Вакансии

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE: We're looking for a Senior Fullstack Engineer for our commercial product LangSmith, an observability and evals platform. In this role, you'll have the opportunity to shape the technical direction of our platform while working closely with enterprise customers, developer end-users and internal stakeholders. WHAT YOU WILL DO: - Lead the technical architecture and implementation of key product features for LangSmith, working across our entire Go, Python, and Typescript stack. - Collaborate closely with product and design teams to iterate on new features. - Mentor and guide more junior members of the team. Drive aggressive project timelines while ensuring high engineering standards are being met. - Lead by example in writing clean, maintainable, and well-tested code   WHAT YOU BRING: - 5+ years of experience in software engineering working on complex platform products - Fullstack engineering experience with Go or Python on the backend and React + Typescript on the frontend. - Strong understanding of database systems, particularly Postgres and Redis - Experience designing and scaling APIs, preferably in a high-performance, data-intensive application - A “get stuff done” attitude - comfortable shipping fast and iterating based on user feedback - Strong communicator with the ability to collaborate closely with various internal stakeholders and engage directly with our top-tier customers - Strong ownership mindset - Bonus: Experience with AI/LLM-powered applications, developer tools, or observability platforms   Annual salary range: $175,000-$240,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done.   ABOUT THE ROLE We are looking for a Senior Backend Engineer to join us. In this role you will be building the backend systems that power LangChain’s observability and evals platform. You will work on the core services that allow developers to monitor and evaluate their AI applications at scale. While the focus is on backend feature development, familiarity with fullstack or frontend engineering, performance tuning, and debugging production issues would be extremely valuable.   WHAT YOU'LL DO - Design, develop, and maintain backend services and APIs to support LangSmith’s tracing, monitoring, and evaluation workflows. - Collaborate on architectural decisions to ensure systems are performant and maintainable. - Optimize storage and query performance for high-volume observability and evaluation data. - Ensure system reliability through strong testing, monitoring, and alerting practices. - Troubleshoot and resolve production issues, performing root-cause analysis and implementing long-term fixes. - Create and maintain technical documentation, including system design and API references. - Work closely with full-stack engineers, product managers, and product designers on rolling out new features.   WHAT YOU'LL BRING - 5+ years of professional experience in backend engineering working on highly complex products - Proficiency in one or more backend languages/frameworks, ideally Python or Go - Strong understanding of API design and building reliable data services. - Experience with high-throughput or mission-critical systems. - Demonstrated ability to optimize backend services for performance and reliability. - Experience with database systems (Postgres, Redis, Clickhouse), and cloud platforms (AWS, GCP, Azure) - Strong communication skills, with the ability to collaborate cross-functionally - Customer centricity and ownership mentality   Compensation Annual salary range: $180,000- $240,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM   This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.     ABOUT THE ROLE   You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $185,000–$315,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.   ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world.   WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement   WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production   NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Palo Alto, CA or Seattle, WA 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. _______________________________________________________________________ As agents take on bigger jobs, the infrastructure around them matters more. Docker's answer is to give every agent a strong boundary, make its environment and authority reproducible, and let the work run where it makes sense, from a developer's laptop to the cloud. The Docker AI Substrate team brings that foundation to the enterprise: the largest companies in the world, running agents at scale, with the security, reliability, and control they expect from any critical system. We are a small, senior team at the start of that work. As a Staff Software Engineer here, you will shape the architecture, build the core systems, and run what you build. Locations: Seattle, WA or Palo Alto, CA. RESPONSIBILITIES - Design and build the systems that deploy, release, and operate Docker's agentic platform for enterprise customers, in Go and on Kubernetes. - Make the platform run consistently across cloud providers and environments, with the security, identity, and network boundaries enterprises require. - Own the release and supply chain path so every deployment is reproducible, verifiable, and trusted. - Run what you build: production ownership, on-call, SLOs, incident response, and the operational tooling that keeps it boring. - Set technical direction with the team's architect and engineering leadership, and work with partner teams across runtime, developer experience, identity, and observability. - Raise the bar through design review, testing discipline, and mentorship as the team grows. QUALIFICATIONS REQUIRED - You have built and operated a cloud control and management plane. Software that provisions, upgrades, and watches infrastructure for many tenants or environments, in production, with a pager. Experience at a cloud provider, a managed-service vendor, or a platform team that stamps out environments. - Kubernetes beyond deployment. You have written controllers or operators, understand reconciliation and CRDs, and know why declarative beats imperative at fleet scale. - Deep in at least one major cloud. Hands-on with compute, networking, identity, and managed services, and able to pick up a second cloud fast. - Production ownership. On-call, incident response, SLOs, post-mortems. You run what you build. - Distributed systems design. Fault tolerance, consistency, observability, idempotent reconciliation. - Go. Professional proficiency. Docker's backend and all of this team's code is Go. - 10+ years of professional software engineering in infrastructure, platform, or cloud services, with the judgment to set direction for others. STRONGLY PREFERRED - Kubernetes resource orchestration and cloud controllers, such as KRO. - Release engineering and software supply chain: OCI registries, digests, license compliance. - Private connectivity between cloud accounts: PrivateLink, VPC peering, service endpoints, egress policy. - OpenTelemetry pipelines with multiple destinations. - Building managed services. - Firecracker, microVMs, or other isolated execution environments for untrusted code. - Bachelor's degree in Computer Science or a related field, or equivalent practical experience. Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $170,350 – $275,550 + equity ______________________________________________________________________ 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: Boston, MA; Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY; Washington, DC 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 Endpoint team (Client Platform Engineering) treats Anthropic's device fleet as a platform we build and run. We run our own MDM as a production service and manage every piece of device configuration as code. Policies, configuration profiles, queries, remediation scripts, and software all ship through pull requests, CI, a staging environment, and a canary group before they reach the fleet. The fleet is mostly macOS, plus a small number of Linux machines and a growing mobile footprint. You'll own that platform end to end: the infrastructure underneath the MDM, the configuration on top of it, the patching and software pipelines that keep thousands of devices patched and secure, and the telemetry that tells us what is actually true on every device. You'll also build automation that cuts down on manual operational work. You'll work with Security teams on hardening, compliance controls, and detection and response, and with developer and infrastructure teams to make sure those controls don't get in the way of their work. Your work will let us base access decisions on whether a device can be trusted. We value people who double check a compliance report before they believe it. The team is deliberately lean and runs with high autonomy. You'll help define the endpoint roadmap, make architecture decisions, and own the platform every Anthropic employee's work runs on. You'll also help us meet the security standards our Responsible Scaling Policy requires as models advance. Responsibilities Own endpoint configuration as code: author, review, test, and progressively roll out MDM policies, configuration profiles, and remediation scripts across macOS and mobile, with canary stages and rollback built in Operate the MDM platform itself as a production service, including infrastructure as code, observability, upgrades, and incident response Build patch management automation with rapid enforcement timelines while maintaining good user experience Design zero touch provisioning that turns a sealed box into a productive machine on day one Support a small number of Linux machines alongside the Mac fleet Turn fleet telemetry into policy, dashboards, and early drift warnings, and use Claude to automate manual ops work Partner with Corporate Security on endpoint hardening, binary authorization, and compliance controls Take shifts on the team's rotation for incoming requests and escalations, and serve as the deep escalation tier for endpoint issues IT Operations can't resolve You may be a good fit if you Have 8+ years building secure IT systems in complex environments, including leading projects across multiple teams Have managed endpoint fleets of thousands of macOS devices through a modern MDM Treat endpoint configuration as code that is version controlled and peer reviewed, rather than clicking in consoles Go deep on macOS internals such as launchd, configuration profiles, TCC, and system extensions Write Python and shell scripts Write design docs and runbooks so teammates can review and support what you build Strong candidates may also have Have operated an MDM or device management platform as a service, not only consumed one as SaaS Have worked with open source endpoint and device management tooling (Munki, osquery, AutoPkg) Have built automated, progressive rollout systems with promotion gated on telemetry Have experience running infrastructure as code in a public cloud Have working knowledge of Linux administration (packaging, systems, config management) Have used LLMs to automate ops work Deadline to apply: None. Applications will be received on a rolling basis. 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: $285,000 — $325,000 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 (United States | Canada) Workplace: Remote 1Password is growing. We’ve surpassed $500M in ARR and we’re continuing to accelerate, earning a spot on the Forbes Cloud 100 for four years in a row and teaming up with iconic partners like Oracle Red Bull Racing. About 1Password At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses, from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work. If you're excited about the opportunity to contribute to the digital safety of millions, to work alongside a team of curious, driven individuals, and to solve hard problems in a fast-paced, dynamic environment, then we want to hear from you. Come join us and help shape a safer, simpler digital future. Our Infrastructure Services organization is responsible for the underlying infrastructure that powers the 1Password application. It includes Compute Services, Network and Edge Services, and Stateful Services. As a Senior Staff Cloud Platform Engineer, you set the multi-year technical strategy for Infrastructure Services. You decide where the organization invests, define the architecture and standards that every infrastructure team and internal tenant builds on, and make sure our compute, network and edge, and stateful platforms evolve as one coherent system rather than three separate ones. You partner with engineering and product leadership, security, and finance to balance reliability, security, cost, and delivery speed, and you are the senior technical voice for infrastructure across the company. This is a hands-on role. You write design docs, prototype, review the hardest designs, and step into the most serious incidents. But your main impact comes from making many teams more effective and from the decisions that hold up for years. How we’re using AI today Our Engineering, Product, and Design teams are thoughtfully integrating AI across the full software and product development lifecycle to move faster without sacrificing quality or security. In practice, that looks like engineers using AI-assisted coding tools to accelerate reviews and catch bugs earlier, product managers synthesizing user research at scale, and designers rapidly prototyping and iterating with AI-generated mockups. We approach AI the same way we approach security: with clear principles, human accountability at every consequential decision point, and rigorous evaluation before anything ships to customers. This is a remote opportunity within Canada and the US. What we're looking for: - You have set technical direction across multiple teams. You have owned an infrastructure strategy or architecture spanning several teams or an entire organization, and you can point to the multi-year outcomes: what others adopted, what shipped, and what measurably improved. - You have operated Kubernetes at production scale. This includes multi-cluster, multi-tenant, customer-traffic-bearing environments (EKS or similar managed platforms preferred). You know it deeply, from autoscaling and admission control to GitOps, workload identity, and fleet-wide cluster upgrades. - You combine depth with breadth. Beyond Kubernetes, you have working fluency in networking and edge and in stateful data systems, and you understand how a decision in one layer affects the rest. - You have made reliability a standard, not a project. You defined SLIs, SLOs, and error budgets, and you got multiple teams to adopt them. You have improved incident response, post-incident learning, and disaster recovery across an organization, not just on your own team. - You have cut cloud costs through engineering. You can show measurable, real-dollar impact from work such as capacity automation, right-sizing, architecture changes, or commitment strategy, and you have worked with finance on forecasting and tradeoffs. - You build security in by design. You have driven practices such as workload identity, least-privilege IAM and