the hiring process. Oakland Pay Range $232,338 — $290,422 USD Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: Remote GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Site Reliability Engineers keep GitLab's user-facing services and production systems running reliably at scale. They combine software engineering with operational excellence, applying sound engineering principles, automation, and continuous improvement to build, operate, and evolve our production infrastructure. This is a single application for Site Reliability Engineering opportunities across Infrastructure Platforms. Rather than asking you to choose the right team or level upfront, we evaluate your skills holistically and match you to the opportunity that best aligns with your experience and our hiring needs. We hire Site Reliability Engineers from Intermediate through Senior Staff across multiple Infrastructure Platforms teams. We don't expect every candidate to have experience with every technology in our environment. We're looking for engineers with strong technical fundamentals, a growth mindset, and the ability to learn quickly. We'll support you in becoming successful with GitLab's tools, systems, and ways of working. Please note: This position is open to candidates based in the United Kingdom only. Candidates based in the United States or Canada can apply to this posting: Site Reliability Engineer, Infrastructure Platforms — AMER (Intermediate to Senior Staff) How our SRE hiring works Because this is a single application for SRE roles across Infrastructure Platforms, our process is built to evaluate you once and match you well, rather than interviewing separately for every team. Recruiter Screen: A conversation about your background, what you're looking for, and the level and teams that fit, so we can point your process in the right direction. Core Technical: The shared assessment every SRE candidate takes, regardless of eventual team. A low-stress, collaborative discussion covering system architecture and incident review. Hiring Manager Interview: A conversation about ownership, judgment, execution, collaboration, and growth, the non-technical signals that make an SRE effective at GitLab. Peer Technical: Team-specific depth, run by SREs from the team you're most likely to join, focused on the problems that team actually works on. Skip-Level Interview: A conversation with a senior leader on values alignment, and how you'll work across teams. After your interviews, we consider your performance alongside our current hiring needs to confirm the level and team where you'll do your best work. Interview results are a major factor, and final placement also reflects our active hiring priorities at the time. We’ll calibrate your level throughout the interview process based on the scope and impact of your experience. Intermediate: You independently deliver meaningful reliability improvements within a defined area. Senior: You own complex reliability work end to end and raise the effectiveness of your team. Staff: You shape reliability across multiple teams, solving systemic problems and creating approaches others can reuse. Senior Staff: You set technical direction across a broader Infrastructure area and influence reliability strategy at organizational scale. What you'll do Keep user-facing services and production systems reliable, scalable, and efficient Build automation and tooling that reduces toil and replaces manual work with repeatable, infrastructure-as-code-driven workflows Operate and troubleshoot production systems on Kubernetes, including deployments, rollouts, and scaling Write and maintain infrastructure as code, and ship changes safely through CI/CD and GitOps Participate in on-call, triage alerts, follow and improve runbooks, and escalate appropriately Contribute to the observability stack, using metrics, logs, and SLOs to detect symptoms early rather than just outages Take part in incident response and post-incident reviews, turning learnings into changes in automation and process Document runbooks, architecture decisions, and reviews so your findings become repeatable practices What you'll bring Experience keeping production systems reliable, combining an operations mindset with real software engineering practice Experience building net-new infrastructure tooling and automation, not just configuring existing tools. For example, Terraform modules, Kubernetes operators or controllers, or