Software Engineer (Research Infrastructure)

Join Anthropic, a leading AI safety and research company, as a Software Engineer in our Research Productivity organization. In this role, you will design, build, and scale infrastructure and systems that support our rapidly increasing research demands. You will independently scope and lead complex engineering projects, drive cross-organizational alignment, and make architectural decisions that shape our research infrastructure. You will also partner directly with researchers to understand their workflows and anticipate their changing needs. This is a unique opportunity to work in a fast-paced, startup-like environment with high autonomy and impact.

• Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve.
• Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system.
• Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams.
• Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders
• Experience making architectural decisions that other engineers and teams build on top of
• Experience designing, building, and operating large-scale distributed systems or infrastructure in production
• Demonstrated ability to operate effectively in ambiguous, fast-changing environments
• Strong software engineering fundamentals and hands-on coding ability
• A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
• Strong candidates may also have
• Experience building infrastructure or platforms specifically for research or machine learning workflows
• Direct experience navigating the reliability and architectural challenges that come with rapidly scaling systems
• Familiarity with the compute, tooling, and workflow needs of large-scale machine learning research
• Experience with distributed systems, cloud infrastructure, and infrastructure-as-code
• Prior experience as a technical lead or mentor for other engineers
• Experience operating in a startup or startup-like environment, i.e. a small, fast-moving team with high autonomy
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed