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's Inference organization is responsible for serving Claude to millions of users and enterprise customers with the speed, reliability, and efficiency that frontier AI demands. As we scale across multiple accelerator platforms—GPUs, TPUs, and Trainium—the complexity of our development environment grows in lockstep. We're looking for an Engineering Manager to build and lead a new team focused on developer productivity within Inference: making every engineer in the org dramatically more effective at building, testing, and shipping inference software.

This is a leadership role at the intersection of infrastructure and developer experience. You'll own the toolchains, workflows, and feedback loops that Inference engineers depend on every day. Your work will establish priorities to keep our engineering velocity high and driving investments to keep the larger org productive. You'll partner closely with Anthropic's central Infrastructure organization (where company-wide developer productivity efforts live) while ensuring the Inference org's unique needs are met.

This role is ideal for someone who gets deep satisfaction from unblocking other engineers, who thinks in terms of systems and feedback loops, and who can lead a team that operates at the seam between ML infrastructure and software engineering productivity.

Responsibilities:-Build and lead a high-performing team focused on developer productivity for the Inference organization, hiring engineers who combine infrastructure expertise with a service-oriented mindset

• Own accelerator toolchain management across GPU (CUDA), TPU, and Trainium platforms—keeping compilers, drivers, libraries, and frameworks current, compatible, and well-tested so that Inference engineers can focus on model serving rather than environment issues

• Build infrastructure for efficient accelerator usage during development—including devbox environments, automation for pre- and post-landing validation, and shared tooling that reduces the friction of working across heterogeneous hardware

• Establish and drive productivity metrics across the Inference org, creating dashboards, alerts, and processes that surface slowdowns early (e.g., smoke tests red for extended periods, build times regressing, toolchain breakages) and ensure rapid resolution

• Identify and eliminate inefficiencies across Inference engineering workflows—proactively finding bottlenecks, toil, and friction points that slow down the org, and building systems or driving process changes to address them

• Partner with Anthropic's Infrastructure org to align on company-wide developer productivity initiatives, contribute Inference-specific requirements, and avoid duplicating effort while ensuring Inference's specialized needs (multi-accelerator support, large-scale testing) are well-served

• Coach and develop engineers on your team, providing clear direction, actionable feedback, and growth opportunities in a fast-moving environment

You may be a good fit if you:

• 3+ years of engineering management experience, ideally leading infrastructure, platform, or developer productivity teams

• Strong technical background in systems engineering, build/test infrastructure, or ML infrastructure—you can go deep on toolchain issues, CI/CD pipelines, and developer workflow optimization

• Experience managing toolchains or development environments for compute-intensive workloads (ML training/inference, HPC, large-scale distributed systems)

• Familiarity with at least one accelerator ecosystem (CUDA/GPU, TPU, or Trainium/AWS Neuron) and an appetite to learn the others

• A track record of defining and using engineering metrics to drive organizational improvement—you've built dashboards, set SLOs on developer workflows, or led initiatives to measurably improve engineering velocity

• Experience partnering across organizational boundaries—you know how to advocate for your team's needs while contributing to shared infrastructure efforts

• Strong communication skills and the ability to influence without authority across a technical organization

• A genuine passion for making other engineers more productive, and the empathy to understand their pain points deeply

Strong candidates may also have:

• Experience with ML compiler toolchains (XLA, Triton, NeuronX) or accelerator driver/firmware management at scale

• Bbackground in building or running shared development environments (devboxes, remote development, ephemeral environments) for hardware-dependent workflows

• Experience with CI/CD systems at scale, particularly for workloads involving accelerator hardware

• Familiarity with Kubernetes-based development and job scheduling environments

• Prior experience in a developer productivity or platform engineering role at a fast-growing AI/ML company

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.

Annual Salary:$405,000—$485,000 USD

Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.

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.

Come work with us!
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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process