production automation and services written from scratch The ability to read, debug, and reason about code. Most of our teams work in Go; some work in Ruby. You can discuss a piece of code's behavior, performance, and failure modes Experience with infrastructure as code, and with Kubernetes and its ecosystem, at a depth appropriate to your level Hands-on experience with at least one major cloud provider (GCP or AWS) Familiarity with observability practices, including metrics, logging, alerting, and SLOs or SLIs, and using data to inform operational decisions Comfort participating in on-call and incident response, with a structured approach to troubleshooting under pressure Strong written communication and the ability to operate as a manager-of-one in an async, distributed environment A track record of using automation, and increasingly AI, to reduce toil and improve how you and your team work Alignment with GitLab's values and a commitment to working in accordance with them About the team Infrastructure Platforms is responsible for the availability, reliability, performance, and scalability of GitLab’s user-facing services, most notably GitLab.com . The organization spans teams across Production Engineering , GitLab Dedicated , GitLab Delivery , and Developer Experience , covering everything from the production fleet and networking platform to observability, incident response, deployment infrastructure, tenant scale, and our single-tenant Dedicated offering. We are a globally distributed, remote-first organization that works asynchronously, favors automation over toil, and uses monitoring, metrics, and clear ownership to continuously improve the reliability of GitLab at scale. For more on how we work, see the Infrastructure Handbook Page . How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Задачи: — Архитектура, разработка и поддержка full-stack программных платформ для команд инфраструктуры и операций. — Ведение технического дизайна систем для обработки и анализа инфраструктурных и операционных данных в масштабе. — Разработка backend-сервисов и API для сбора, обогащения и запросов данных. — Создание и поддержка веб-интерфейсов с расширенным поиском и фильтрацией для технических пользователей. — Проектирование и реализация ETL и конвейеров обработки данных для структурированных и полуструктурированных источников. — Обеспечение полной контейнеризации приложений и готовности к продакшену с использованием Docker и Kubernetes. — Выступать техническим лидером по вопросам дизайна систем, производительности, надежности и поддержки. — Сотрудничество с платформенными, инфраструктурными, безопасностными и продуктовыми командами для формирования долгосрочной стратегии. — Установление и поддержание лучших инженерных практик по тестированию, качеству кода, документации и готовности к эксплуатации. — Ревью дизайнов и кода, повышение технического уровня команды. — Выявление системных проблем, снижение технического долга, улучшение масштабируемости и опыта разработчиков. Требования: — Опыт работы на позиции Staff или Senior Full Stack Software Engineer с комплексными продакшен-системами. — Способность работать самостоятельно в условиях неопределенности и доводить решения до конца. — Сильные навыки backend-разработки, включая дизайн API и работу с данными. — Опыт создания приложений с обработкой, трансформацией и анализом данных. — Владение одним или несколькими backend-языками: C#, Python, Go, Java. — Хорошие знания SQL и опыт работы с реляционными базами данных. — Практический опыт с Docker и контейнеризацией приложений. — Понимание распределенных систем и облачного нативного дизайна. — Опыт работы с CI/CD и современными процессами разработки. — Отличные технические суждения, коммуникация и влияние без формальной власти. Преимущества: — Опыт проектирования и эксплуатации систем на Kubernetes. — Знакомство с PostgreSQL, MySQL или аналогичными базами. — Опыт с ETL, аналитическими платформами или инструментами для операционных данных. — Знание облачных платформ GCP или AWS. — Опыт создания внутренних платформ или инструментов для инфраструктуры, SRE, DevOps или платформенной инженерии. — Понимание наблюдаемости, оптимизации затрат, надежности и автоматизации инфраструктуры. Образование и опыт: — Степень бакалавра в области компьютерных наук или эквивалентный практический опыт. — Обычно 10+ лет профессионального опыта в разработке ПО с подтвержденным владением крупными или критичными системами.

