Anthropic

1 month ago

Staff + Sr. Software Engineer, Cloud Inference Launch Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Own the end-to-end cloud inference launch workflow for Claude across AWS, GCP, and Azure. Drive fast, reliable model launches, scale inference servers, and improve performance and cost through CI/CD, observability, and cross-platform optimization. Collaborate with the inference and platform teams to reduce validation time and push frontier models into production across providers.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key 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) to cloud platforms, owning the platform-specific integration that gets them to production.
•Identify and fix gaps that cause inference to behave differently across first-party and CSPs—config drift, observability, deployment patterns, cross-platform bugs—at the source.
•Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines, and correctness checks.
•Drive down merge-to-production cycle time by making validation faster, parallel, and cost-effective to run on the constrained accelerator pool without sacrificing reliability.

Pay and Benefits

Salary: USD 320,000 - 485,000 annually

Equity and Bonus:Equity

Perks:Paid LeaveParental LeaveFlexible HoursEquity

Key Requirements

•Strong software engineering experience with high-performance, large-scale distributed systems serving millions of users.
•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.
•Track record of building automation or test infrastructure that measurably improved release velocity or reliability.
•Autonomy and ownership of problems end-to-end, including work outside your job description.
•Fast learner who can ramp up on new technologies, hardware platforms, and provider ecosystems.

Experience:Cloud computingDistributed systemsAi infrastructure

Education:Bachelor's

Skills:PythonRustKubernetesTerraformDockerAWSGCPAzureInfrastructure as code

Languages:English

Tech Stack:PythonRustKubernetesTerraformDockerAWSGCPAzure

Company Brief

Anthropic

Develops large-scale AI systems and safety research to create reliable, steerable, and interpretable AI assistants and models for commercial and research applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2021

Website LinkedIn

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Anthropic

1 month ago

Staff + Sr. Software Engineer, Cloud Inference Launch Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 20 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Sr. Manager level

Key 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) to cloud platforms, owning the platform-specific integration that gets them to production.
•Identify and fix gaps that cause inference to behave differently across first-party and CSPs—config drift, observability, deployment patterns, cross-platform bugs—at the source.
•Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines, and correctness checks.
•Drive down merge-to-production cycle time by making validation faster, parallel, and cost-effective to run on the constrained accelerator pool without sacrificing reliability.

Pay and Benefits

Salary: USD 320,000 - 485,000 annually

Equity and Bonus:Equity

Perks:Paid LeaveParental LeaveFlexible HoursEquity

Key Requirements

•Strong software engineering experience with high-performance, large-scale distributed systems serving millions of users.
•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.
•Track record of building automation or test infrastructure that measurably improved release velocity or reliability.
•Autonomy and ownership of problems end-to-end, including work outside your job description.
•Fast learner who can ramp up on new technologies, hardware platforms, and provider ecosystems.

Experience:Cloud computingDistributed systemsAi infrastructure

Education:Bachelor's

Skills:PythonRustKubernetesTerraformDockerAWSGCPAzureInfrastructure as code

Languages:English

Tech Stack:PythonRustKubernetesTerraformDockerAWSGCPAzure

Company Brief

Anthropic

Develops large-scale AI systems and safety research to create reliable, steerable, and interpretable AI assistants and models for commercial and research applications.

Industry: AI & Machine Learning

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Francisco, United States

Founded: 2021

Website LinkedIn