Staff+ Software Engineer (Inference Velocity)

• This is a senior IC role with broad technical ownership. You’ll set technical direction for the team’s toolchains, workflows, and feedback loops, and you’ll be the one making the hard calls on architecture, prioritization, and tradeoffs across heterogeneous accelerator platforms
• You’ll pair with the team’s Engineering Manager, who owns hiring and people development, while you own the technical roadmap and drive the work. You’ll also partner closely with Anthropic’s central Infrastructure org, where company-wide developer productivity lives, to make sure Inference’s multi-accelerator reality is well served without duplicating effort
• Set technical direction for Inference Developer Productivity, owning the architecture and roadmap for toolchains, dev environments, and CI/CD across GPU (CUDA), TPU, and Trainium platforms
• Be the technical owner of accelerator toolchain management: compilers, drivers, libraries, frameworks, kept current, compatible, and well-tested so Inference engineers focus on model serving instead of environment archaeology
• Design and build infrastructure for efficient accelerator usage during development, including devbox environments, pre- and post-land validation automation, and shared tooling that reduces the cost of working across heterogeneous hardware
• Define and instrument productivity metrics for the Inference org, building the dashboards and alerting that surface regressions early (smoke tests red for extended periods, build times creeping up, toolchain breakages) and drive them to resolution
• Proactively hunt down bottlenecks, toil, and friction across Inference engineering workflows, then design and build the systems that eliminate them
• Act as the technical counterpart to Anthropic’s central Infrastructure org, aligning on shared developer productivity initiatives, contributing Inference-specific requirements, and making the call on build vs. adopt
• Mentor engineers on the team through design review, code review, and direct collaboration, raising the technical bar without owning headcount

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents
• Inclusive fertility benefits via Carrot Fertility
• 22 weeks of paid parental leave
• Flexible paid time off and absence policies
• Mental health support for you and your dependents
• Competitive salary and equity packages
• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
• Retirement plans with competitive matching
• Life and income protection plans
• $500/month flexible wellness and time saver stipend
• Commuter benefits
• Annual education stipend
• Home office stipends
• Relocation support for those moving for Anthropic
• Daily meals and snacks in the office

• This role is for someone who has been the technical anchor on a platform or infrastructure team before, who thinks in systems and feedback loops, and who gets real satisfaction from the moment another engineer stops fighting their environment and starts shipping
• Experience owning toolchains or development environments for compute-intensive workloads (ML training or inference, HPC, large-scale distributed systems)
• Deep background in systems engineering, build/test infrastructure, or ML infrastructure, with the ability to go hands-on with toolchain issues, CI/CD pipelines, and developer workflow optimization
• A track record of defining and using engineering metrics to drive improvement: you’ve built dashboards, set SLOs on developer workflows, or led initiatives that measurably improved engineering velocity
• Strong written and verbal communication, and the ability to influence technical direction without formal authority
• 8+ years of software engineering experience, with significant time as the technical lead or anchor on an infrastructure, platform, or developer productivity team
• Real depth in at least one accelerator ecosystem (CUDA/GPU, TPU, or Trainium/AWS Neuron) and genuine appetite to learn the others
• Experience driving technical alignment across organizational boundaries, advocating for your team’s needs while contributing to shared infrastructure
• Experience with ML compiler toolchains (XLA, Triton, NeuronX) or accelerator driver/firmware management at scale
• Experience with CI/CD systems at scale, particularly for workloads involving accelerator hardware
• Background building or running shared development environments (devboxes, remote development, ephemeral environments) for hardware-dependent workflows
• Prior tech lead experience on a developer productivity or platform engineering team at a fast-growing AI/ML company
• Familiarity with Kubernetes-based development and job scheduling environments