What are the responsibilities and job description for the Staff Software Engineer, Infrastructure position at Anthropic?
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. By joining our Infrastructure team, you will have the opportunity to work on groundbreaking AI technologies and contribute to the development of frontier models, supporting Anthropic's mission to create safe and reliable AI systems that benefit humanity.
We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the infrastructure teams where they'll have the greatest impact and growth potential:
- Data Infrastructure: We build and maintain the data systems powering Anthropic's AI research and products. You'll design and optimize data pipelines using tools like Spark, Airflow, and dbt across GCP and AWS. Your work will ensure reliable, scalable data infrastructure while implementing governance best practices and driving continuous improvement.
- 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. Your work will be crucial in ensuring Anthropic is able to continue reliably and safely training frontier models. You will be responsible for building systems and running large Kubernetes clusters with GPU/TPU/Tranium workloads.
- Observability: We build and maintain the infrastructure that monitors the health, performance, and efficiency of our AI systems. You'll work across teams to implement monitoring solutions using tools like Prometheus, Splunk, and Grafana, while developing automated approaches for dashboards and alerts. Your work will create reliable, low-maintenance systems that enable proactive monitoring and operational excellence.
- 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. All of the code written at Anthropic goes through systems/infrastructure built and maintained by our team. We aim to make development at Anthropic secure, efficient, and delightful.
- 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.
- Claudification: The Claudification team works on exciting LLMs meet developer productivity problems.
- Cloud Inference: We scale and optimize Claude to serve the massive audiences of developers and enterprise companies using AWS and GCP. Our team's engineers are extremely high leverage because we simultaneously drive two of our company's largest and fastest growing revenue streams, and we optimize the consumption of one of our most precious resources: compute. Our team ensures our LLMs meet rigorous safety, performance, and security standards and enhance our core infrastructure for packaging, testing, and deploying inference technology. Your work will increase the scale at which our services can operate and accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms.
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 10 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 also:
- 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. Applications will be reviewed on a rolling basis.