RBAC, credential rotation, and strong isolation in multi-tenant environments, and you have partnered with security teams on risk decisions and compliance requirements. - You still build. You are proficient in Go (or a similar language) and Infrastructure as Code (Terraform), and you have a track record of automating complex, high-toil operational workflows at fleet scale. - You influence without relying on authority. You write clear strategy and design documents, present to senior leaders, resolve technical disagreements between teams, and build alignment on difficult tradeoffs. - You grow other engineers. You have mentored Senior and Staff engineers, raised the bar on design review, and helped shape how your organization hires and evaluates technical talent. Bonus points for: - Hands-on experience with service mesh and service-to-service networking, such as Linkerd or Amazon VPC Lattice. - Experience operating scalable database technology, such as MySQL, Postgres, or DynamoDB. - Designing developer platform abstractions for internal teams, such as paved-road service toolkits and production readiness frameworks, that measurably improved usability and productivity. - Helping build AI-assisted operations tools, such as auto-remediation or AI-assisted diagnosis, rather than only using them. - Operating highly available, multi-region services in a large SaaS environment, including capacity planning and performance optimization at scale. - Experience in a security, identity, or other high-trust product environment. What you can expect: - Set the multi-year technical strategy and architecture for Infrastructure Services, working with directors and senior engineering leadership to shape roadmap and investment decisions, including build versus buy. - Define the patterns, standards, and guardrails across compute, network and edge, and stateful services that internal teams depend on for years. - Represent Infrastructure Services in cross-organization reviews with product engineering, security, and finance, and serve as the senior technical voice for the platform. - Serve as an escalation point for major incidents, and drive organization-wide improvements to incident management, reliability targets, and disaster recovery. - Lead cost, capacity, and efficiency strategy for our cloud footprint, with measurable goals. - Drive adoption of automation and AI-assisted operations to reduce toil across the organization. - Mentor Staff and Senior engineers, raise the bar on design review and engineering practice, and help us hire and develop the next generation of infrastructure leaders. USA-based roles only: The annual base salary for this role is between $230,000 USD and $334,000 USD, plus immediate participation in 1Password's benefits program (health, dental, 401k and many others), utilization of our generous paid time off, an equity grant and, where applicable, participation in our incentive programs. Canada-based roles only: The annual base salary for this role is between $202,000 CAD and $293,000 CAD, plus immediate participation in 1Password’s generous benefits program (health, dental, RRSP and many others), utilization of our generous paid time off, an equity grant and, where applicable, participation in our incentive programs. At 1Password, we approach each individual's compensation with a promise of fair market value and internal equity commensurate with experience and specific skill set. This posting is for an existing vacancy. Our culture At 1Password, we prioritize collaboration, clear and transparent communication, receptiveness to feedback, and alignment with our core values: keep it simple, lead with honesty, and put people first. You’ll be part of a team that challenges the status quo, and is excited to experiment and iterate in search of the best solution. That said, 1Password is not for everyone https://blog.1password.com/inside-the-culture-powering-1passwords-next-chapter/. Our work is demanding, we strive for excellence, and the pace is fast. We need people who are keen to take on challenging problems, who seek feedback to grow, and who are driven to make an impact. If you're looking for a place where you can settle into a comfortable routine, this might not be the right fit for you. We’re looking for individuals who are proven experts in their fields, as well as those who are highly adaptable, can thrive in ambiguity and through change, are curious, and above all deliver results. How we work with AI We are committed to leveraging cutting-edge technology—including AI—to achieve our mission. We also understand that thinking critically about AI in its current forms will help us create better solutions for our customers and ourselves with its future forms, which will help us continue to close the gap between security and privacy and achieve our mission. We want team members at all levels to take the approach of actively learning AI best practices, identifying opportunities to apply AI in meaningful ways, and driving innovative solutions in their daily work. Embracing the future of AI isn't just encouraged—it's an essential part of how we will be successful at 1Password. This approach extends to our hiring process—candidates are welcome to use AI tools responsibly and thoughtfully during the application process. To us, this means we do ask that you join live interviews without using AI tools so we can get to know how you communicate, solve problems, and collaborate with others. Our approach to remote work We believe in the power of remote work, but recognize that in-person connection is important to help us achieve our mission. While we are a remote-first company, travel for in-person engagement is a part of almost all roles, and we require our employees to be ready and willing to take part. Frequency will depend on role and responsibilities, and may include, but is not limited to: annual department-wide offsites, team meetings, and customer/industry events. What we offer We believe in working hard, and rewarding that hard work through our benefits. While not an exhaustive list, here is a glance at what we currently offer: Health and wellbeing 👶 Maternity and parental leave top-up programs 🩺 Competitive health benefits 🏝 Generous PTO policy Growth and future 📈 RSU program for most employees 💸 Retirement matching program 🔑 Free 1Password account Community 🤝 Paid volunteer days 🏆 Peer-to-peer recognition through Bonusly 🌎 Remote-first work environment *Some roles in our GTM team are currently being hired for in-person hybrid work in Toronto and Austin. These roles will specify on the posting. You belong here. 1Password is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Be yourself, find your people and share the things you love. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at nextbit@agilebits.com and we’ll work to meet your needs. Remote work is a part of our DNA. Given that our company was founded remotely in 2005, we can safely say we're experts at building remote culture. That said, remote work at 1Password does mean working from your home country. If you've got questions or concerns about this, your talent partner would be happy to address them with you. Successful applicants will be required to complete a background check that may consist of prior employment verification, reference checks, education confirmation, criminal background, publicly available social media, credit history, or other information, as permitted by local law. 1Password uses artificial intelligence (AI) and machine learning (ML) technologies, including natural language processing and predictive analytics, to assist in the initial screening of employment applications and improve our recruitment process. See here https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf for the latest third party bias audit information. If you prefer not to have your application assessed using AI/ML features, you may opt out by completing this form https://jobs.ashbyhq.com/1password/automation-notice. For additional information see our Candidate Privacy Notice https://1password.com/files/candidate-privacy-notice.pdf.

Location: Paris; Zurich; Madrid; Amsterdam; Warsaw; Linz; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it. You will own our Kubernetes product end to end: a metal-to-on-demand platform built on in-house infrastructure, with GPU support for training, inference, and general-purpose compute. Kubernetes is our product, not just our platform — we run it on infrastructure we own end to end. You will decide how the control plane scales, how GPUs get scheduled, and how quickly a rack of bare metal becomes an on-demand cluster a customer can use. The decisions you make here shape how our infrastructure scales from today's footprint to a gigawatt, and how we turn frontier AI research into production systems used by millions. This is a role for an engineer who leads from the front because that is where the work is, not because management was the next rung on the ladder. WHAT YOU WILL DO - Design and ship the control plane. You build alongside your team and own the architecture and the hardest implementation decisions — scheduling, operators, provisioning, node lifecycle. - Grow the engineers, not just the software. You set the standard for ownership, remove the obstacles in their way, and coach them past their comfort zone until the work they ship surprises them. - Own the reliability of the Kubernetes control plane. It is the team's headline KPI. You make the calls when it breaks at 3am, and your engineers learn from how you do it. - Shrink the distance from metal to on-demand. Provisioning a cluster should be minutes of automation, not weeks of tickets. - Partner with Product Managers to set priorities, scope initiatives, and make the technical and business tradeoffs. - Own people management for the team: hiring, performance, growth paths, and honest feedback — the leadership work that never becomes someone else's job. - Define the team's processes and execution rituals as it grows. WHAT WE'RE LOOKING FOR - 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - You have shipped production systems in Go. Not dabbled. Shipped. - You have run Kubernetes in anger — and ideally built parts of it: operators, schedulers, controllers. You understand what happens underneath it, and you have worked on Linux directly, not just on managed services that sit on top of it. - You have run GPU workloads on Kubernetes, or you are confident you can own that domain fast. - You think like a developer who happens to build infrastructure, not an operator who manages it. You write code other engineers depend on. - Extensive experience building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Zurich; Madrid; Amsterdam; Warsaw; Linz; Munich; London; Berlin ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a founding people-leadership role. There is no team to inherit and no legacy to maintain — you build the team as well as the stack, and you are accountable for both from day one. Early on you will be deliberately hands-on, because there is no one else to solve the hardest problems — but hiring your first engineers, coaching them, and setting their growth paths starts immediately, not later. If you are looking for a senior IC role, this is not it. You will be the founding Engineering Team Lead for storage on our cloud. Block, filesystem, and object storage for training runs, sandboxed workloads, and general compute: you decide what we build, what we buy, and how it adds up to storage our customers can bet a business on. Some layers we deploy and harden from best-in-class vendors. The ones that matter most we write ourselves in Go — S3-compatible object storage, tiering, backup and recovery, caching layers that put cold data on cheap spinning disks. As the team grows, the balance shifts toward people leadership, and you decide how fast. You will own capacity planning across datacenters and the architecture that keeps data durable when disks, networks, and entire sites fail. Storage is a strategic bet for this org: the team you build and the calls you make will define how a gigawatt of European compute stores its data. WHAT YOU WILL DO - Stand up the storage stack — block, file, object — for training, sandbox, and general compute workloads. - Make the build-vs-buy calls: deploy and harden vendor platforms where they win; design and write our own services in Go where they don't. - Own the data plane: allocation, duplication, tiering, backup and recovery, S3-compatible APIs. - Plan capacity across datacenters and across failure domains — petabytes, not terabytes. - Build the team from zero: make the first hires, onboard and coach them, own performance and growth paths, and set the standard for ownership. - Partner with Product Managers to shape the storage roadmap and make the technical and business tradeoffs. WHAT WE'RE LOOKING FOR - 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - You have built storage systems — object, block, or distributed filesystems — not just operated them. You know what happens when a disk dies mid-write and when a rebalance collides with a backup window. - Deep distributed-systems fundamentals: durability, consistency, replication, erasure coding, failure domains. - You have shipped production systems in Go. Systems engineers coming from C++ or Rust who are ready to write Go daily should still talk to us. - You are comfortable with hardware reality: HDD, SSD, and NVMe tiers, and the economics of each. - 8+ years building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Zurich; Madrid; Amsterdam; Warsaw; Linz; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it. AI agents don't run in browsers. They run in sandboxes — and you will lead the team building ours. We build secure, isolated, network-controlled environments with snapshotting primitives, designed for AI agents and reinforcement-learning workloads. An RL training run doesn't need one environment; it needs thousands, created and destroyed every second. An agent needs to be sandboxed from the world while still feeling fast enough to be useful. That tension — airtight isolation, at fleet scale, at low latency — is the product. Your customers are the people building the next generation of AI software on our infrastructure; the primitives you ship become the runtime their agents live in. WHAT YOU WILL DO - Build the isolation layer: microVMs or containers, namespaces, cgroups, seccomp, snapshot and restore. - Own the security boundary. Customers run code they didn't write and can't fully trust — your systems make that safe. - Scale to fleets: creation latency, density, and lifecycle management for thousands of concurrent environments. - Write Go alongside your team and own the architecture and the hardest implementation decisions. - Grow the engineers, not just the software — set the standard for ownership and coach people past their comfort zone. - Own people management for the team: hiring, performance, growth paths, and honest feedback. - Partner with Product Managers to turn frontier research needs into shippable primitives. WHAT WE'RE LOOKING FOR - 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - Deep Linux internals: namespaces, cgroups, seccomp, virtualization — ideally microVMs of the Firecracker class. - You have shipped production systems in Go. Not dabbled. Shipped. - You understand network isolation at the packet level — not just firewall rules. - Performance instincts: you know what a syscall costs, and you have the profiles to prove you've cared. - 8+ years building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Munich; Warsaw; London Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE The Inference Foundation team owns the core of Mistral's inference stack: the inference engine and its orchestration, from the feature set and configuration that serve our models in production to the release machinery that keeps the stack current and production-grade. This is a hybrid position spanning production LLM serving, engine and platform development, and capacity engineering. You will work on three intertwined problems: 1. Optimize the inference stack at scale — feature development and fixes in the engine and orchestrator, squeezing more throughput and lower latency out of every GPU under strict quality-of-service targets. 