Engineering Manager, API Core

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

Anthropic is seeking an Engineering leader to lead the API Core team within API. API Core owns the hot path of the Claude API —/v1/messages and the request lifecycle that sits in front of every inference call Anthropic serves. As Claude's usage continues to scale, the efficiency, throughput, and reliability of the core API directly determine how much capacity we can deliver per chip, how quickly we can onboard new workloads, and how fairly we allocate constrained inference resources across customers.

The work spans service-level efficiency (improvements of latency-sensitive paths), throughput scaling (RPS improvements, request multiplexing, connection management), rate limiting and acceleration limits (the quota and fairness systems that mediate access to compute), and the foundational platform abstractions that the rest of the API organization builds on. The team operates at the intersection of product engineering and infrastructure, partnering deeply with Inference, Compute, and the broader Platform org to translate model-serving capacity into customer-facing throughput.

This is a high-impact, high-visibility leadership role reporting to the Head of API Engineering. You will set technical direction, drive delivery against committed efficiency and capacity targets, and represent API Core in cross-org architecture and capacity-planning forums.

Responsibilities

• Own all aspects of the API Core team—hiring, performance management, career development, and overall org health.
• Lead the technical strategy and delivery roadmap for the API hot path: service efficiency, throughput scaling, and the rate-limiting and acceleration-limit systems that govern access to inference capacity.
• Drive multi-quarter initiatives to improve token-path efficiency and reduce per-request overhead, protocol-level optimizations, and architectural changes to the request pipeline to serve the next generation APIs to serve our models.
• Partner with Inference and Compute on capacity planning, regional load balancing, and the engineering response to capacity-constrained periods—including translating compute forecasts into concrete API-tier roadmap commitments.
• Own the rate-limiting and acceleration-limit subsystems end-to-end: quota models, enforcement, fairness across tiers, and the operational tooling that GTM and Support rely on.
• Set and uphold reliability standards for the /v1/messages path: latency SLOs, error-budget management, and the incident-review discipline that keeps a service at this scale operable.
• Build and maintain strong cross-functional relationships with Infrastructure, Inference, Safeguards, and the other API and Platform team to ensure architectural coherence across the platform.
• Represent API Core in API Engineering leadership forums and drive alignment on roadmap, resourcing, and cross-team dependencies.

You may be a good fit if you:

• Have 10+ years experience managing engineering teams, ideally teams building high-throughput, latency-sensitive backend services or developer platforms.
• Have a track record of leading teams that have delivered measurable service-efficiency or throughput improvements on systems operating at significant scale (millions of QPS, multi-region, capacity-constrained).
• Bring depth in at least one of: systems-level performance engineering (Rust, Go, profiling, allocator and runtime tuning), large-scale distributed systems (load balancing, rate limiting, backpressure, request routing), or API platform design.
• Are comfortable making architectural calls under capacity pressure—balancing short-term mitigations against the longer-term rewrites and migrations that compound over quarters.
• Are a strong communicator and partner to non-engineering stakeholders—you can represent technical tradeoffs clearly to GTM, Finance, and executive audiences making capacity and prioritization decisions.
• Build high-performing teams through clear expectations, direct feedback, and genuine investment in engineer growth.
• Operate effectively at the intersection of technical complexity and business urgency, setting realistic commitments while maintaining quality.