Staff+ Software Engineer, Claude Managed Agents

Anthropics 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.

We are looking for experienced backend and distributed systems engineers to join the Agentic Systems team within our Platform organization. Agentic Systems builds Claude Managed Agents: the hosted platform for building running and scaling production agents on Claude. Instead of every developer hand-rolling an agent loop sandboxed execution state management credential handling and error recovery and reworking all of it with every model release Managed Agents pairs an Anthropic-built agent harness with production infrastructure for sessions environments tools memory and permissions exposed through a small set of composable APIs designed to stay stable as models and harnesses evolve. It powers agentic products inside Anthropic as well as those built by customers on the Claude Platform.

Managed Agents is in public beta and growing quickly and this is still an early team with a lot of surface area left to define. Youll drive 0 1 efforts from ideation through GA own systems end to end from API design through operations and partner closely with product research developer experience and go-to-market teams to figure out what managed should mean for the next generation of agents. You should be comfortable going deep on hard distributed systems problems care about APIs as a product in their own right and be motivated by turning ambiguous ideas into high-quality shipped platform capabilities that other engineers build their products on.

Scale the platform. Managed Agents runs long-lived stateful sessions that execute autonomously for minutes or hours/days persist through disconnections and resume cleanly across Anthropic-hosted sandboxes self-hosted environments on customer infrastructure and other clouds. Youll design and operate the systems underneath that: durable session and event storage sandbox orchestration streaming scheduling and multi-tenant isolation. Reliability latency and cost efficiency are product features here and youll own them in production.

Evolve the harness and prove it with evals. The harness is the loop that calls Claude routes tool calls manages context (caching compaction memory) and recovers from errors. Harnesses encode assumptions about what the model cant yet do on its own and those assumptions go stale as models improve. Youll work alongside research to revisit them with each model generation build the eval infrastructure that measures harness quality against research baselines and real customer workloads and hold the bar that lets us say our harness gets the most out of Claude.

Help builders get the most out of Claude. Our customers internal and external are building agents both as products for their users and to transform their own operations. Youll ship the capabilities that raise the ceiling on what those agents can do: outcome-driven execution where developers specify success criteria and a budget and Claude iterates until it gets there multi-agent orchestration memory and the observability and tracing that make long-running agents debuggable. The goal is the highest intelligence per dollar of any agent platform delivered safely.

Design APIs that outlast their implementations. Agents environments sessions vaults and event streams are interfaces thousands of developers build against and that our own products depend on. Youll shape those primitives versioning ergonomics across API SDK and CLI sensible defaults escape hatches with the expectation that the implementations underneath will change many times while the contracts hold.

• Have a minimum of 8 years of practical experience as a backend distributed systems or infrastructure engineer
• Have built and operated stateful long-running or high-throughput systems in production workflow orchestration streaming storage container or job orchestration and can reason rigorously about durability consistency failure modes and cost
• Have strong product sense and treat API design as a craft; you care about the developer on the other side of the interface and can ideate and execute product strategy with cross-functional partners in new domains
• Are excited by 0 1 work and comfortable navigating ambiguity and have ideally operated in both early-stage and more mature team or company settings
• Use Claude or other AI tools as a core part of how you build software and have opinions about what makes an agent harness good
• Take full ownership of your work from design through build deployment and operations (including on-call) to iterating on and improving what you ship
• Care about building systems that other engineers and businesses love to use and about doing so safel

• Built or contributed to an agent harness agent framework or LLM orchestration layer tool execution context management memory or multi-agent coordination
• Worked on an AI or ML platform (model serving inference infrastructure developer tooling) at an AI lab or an AI-native product company or led adoption of AI-driven development inside an engineering organization
• Built evaluation or benchmarking infrastructure for LLM or agent systems
• Experience with durable execution or workflow engines sandboxed code execution or container runtimes
• Shipped public developer platforms APIs or SDKs used by external developers at scale

Deadline to apply:None. Applications will be reviewed on a rolling basis.

Location Preference: Preference will be given to candidates based in NY SEA SF or the Bay Area given the current location of team.

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

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. Were 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.

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 aboutour policy for using AI in our application process.