Staff Cloud Inference Launch Engineer for Scalable AI

Anthropic; San Francisco (CA); On-site; USD 320,000 - 485,000; Full time

Job summary

Anthropic is seeking an experienced Cloud Inference Engineer to scale Claude across major cloud platforms and drive end‑to‑end inference deployment. You will own API integrations, routing, inference execution, capacity management, and day‑to‑day operations for production workloads.

You will work on the model and inference launch pipeline, validating new launches, performance improvements, safeguards, and cross‑platform correctness to ensure reliable delivery to customers.

Qualifications

• Strong interest in LLM serving; prior inference or ML experience is not required.
• Significant software engineering experience with large-scale distributed systems serving millions of users.
• Proven ability to build automation or test infrastructure that measurably improved release velocity or reliability.
• Experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration.
• Thrive in cross-functional collaboration with both internal teams and external partners.

Responsibilities

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first‑party platform.
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform‑specific integration that gets them to production.
• Identify and dive deep on the gaps that make inference behave differently across first‑party and CSPs — config drift, observability, deployment patterns, hard cross‑platform bugs — and fix them at the source rather than building platform‑specific workarounds.
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge‑to‑production cycle time by making validation faster, more parallel, and cost‑effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real‑world production workloads

Skills

Distributed systems

Software engineering

Automation

Cloud platforms

Cross-functional collaboration

Autonomy

Learning new tech

Education

Bachelor's degree

Tools

Kubernetes

Infrastructure as Code

Container orchestration

Python

Rust

Job description

Anthropic is seeking an experienced Cloud Inference Engineer to scale Claude across major cloud platforms and drive end‑to‑end inference deployment. You will own API integrations, routing, inference execution, capacity management, and day‑to‑day operations for production workloads.

You will work on the model and inference launch pipeline, validating new launches, performance improvements, safeguards, and cross‑platform correctness to ensure reliable delivery to customers.