Staff+ Software Engineer, Platform

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.

We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages.

You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day.

We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential.

Platform Acceleration: We work on maximizing the developer productivity of product engineers at Anthropic. You'll architect and optimize the critical development infrastructure that powers our AI product development, including dev environments, observability, and CI/CD pipelines. You’ll partner closely with product teams to understand their development workflow and eliminate friction points. Your work will have an extraordinary multiplier effect, enhancing productivity across our entire product organization and accelerating our mission.

Service Infra: we build and maintain the core infrastructure that powers Anthropic's engineering organization, from service mesh and observability systems to deployment pipelines and shared libraries. Our work enables product teams to build and operate reliable services at scale, making us a critical force multiplier across the entire company.

Multicloud: We build and maintain the infrastructure that enables Anthropic to operate across multiple cloud providers. We focus on cloud-agnostic tooling, cross-cloud networking, and multi-region deployments.

Auth & Identity: We build and maintain the critical infrastructure that powers identity and authentication across Anthropic's product suite. We work closely with product teams, security, support, and trust & safety as customers. We create scalable solutions for user authentication, authorization, role-based access control, and single sign-on that form the backbone of our company's identity management operations. We maintain a user-centric approach, building reliable systems that our users and company can depend on as we tackle complex challenges at the intersection of security, scalability, and user experience.

Connectivity: Our mission is to make Claude the most connected AI. We own the MCP proxy that routes every tool call and the OAuth and token management that keeps connections authenticated. We're also the core contributors to the MCP spec — now an open standard under the Linux Foundation — and maintain the official Python and TypeScript SDKs. You'll work on problems where reliability and enterprise trust are the bar: token refresh at scale, admin controls that let IT govern what agents can do, proxy infrastructure that stays up when partner servers don't. We ship for claude.ai, Claude Code, Cowork, and the API. Relevant experience includes OAuth, API gateways, multi-tenant platforms, building for enterprise, and MCP.

API Distributability: The Claude API today is a rapidly growing platform serving developers and enterprises at scale—but reaching the next tier of enterprise customers requires transforming how and where we deploy it. The Distributability team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it.

Platform Intelligence: We build the training systems that adapt Claude to specific customer workloads. The core problem is task-specific adaptation: getting the right intelligence, cost, and latency profile for a particular use case, and building toward systems where that adaptation can deepen as the customer's usage grows. We work closely with research on training methods and with agent platform teams on data paths. Relevant experience: ML training infra, production ML pipelines, backend engineering. Finetuning experience is a plus.

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. 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.

• Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent
• distributed systems, cloud-native products, developer tools, or external developer facing products
• Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end

$405,000—$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.