2. Make capacity elastic — scaling up and down should be cheap and fast, not a performance cliff. 3. Power the training of our frontier models — high-performance serving that keeps RL and post-training loops running at full speed.   What You Will Do INFERENCE ENGINE & ORCHESTRATION - Develop and fix the core of the inference stack — engine and orchestrator — including feature selection, configuration, and tuning for maximum performance at scale - Own the release process for the serving stack: validated, regression-free releases through automated performance gates and progressive rollout - Drive improvements and fixes upstream when the open-source engine is the right place for them PERFORMANCE & CAPACITY AT SCALE - Optimize serving efficiency across the fleet — driving down pod startup time, tackling cold-cache regressions on scale-up, smarter caching and offloading - Optimize and maintain the optimal serving topology — overlap communication and transfers with computation, ensure optimal placement, connectivity, and routing SERVING FOR FRONTIER TRAINING - Build the serving infrastructure that powers RL and post-training for our frontier models - Optimize inference performance across the full spectrum of our workloads   What We're Looking For - Experience building and running ML/LLM services at scale, with clear latency and availability targets - Hands-on experience with inference engines such as vLLM, SGLang, TensorRT-LLM, or others - A solid grasp of inference internals: prefill vs. decode, KV-cache behavior, batching, scheduling, speculative decoding, parallelism strategies - Familiarity with distributed and disaggregated serving architectures - Comfortable debugging across the full stack — CUDA/NCCL, kernels, containers, networking, storage - Python for systems tooling and backend services; PyTorch - Kubernetes for running infrastructure at scale - GPU and networking fundamentals: CUDA runtime, NCCL, InfiniBand/RDMA It Would Be Great If You Have - Demonstrated vLLM/sglang know-how — upstream contributions, or a track record of running in demanding production environments - Hardware-aware optimization for various model architectures - Experience serving MoE models at scale (expert parallelism, expert placement/load balancing) - CUDA/Triton kernel development; Nsight Systems/Compute profiling - Rust and/or C++ in production systems WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Portland, Oregon Workplace: Remote Who We Are X-LAB is the in-house performance bicycle line by XDS, which has quietly become the world’s largest and most vertically integrated bicycle manufacturer and the largest maker of carbon fiber frames, supplying many of the top brands in cycling and mobility. Today, XDS is quiet no more. XDS launched X-LAB in April 2026 as the global consumer brand to take the industry by storm. Three decades of experience building exceptional bicycles have culminated into a unique line of road, gravel, electric, city, hybrid, and soon mountain bikes that riders and shops can’t stop talking about. X-LAB is the new inflection point for the category. We launched in April 2026 with a full lineup across road, gravel, city, fitness, e-bike, and soon mountain categories, with validation from the highest and most demanding levels of the sport through the XDS Astana Team and a rapidly growing network of dealers. Our ambition is not simply to sell more bikes. It is to make great bikes more integrated, more accessible, and better supported through the independent shops and communities that grow cycling and bring in new riders. That is what makes this moment exciting. Joining X-LAB means shaping a company with unmatched production scale, real engineering R&D depth, and the confidence to earn trust… one rider, one dealer, one product, and one market at a time. Are you ready to ride ahead of the pack? Learn more at https://xds.co/https://xlabbikes.com See an insider’s look of our factory: Youtube Video https://www.youtube.com/watch?v=06SheO5XFsY _________________________________________________ XDS is seeking a Territory Sales Manager to join us on this ground-floor opportunity to establish XDS in the North American market. This is a hands-on, field-based sales role focused on opening new dealer accounts and getting XDS bikes on shop floors across a defined territory. You’ll be out in-market most days, walking into stores, having real conversations with shop owners and managers, and building relationships face to face. This role is about laying the groundwork for XDS in North America and being the brand’s presence on the ground. The territory for this position will include Oregon and Washington. We welcome applicants from any of these states. What You’ll Do - Visit bike shops regularly to introduce XDS, open new accounts, and grow relationships - Prospect in person within your territory, including cold walk-ins - Take deals from first conversation through initial order - Train shop staff on product and positioning - Keep a pulse on competitors, pricing, and local market dynamics - Represent XDS in a professional, consistent way You’re a Great Fit With: - Experience in the cycling industry and with bicycle shops (mandatory) - 5+ years of territory/regional sales experience built on relationships, not just inbound leads - Ability to build interest and convert into sales - Comfort and flexibility with traveling, opening doors, and starting conversations in person - Strong organization and follow up skills - Background or interest in cycling or performance sports Success Metrics (1st Year) - Opening new dealer accounts - Hitting agreed revenue targets - Establishing active dealers and demo placements - Maintaining a healthy pipeline and consistent territory coverage _________________________________________________ Our Compensation and Benefits - Salary plus commission structure (expected OTE $125-175k) - Demo bike fleet and comprehensive travel allowances - Remote-focused role - Office space in beautiful Santa Monica, California

