Staff+ Software Engineer, Enterprise (Platform)

• Define and drive multi-year technical strategy for foundational enterprise systems, including our distributability and multi-cloud direction
• Identify and personally lead the highest-complexity, highest-impact engineering initiatives spanning multiple teams
• Serve as a primary technical decision-maker for major architectural decisions with org-wide scope
• Design the platform primitives-identity, permissions, governance, connectivity, and usage data-that other product teams build on
• Partner with teams such as Inference and Platform on foundational systems, Customer Success for the voice of the customer, and Infrastructure and Safeguards on security, privacy, and responsible deployment
• Mentor and develop senior engineers across the org, and drive alignment across Product, GTM, and Customer Success while proactively addressing systemic technical risks

• Have 8+ years of engineering experience with a clear track record operating at Staff or equivalent technical leadership level
• Have deep expertise in distributed systems and API architecture, and are effective writing design docs, making architectural calls, and coding in critical paths
• Have shaped technical strategy at a Cloud Service Provider or large-scale Enterprise SaaS company
• Bring strong domain expertise and intuition in enterprise areas such as security, identity, compliance, governance, permissions, and connectivity
• Drive the highest-leverage technical outcomes without formal authority-you lead through influence, quality of thinking, and trust
• Are highly effective across org boundaries-you build trust with GTM, Platform, Inference, Infrastructure, Privacy, Safeguards, and business stakeholders alike

Strong candidates may also have

• Experience with multi-cloud or distributable deployments of complex systems
• Experience building the data foundations for enterprise administration-entitlements, metering, usage and cost visibility, 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.

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.

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., Enterprise is central to Anthropic’s mission. The organizations that could benefit most from Claude often have the most demanding needs, with rigorous requirements around end-user experience, procurement, security, and permissions. We believe earning their trust is essential to ensuring AI benefits the world broadly. We’re looking for a Staff+ Platform Engineer for our Enterprise pillar-the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, the systems you design-identity, permissions, governance, connectivity, and the data foundations beneath them-are what make it possible. This is a high-agency role: you’ll design the abstractions other teams want to adopt, help the team evaluate hard tradeoffs, and be the engineer in the room who can interface with executives and security teams from the world’s largest companies., 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.