Задачи: — Архитектура, разработка и поддержка full-stack программных платформ для команд инфраструктуры и операций. — Ведение технического дизайна систем для обработки и анализа инфраструктурных и операционных данных в масштабе. — Разработка backend-сервисов и API для сбора, обогащения и запросов данных. — Создание и поддержка веб-интерфейсов с расширенным поиском и фильтрацией для технических пользователей. — Проектирование и реализация ETL и конвейеров обработки данных для структурированных и полуструктурированных источников. — Обеспечение полной контейнеризации приложений и готовности к продакшену с использованием Docker и Kubernetes. — Выступать техническим авторитетом по вопросам дизайна систем, производительности, надежности и поддержки. — Сотрудничество с платформенными, инфраструктурными, безопасностными и продуктовыми командами для формирования решений в соответствии с долгосрочной стратегией. — Установление и поддержание лучших инженерных практик по тестированию, качеству кода, документации и готовности к эксплуатации. — Ревью дизайнов и кода, предоставление рекомендаций и повышение технического уровня команды. — Выявление системных проблем, снижение технического долга и улучшение масштабируемости платформы и опыта разработчиков. Требования: — Опыт работы на позиции Staff или Senior Full Stack Software Engineer с комплексными производственными системами. — Способность работать самостоятельно в условиях неопределенности и доводить решения до конца. — Сильные навыки backend-разработки, включая дизайн API и работу с интенсивными данными сервисами. — Опыт создания приложений, основанных на данных, включая сбор, трансформацию и анализ. — Владение одним или несколькими backend-языками: C#, Python, Go, Java. — Хорошие навыки SQL и опыт работы с реляционными базами данных. — Практический опыт с Docker и контейнеризацией приложений. — Понимание основ распределенных систем и облачного дизайна приложений. — Опыт работы с CI/CD и современными процессами разработки ПО. — Отличное техническое суждение, коммуникационные навыки и способность влиять без формального авторитета. Предпочтительный опыт: — Проектирование и эксплуатация систем на Kubernetes. — Знакомство с PostgreSQL, MySQL или аналогичными базами данных. — Опыт работы с ETL-конвейерами, аналитическими платформами или инструментами для операционных данных. — Опыт работы с облачными платформами GCP или AWS. — Опыт создания внутренних платформ или инструментов для инфраструктуры, SRE, DevOps или платформенной инженерии. — Понимание наблюдаемости, оптимизации затрат, надежности и автоматизации инфраструктуры. Образование и опыт: — Степень бакалавра в области компьютерных наук или смежной области, либо эквивалентный практический опыт. — Обычно 10+ лет профессионального опыта в разработке ПО с подтвержденным владением крупными или критическими системами.

Задачи: — Архитектура, разработка и поддержка full-stack программных платформ для команд инфраструктуры и операций. — Ведение технического дизайна систем для обработки и анализа инфраструктурных и операционных данных в масштабе. — Разработка backend-сервисов и API для сбора, обогащения и запросов данных. — Создание и поддержка веб-интерфейсов с расширенным поиском и фильтрацией для технических пользователей. — Проектирование и реализация ETL и конвейеров обработки данных для структурированных и полуструктурированных источников. — Обеспечение полной контейнеризации приложений и готовности к продакшену с использованием Docker и Kubernetes. — Выступать техническим авторитетом по вопросам дизайна систем, производительности, надежности и поддержки. — Сотрудничество с платформенными, инфраструктурными, безопасностными и продуктовыми командами для формирования решений в соответствии с долгосрочной стратегией. — Установление и поддержание лучших инженерных практик по тестированию, качеству кода, документации и готовности к эксплуатации. — Ревью дизайнов и кода, предоставление рекомендаций и повышение технического уровня команды. — Выявление системных проблем, снижение технического долга и улучшение масштабируемости платформы и опыта разработчиков. Требования: — Опыт работы на позиции Staff или Senior Full Stack Software Engineer с комплексными производственными системами. — Способность работать самостоятельно в условиях неопределенности и доводить решения до конца. — Сильные навыки backend-разработки, включая дизайн API и работу с интенсивными данными сервисами. — Опыт создания приложений, основанных на данных, включая сбор, трансформацию и анализ. — Владение одним или несколькими backend-языками: C#, Python, Go, Java. — Хорошие навыки SQL и опыт работы с реляционными базами данных. — Практический опыт с Docker и контейнеризацией приложений. — Понимание основ распределенных систем и облачного дизайна приложений. — Опыт работы с CI/CD и современными процессами разработки ПО. — Отличное техническое суждение, коммуникационные навыки и способность влиять без формального авторитета. Предпочтительный опыт: — Проектирование и эксплуатация систем на Kubernetes. — Знакомство с PostgreSQL, MySQL или аналогичными базами данных. — Опыт работы с ETL-конвейерами, аналитическими платформами или инструментами для операционных данных. — Опыт работы с облачными платформами GCP или AWS. — Опыт создания внутренних платформ или инструментов для инфраструктуры, SRE, DevOps или платформенной инженерии. — Понимание наблюдаемости, оптимизации затрат, надежности и автоматизации инфраструктуры. Образование и опыт: — Степень бакалавра в области компьютерных наук или смежной области, либо эквивалентный практический опыт. — Обычно 10+ лет профессионального опыта в разработке ПО с подтвержденным владением крупными или критическими системами.

