Senior Software Engineer, Infrastructure
Anthropic is seeking experienced Infrastructure Engineers to support the development, scaling, and maintenance of AI systems, with 8+ years of experience and expertise in cloud infrastructure.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.
About the role
Anthropic is seeking talented and experienced Infrastructure Engineers to join our team and support the development, scaling, and maintenance of our cutting-edge AI systems.
We have multiple teams that are currently hiring.
- Data Infrastructure: We build and maintain the data systems powering Anthropic's AI research and products.
- Core Infrastructure: The systems team is responsible for supporting some of the largest, most sophisticated clusters in industry used to train, research, and ultimately serve AI models.
- Runtime Platform: We build and maintain the infrastructure that monitors the health, performance, and efficiency of our AI systems.
- Developer Productivity: The Developer Productivity team enables Anthropic researchers and engineers to be maximally effective in securely developing state-of-the-at models, and products that expose those models to users.
- Product Infrastructure: The Product Infrastructure team enables Anthropic's products to achieve best-in-class performance, reliability, and developer velocity by building and maintaining a robust, efficient, and scalable product infrastructure stack.
- Cloud Inference: We scale and optimize Claude to serve the massive audiences of developers and enterprise companies using AWS and GCP.
Responsibilities:
- Lead build out of industry-leading AI clusters (thousands to hundreds of thousands of machines), partnering closely with cloud service providers on cluster build out and required features
- Consult with different stakeholders to deeply understand infrastructure, data and compute needs, identifying potential solutions to support frontier research and product development
- Set technical strategy and oversee development of high scale, reliable infrastructure systems.
- Mentor top technical talent
- Design processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice
You may be a good fit if you:
- Have 8+ years of relevant industry experience, 3+ years leading large scale, complex projects or teams as an engineer or tech lead
- Are obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement
- Strong proficiency in at least one programming language (e.g., Python, Rust, Go, Java)
- Strong problem-solving skills and ability to work independently
- Have a passion for supporting internal partners like research to understand their needs
- Have excellent communication skills to build consensus with stakeholders, both internally and externally
- Possess deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, AWS, and GCP
Strong candidates may have:
- Security and privacy best practice expertise
- Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
- Low level systems experience, for example linux kernel tuning and eBPF
- Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems
Deadline to apply: None.
The expected salary range for this position is:
Annual Salary:
$300,000—$320,000 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.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate.
We encourage you to apply even if you do not believe you meet every single qualification.
How we're different
We believe that the highest-impact AI research will be big science.