Location: Paris Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE MISSION You will be the reference point for the most complex hardware interventions across our sites. Mistral's compute is our largest investment and the foundation of frontier AI in Europe. As a Senior Data Center Hardware Engineer, you own the interventions that require the highest level of technical expertise: multi-node failures in production, full-rack deployments of GPU-dense systems, and vendor escalations where you speak as the technical authority for our sites. You'll work end-to-end — compute, storage, interconnect, power and cooling interfaces — across our data center footprint, raising the bar on reliability as our capacity grows. This is a hands-on senior IC role: deep technical leadership and mentorship, no direct line management. Location: Based at one of our data centers in the Paris region, with occasional visits to our other sites as needed.   WHAT YOU'LL DO - Lead complex interventions — vendor-level and multi-node operations in production: full rack builds and bring-up, GPU-dense platform deployment (H100/H200-class and next-gen, including liquid-cooled racks), intricate recabling, post-restart diagnosis. You own the plan, the risk assessment, and the rollback. - Own vendor management — coordinate repairs, part replacements and escalations directly with hardware vendors; hold them to their SLAs; drive proactive fixes from failure trends. - Diagnose at depth — correlate symptoms across compute, storage, interconnect and cooling; read BMC/IPMI consoles, OS logs and crash dumps; methodical root-cause analysis that ends in concrete corrective actions. - Deploy and validate — structured bring-up and validation of new racks and platforms; work with networking and infrastructure teams to take installations from delivery to production-ready. - Lift the team — mentor and pair with L1–L3 engineers on live operations; turn your knowledge into SOPs, checklists and training material; propose and build small automation (Python/Bash) to shorten MTTR. - Work the facility interface — partner with critical facilities/engineering ops on power, cooling (air and liquid), PDU and monitoring (BMS/EPMS) boundaries; enforce ESD/LOTO/PPE and audit-ready change discipline everywhere. - Own spares & reliability — plan spares strategy, track fleet failure trends, and run proactive vendor actions before incidents happen.   ABOUT YOU - 6+ years in data center / server hardware or L2/L3 hardware support, including complex hands-on work in production environments (HPC/AI/cloud at scale strongly preferred). - End-to-end hardware expertise: CPU/memory/PCIe (incl. accelerators), NICs, PSUs, drives, network, power and cooling interfaces (DLC included); strong judgment on when and how to escalate. - Diagnostics depth: confident with BMC/IPMI logs, Linux logs and CLI checks; structured root-cause analysis. - Deployment experience: you've taken racks from delivery to production, with concrete examples to show for it. - Vendor fluency: you've managed hardware vendors — RMAs, field replacements, escalations — to concrete outcomes. - Impeccable safety and discipline: ESD/LOTO/PPE without exception; clean, labeled, auditable work. - Communication & mentoring: clear status updates and handovers; able to coach engineers during live incidents with composure. - Mobility: willing to visit our other sites in the Paris region as needed.   NICE TO HAVE - GPU-dense platform experience: NVIDIA H-series (H100/H200) or GB-series rack deployments. - High-speed interconnects (InfiniBand/RoCE), RAID/storage (NVMe/SAS/SATA), vendor tooling (iDRAC/iLO/IPMI). - Automation (Python/Bash) for ops tooling and reporting; ticketing (Jira/ServiceNow), inventory/RMA flows. - Hardware qualification, burn-in or factory validation background. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA | New York City, NY | Seattle, WA 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 Frontier AI is on track to be among the most consequential and most adversarially-targeted technology in the world. The capability curve is steep, the adversaries who want these systems are extremely well-resourced, and the security bar this will eventually require is well beyond where the industry operates today. Incremental hardening alone is not going to close that gap, so we need breakthroughs and a group of people to go find them. Security Labs is that team. We run a portfolio of high-risk, high-expected-value security projects: the work that seems impractical until someone optimistic and stubborn enough actually tries it. Projects run on the order of weeks rather than quarters, and each one is either handed off to the Anthropic team that will own it in production or wound down with a writeup of what we learned. We expect a meaningful fraction of our bets not to land. This team is intentionally scrappy and ambitious. We're intentionally iterating fast on high-risk research bets and we expect a meaningful fraction not to land. If a 30% project success rate sounds uncomfortable, or uncharted and chaotic territory isn’t both frightening and exciting, this probably isn't the right fit. There are other places in Anthropic Security doing important work with more structure, less risk, and more certain paths to positive outcomes. The questions we're trying to answer include: Can our core research workflows survive extreme isolation? Can we replace trust with cryptographic guarantees? Can the models themselves become our most effective security control? What would it actually take to defend against a tier-1 state adversary, and how much of that can we build now? Who we're looking for. We're hiring generalists with rare depth. You're a strong software engineer as a baseline, and on top of that you've gone deep in at least one area most engineers don't get near: firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods, reverse engineering, or high-assurance and cross-domain systems. You've built things under your own direction, you're comfortable jumping layers when the problem demands it, and you'd rather take a swing at something that might not work than ship the safe incremental thing. You think the trajectory of AI matters a great deal, you're not comfortable with how the security side of it is going by default, and you'd rather be on the inside building the answer than watching from outside. Current Project Areas The portfolio changes as we learn. The kinds of bets currently in flight or queued: Standing up a prototype high-assurance research cluster: running real Anthropic training and research workloads under extreme isolation and physical security controls, and finding out exactly where productivity breaks and what we'd need to invent to get it back Provable inference: cryptographic verification (zero-knowledge proofs, attestation chains) that a given output came from a specific model running specific code, replacing "trust us" with math Build hypervisor-isolated microVM workload isolation across the fleet Compiling an ML kernel through a formally verified pipeline where every lowering step carries a machine-checked proof of equivalence, making compilation-layer sabotage mathematically detectable Regenerating clusters: automation that spins up a purpose-built cell, runs a workload, and tears the whole thing down on a TTL measured in hours, so attacker persistence has an expiry date Using Claude itself to drive security work end to end: threat modeling new compute platforms, rewriting critical services to zero external dependencies, running the test equipment that validates what hardware datasheets claim Part of your job is deciding what comes next. We hire people we trust to pick good bets, and project selection is owned by the engineers doing the work. Key responsibilities Own Security Labs projects end to end. You'll scope the bet, build the prototype, run it against real workloads, and bring it to either a hand-off or a documented exit Stand up novel security infrastructure fast (isolated clusters, attestation chains, hypervisor and runtime work, verification tooling) optimizing for what we learn rather than for permanence Find the receiving team early, bring them along while you build, and hand them something they actually want to own Work embedded with research