Samsara is the pioneer of the Connected Operations™ Cloud, a platform that enables organizations that depend on physical operations to harness IoT data to improve safety, efficiency, and sustainability. Key requirements: — proficiency in Go, Python, and JavaScript — bonus: experience with C/C++ (firmware/embedded systems)

Требования: — владение Go, Python и JavaScript — опыт с C/C++ (прошивка/встроенные системы) будет плюсом

Требования: — владение Go, Python и JavaScript — опыт с C/C++ (прошивка/встроенные системы) будет плюсом

Задачи: — Архитектура, разработка и поддержка full-stack программных платформ для команд инфраструктуры и операций. — Ведение технического дизайна систем для обработки и анализа инфраструктурных и операционных данных в масштабе. — Разработка backend-сервисов и API для сбора, обогащения и запросов данных. — Создание и поддержка веб-интерфейсов с расширенным поиском и фильтрацией для технических пользователей. — Проектирование и реализация ETL и конвейеров обработки данных для структурированных и полуструктурированных источников. — Обеспечение полной контейнеризации приложений и готовности к продакшену с использованием Docker и Kubernetes. — Выступать техническим авторитетом по вопросам дизайна систем, производительности, надежности и поддержки. — Сотрудничество с платформенными, инфраструктурными, безопасностными и продуктовыми командами для формирования решений в соответствии с долгосрочной стратегией. — Установление и поддержание лучших инженерных практик по тестированию, качеству кода, документации и готовности к эксплуатации. — Ревью дизайнов и кода, предоставление рекомендаций и повышение технического уровня команды. — Выявление системных проблем, снижение технического долга и улучшение масштабируемости платформы и опыта разработчиков. Требования: — Опыт работы на позиции Staff или Senior Full Stack Software Engineer с комплексными производственными системами. — Способность работать самостоятельно в условиях неопределенности и доводить решения до конца. — Сильные навыки backend-разработки, включая дизайн API и работу с интенсивными данными сервисами. — Опыт создания приложений, основанных на данных, включая сбор, трансформацию и анализ. — Владение одним или несколькими backend-языками: C#, Python, Go, Java. — Хорошие навыки SQL и опыт работы с реляционными базами данных. — Практический опыт с Docker и контейнеризацией приложений. — Понимание основ распределенных систем и облачного дизайна приложений. — Опыт работы с CI/CD и современными процессами разработки ПО. — Отличное техническое суждение, коммуникационные навыки и способность влиять без формального авторитета. Предпочтительный опыт: — Проектирование и эксплуатация систем на Kubernetes. — Знакомство с PostgreSQL, MySQL или аналогичными базами данных. — Опыт работы с ETL-конвейерами, аналитическими платформами или инструментами для операционных данных. — Опыт работы с облачными платформами GCP или AWS. — Опыт создания внутренних платформ или инструментов для инфраструктуры, SRE, DevOps или платформенной инженерии. — Понимание наблюдаемости, оптимизации затрат, надежности и автоматизации инфраструктуры. Образование и опыт: — Степень бакалавра в области компьютерных наук или смежной области, либо эквивалентный практический опыт. — Обычно 10+ лет профессионального опыта в разработке ПО с подтвержденным владением крупными или критическими системами.