Engineering Manager, Inference Infrastructure
Anthropic· Software Engineering - Infrastructure
Hybrid (San Francisco, CA), Hybrid (New York City, NY), Hybrid (Seattle, WA)$405k - $625kFull-timePosted 1mo ago
About the role
Engineering Manager responsible for the control plane coordinating Anthropic's inference fleet, leading ML platform, infrastructure, and distributed-systems engineers to ensure efficient, reliable, and scalable inference across heterogeneous hardware and multiple cloud providers.
Responsibilities
- Own the technical roadmap for how the inference fleet is coordinated — where traffic goes, where capacity lives, how caches are placed, how fast the system reacts to demand, and the protocols that keep the control plane and the inference engines in sync
- Partner with the product, inference engine, performance, and capacity teams to identify throughput, latency, utilization, and cost wins, then turn those into shipped improvements with measurable results
- Build the group's habit of quantitative modeling: claim a win only when you can measure it, and know before you ship what the expected effect is
- Set technical strategy for how the control plane evolves across heterogeneous hardware, across multiple cloud providers, and across all our serving surfaces
- Run the group's operational backbone — on-call rotations, incident response, postmortem review, deploy safety — so the teams can ship aggressively without the system becoming fragile
- Create clarity at a seam: this group sits between the API surface, the inference engines, capacity planning, and the cloud deployment teams
- Develop and retain strong existing teams, and hire against a high technical bar
- Coach engineers through a roadmap where priorities shift
- Shape team structure as the scope grows: decide where the boundaries between problem areas should sit, and grow leads who can own each
- Pick up slack when it matters. These are small teams on a critical path; sometimes the EM is the one unblocking a stuck initiative or synthesizing a design debate
Qualifications
- Engineering management experience leading teams on critical-path production infrastructure at scale
- A deep systems background — load balancing, scheduling, cluster orchestration, autoscaling, cache-coherent distributed state, high-performance networking, or similar — with enough depth to make architectural calls about how a large fleet is coordinated and to evaluate candidates who go to the kernel and framework level
- Experience shipping performance or efficiency improvements in large-scale systems, and the ability to explain, with numbers, what the impact was — including the cost side, not just the latency side
- Experience running production infrastructure with real operational stakes: on-call, incident response, capacity events, deploy discipline
- A results-oriented, impact-driven approach, and comfort working in a space where throughput, latency, cost, stability, launch timelines, and feature velocity all pull in different directions
- Ability to build strong relationships across team boundaries — this is a seam role, and much of the job is making sure other teams can rely on yours
- Curiosity about machine learning systems — you don't need an ML research background, but you should want to learn how transformer inference actually works and how that shapes the systems problems
Skills
Required:Engineering managementSystems designPerformance optimizationOn-call and incident response
Benefits
- Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space
Last updated Sep 2, 2026. Interested? Apply on the company site.
About Anthropic
building reliable, interpretable, and steerable AI systems
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
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