and infrastructure teams (Pretraining, RL, Inference, Compute) to test whether their workflows survive what you're proposing, and document precisely where they don't Turn experimental results into short writeups that shape Anthropic's long-term security architecture, and into costed contingency plans we could execute on short notice Help pick the next round of bets and influence the industry to get better along the way Minimum qualifications Genuinely care about where AI is heading and want to work on the security problems that determine whether it goes well. This is the most important thing on this list Have real depth in at least one area most software engineers don't touch (e.g. firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods and verification, reverse engineering and exploit development, or high-assurance / cross-domain systems) Have built and shipped things under your own direction. Maybe you founded a company or research group, maintained an open-source project other people depend on, or shipped research that changed how people in your field work. We weight this far more than where you've worked or for how long Have a track record of choosing the problem yourself and seeing it through, rather than only executing a plan someone else handed you Are comfortable jumping between domains and layers of the stack when the problem calls for it, and have actually done so Have run prototypes or experiments where the goal was answering a hard question rather than shipping a permanent system, including ones that didn't pan out Write clearly enough to turn weeks of work into a couple of pages someone can act on Change your mind when the evidence says to, and are fine being the least-expert person in a room full of specialists Care about defense. Plenty of folks here come from offense and that background is valuable, but what you actually want to spend your time on now is making systems hold up Are a strong programmer (Python plus at least one of Rust, Go, or C/C++) and can stand up real infrastructure without that being the interesting part of your week Preferred qualifications Experience inside airgapped or high-side environments (classified networks, cross-domain solutions, ICS/SCADA, financial trading infrastructure) and the operational realities of working in them A background in offensive security, red teaming, or vulnerability research, with calibrated intuitions for which threats actually matter Familiarity with ML infrastructure (training pipelines, distributed schedulers, inference serving, accelerator hardware) sufficient for grounded conversations with researchers about what their workloads actually need A history of working in environments built around rapid iteration rather than rigid change control: startups, applied research groups, independent consulting, small security shops 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 | New York City, NY | Seattle, WA 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 team Secure Frameworks is the team in Anthropic's Security Engineering org that builds shared security libraries and frameworks the rest of the company builds on. We collaborate closely with teams and leaders across Anthropic to own critical security foundations, including workload identity and authorization, cryptographic frameworks, and the centralized access proxy that  secures traffic to internal applications. Our mission is to make the secure thing easy and the easy thing secure by helping Anthropic engineers get secure behaviour by default and preventing entire classes of vulnerabilities through careful design. We own what we ship, help customers adopt better security practices and at times we work embedded directly in research, infrastructure or product teams. About the role You will design, build and run security foundations used across Anthropic's fleet, from threat model through production, on-call and adoption. Much of the work is greenfield: our infrastructure is growing quickly and the timelines are compressed, so you will help define the architecture rather than inherit it. Depending on your strengths you will focus on one or two of the areas below and contribute across the rest. Build critical security foundations including cryptographic frameworks, mTLS infrastructure, secure serialization, and authorization systems, designed to prevent entire classes of vulnerabilities Partner with product, research, infrastructure, and other security teams to ensure frameworks integrate smoothly with lower-layer security controls Scope, design and build security services and libraries end-to-end, maintain them in production, and drive through ambiguous technical problems with minimal oversight Build and operate the zero-trust access gateway that fronts Anthropic's internal services Design and roll out authorization frameworks so services enforce least privilege consistently instead of each inventing its own access controls Own cryptographic frameworks and libraries Mentor engineers, contribute to hiring, and grow security engineering culture across Anthropic Minimum qualifications 8+ years of software engineering experience building security-relevant systems in production, including leading complex initiatives independently Strong programming skills in Go, Rust or Python Deep understanding of authentication and authorization systems: OAuth 2.0 / OIDC, JWTs, service-to-service auth, policy-based access control Hands-on experience with PKI, X.509, mTLS and workload identity Working knowledge of applied cryptography: choosing and composing primitives correctly, key management, and the ways libraries fail in practice Experience shipping and operating high-reliability services on Kubernetes across cloud and on-prem environments, including being on call for them A track record of bringing clarity and ownership to ambiguous technical problems and driving them to resolution across teams A strong sense of developer experience Clear communication across all levels of the organization Passion for AI safety and the role security engineering plays in building trustworthy AI systems Preferred qualifications Built security frameworks or libraries adopted across an engineering organization, and done the work to drive that adoption Built or operated a zero-trust / BeyondCorp-style access gateway or identity-aware proxy Migrated a fleet to mTLS at scale, including certificate issuance and staged enforcement Maintained or contributed to open-source cryptographic libraries Designed authorization systems using policy languages or relationship-based models Familiarity with ML infrastructure (training, inference serving) 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: $32,000 — $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 | 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 As an AV Engineer focused on Platform & Automation, you'll build and own the software layer of Anthropic's collaboration systems — the tools, integrations, and engineering practices that let a small AV team support a fast-growing global office portfolio. Our rooms, event spaces, and broadcast systems are increasingly managed through APIs and code: device management platforms, DSP and control systems, conferencing administration, ticketing, and paging. Your job is to turn that surface into reliable, team-owned tooling, and to bring software engineering discipline to how we build and maintain it. You can expect a lot of your time writing, shipping, and operating code — fleet health monitoring, automated room testing and ticketing, integrations between our AV platforms and IT systems, and the internal tools that AV Engineering, AV Operations, and