Staff Software Engineer, Inference at Anthropic

✨ The Stack take on this Anthropic job

• 🏢 Anthropic has 53 jobs here, 36 with visa sponsorship see all
• 📊 19 Software Engineer jobs in Ireland in the last 60 days see them
• 🛂 Visa: Critical Skills Employment Permit. Occupations on the Critical Skills list: €40,904 a year with a relevant degree guide
• 💡 No salary shown. Ask Anthropic if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Design, implement and maintain large-scale inference infrastructure to serve models reliably and efficiently.
- Build intelligent request routing, autoscaling and fleet orchestration across heterogeneous accelerators and cloud regions.
- Optimize compute efficiency through batching, caching and performance tuning for production workloads.
- Integrate new accelerator platforms and support multi-accelerator deployments and research workloads.
- Develop deployment pipelines, observability and tools that enable safe, repeatable model releases.
- Collaborate with research, SRE and engineering teams to balance production reliability and experimental needs.

Requirements:
- Strong software engineering background with significant experience in distributed systems and performance optimization.
- Experience with service orchestration, request routing, load balancing or traffic management at scale.
- Familiarity with LLM inference patterns (batching, caching), multi-accelerator deployments and ML system performance trade-offs.
- Proficiency in Python or Rust and practical experience with cloud infrastructure (AWS, GCP) and Kubernetes.
- Track record of shipping production systems, writing reliable automation and improving system observability.
- Results-oriented, collaborative, comfortable with ambiguity and motivated by both product and research impact.

Responsibilities

The Staff Software Engineer will design and maintain critical inference infrastructure to serve Claude to millions of users while optimizing compute efficiency. They will tackle complex distributed systems challenges and integrate new AI accelerator platforms to support research and production workloads.

Requirements

Candidates should have significant experience in distributed systems, performance optimization, and large-scale service orchestration. Proficiency in Python or Rust and familiarity with cloud infrastructure or machine learning deployment at scale is highly valued.

Key skills

• Distributed systems — in 342 other listings on The Stack
• Performance optimization — in 84 other listings on The Stack
• Service orchestration — in 1 other listing on The Stack
• Request routing — in 3 other listings on The Stack
• LLM inference — not in any other listing on The Stack
• Batching strategies — in 2 other listings on The Stack
• Multi-accelerator deployments — in 1 other listing on The Stack
• Machine learning systems — in 3 other listings on The Stack
• Load balancing
• Traffic management
• Kubernetes
• Cloud infrastructure
• AWS
• GCP
• Python
• Rust

On The Stack (as of 2026-11-05)

• Anthropic has 52 other listings on The Stack, 35 of them marked as offering visa sponsorship.
• 37 visa-sponsored jobs in Ireland on The Stack, posted in the last 60 days.
• 195 visa-sponsored software engineer jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about Anthropic

Is this Staff Software Engineer, Inference role still open?

It was posted on 2026-10-13 and is listed as active on The Stack. Confirm on Anthropic's application page before applying.

Does Anthropic offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Anthropic's site.

Where is this role located?

The listing gives the location as Ireland. It is marked on-site.

What skills does this role ask for?

The listing names: Distributed systems, Performance optimization, Service orchestration, Request routing, LLM inference, Batching strategies, Multi-accelerator deployments, Machine learning systems, Load balancing, Traffic management, Kubernetes, Cloud infrastructure, AWS, GCP, Python, Rust.