Events rely on every day. You'll also help own the administration of the software platforms we already run, and set the standards for how the team version-controls, reviews, tests, releases, and maintains everything from DSP designs to firmware to internal services. Responsibilities Design, build, and ship internal tools and integrations that monitor, test, and manage AV and collaboration systems across every office Develop fleet health monitoring and automated room testing that catch failures before users report them and open actionable tickets automatically Build integrations across device and platform APIs — Q-SYS (including plugins and Lua control scripts), Logitech Sync, Google Meet hardware, digital signage; and IT systems such as Jira, Slack, PagerDuty, and Google Workspace Automate repetitive operational work: provisioning, configuration baselines, drift detection, certificate renewal, and asset data — with code others can read, test, and maintain Own administration and lifecycle of the software platforms behind the AV estate, including firmware and software release management with staged rollouts and rollback plans Operate internal tools as production services, with monitoring, alerting, service metrics, and runbooks, on team-owned repositories and service identities so nothing depends on one person Establish the team's engineering practices: source control, code review, testing, CI/CD, and release — and bring AV configuration under version control, with standards set for integrator deliverables and acceptance verified before changes land Enable AV Engineers, Operations Specialists, and Production staff to contribute safely through templates, guardrails, and review paths built for non-developers Partner with Security, IT Engineering, and Network on least-privilege API access, secrets management, and integration with enterprise standards Gather requirements from AV Operations, Events, and AV Engineering, prioritize the tooling roadmap by operational impact, and decide where to build, buy, or push a vendor to close a gap You May Be a Good Fit If You: Have 10+ years of experience across AV, collaboration, or IT systems engineering, including 4+ years writing, shipping, and maintaining production code that other people depend on Are fluent in at least one general-purpose language: Python, Lua, Go, TypeScript, or similar — and comfortable with shell scripting Practice engineering fundamentals by default: Git-based workflows, code review, automated testing, CI/CD, logging, and observability Understand how AV and collaboration systems work: DSP and control, conferencing platforms, room devices, signal flow, AV-over-IP — well enough to build reliable tools on top of them Have built integrations against REST APIs, webhooks, and vendor SDKs, and know how to handle auth, rate limits, pagination, retries, and partial failure Have owned a tool or service in production over time, not just written it, including fixing it when it broke and handing it off cleanly Have defined engineering practices for a team, especially one where most contributors aren't developers Turn operational pain into well-scoped tooling, and can say no to work that shouldn't be built Thrive in a fast-moving environment where standards are being written rather than inherited Strong Candidates May Also Have Experience With: Q-SYS Lua scripting and plugin development Logitech Sync and CollabOS, and Google Meet hardware administration through the Google Admin console and Admin SDK Google Workspace APIs, GCP (Cloud Run, Cloud Scheduler, Pub/Sub, Secret Manager), and Terraform or other infrastructure-as-code Jira, Slack, and PagerDuty APIs and automation Crestron, Extron, or other control system programming Dante, AES67, NDI, and network fundamentals for AV-over-IP, including multicast, VLANs, and QoS Building with LLMs — agentic automation, LLM-assisted internal tools, or MCP integrations Monitoring and alerting stacks such as Prometheus and Grafana, and containerized deployment Q-SYS Level 2, CTS, or equivalent demonstrated capability Role Specific Location Policy: This role will be based in our San Francisco or New York City office This role is expected to be in office 50% of the time Up to 4 weeks of domestic and international travel annually for platform rollouts, new-office readiness, and on-site testing Business-hours escalation coverage for the tools and platforms this role owns Deadline to apply: None. Applications will be received on a rolling basis. 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: $285,000 — $325,000 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 Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems. Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated, whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA. We’re looking for a systems engineer who enjoys working deep in the stack. You’ll build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of Modal’s container platform. You’ll also work closely with maintainers of gVisor and contribute to the runtime itself when the right fix belongs upstream. WHAT YOU'LL WORK ON: - Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads - Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads - Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime - Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling - Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage - Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware - Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation - Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability - Work across the runtime, scheduler, storage, and GPU infrastructure, and take ambiguous production problems from investigation through deployment YOU MAY BE A FIT IF: - You have strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals - You’ve built or debugged container runtimes, sandboxes, the Linux kernel, or similarly low-level infrastructure - You have strong programming ability in Rust, Go, or another systems language, and an interest in becoming productive in both Rust and Go - You’ve profiled and improved systems where memory movement, I/O, synchronization, or kernel interactions dominate performance - You’re comfortable debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel - You can turn loosely defined production problems into well-designed, reliable systems - You want to own important infrastructure and work closely with both internal teams and customers NICE-TO-HAVE: Any of the following would be helpful, but none is required: - gVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems - Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying - CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling - RDMA and high-performance networking - FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines - Large-memory or multi-GPU inference and training systems - Contributions to open-source systems software Prior gVisor or machine-learning experience is not required. We care more about strong systems fundamentals, curiosity, and the ability to learn unfamiliar parts of the stack. WHY THIS ROLE: The container runtime is directly on the critical path for inference performance. Improvements here can substantially reduce cold starts, increase token throughput, unlock new accelerator types, and make previously impractical workloads possible. This is an opportunity to work on unusually deep systems problems with immediate production impact. You’ll have room to shape the architecture, contribute to open-source runtime technology, and take ownership of foundational infrastructure used by every inference and training workload on Modal.