About the role:
Anthropic is seeking an Engineering Manager to lead our Research Prototyping team, a critical function that bridges cutting-edge AI research and transformative product experiences. As the Engineering Manager for Research Prototyping, you'll create an environment where engineers an designers can rapidly experiment with emerging AI capabilities, validate breakthrough ideas, and accelerate the path from research innovation to user impact.
You'll lead a team that operates at the frontier of what's possible with AI, building prototypes that push model capabilities to their limits while generating crucial learnings for both research and product teams. Success in this role requires a 0-to-1 mindset, the ability to coach engineers and designers through the idea maze as they explore the properties and potential of large language models, and the ability to balance rapid experimentation with strategic thinking about AI's transformative potential.
About Research Prototyping
The Research Prototyping team serves as Anthropic's innovation accelerator, identifying paradigm-shifting AI capabilities and building prototypes that demonstrate their potential. It is the most R&D-org-like of the Product teams, operating with a "fail fast" mentality and accepting high failure rates in exchange for breakthrough discoveries. Prototypes range from internal tools that make researchers more productive to ambitious demos that showcase entirely new AI paradigms. Successful projects may spin out into dedicated product teams or inform critical research directions.
Responsibilities:
- Lead and grow a team of versatile engineers who thrive in 0-to-1 environments and can rapidly prototype across the full stack
- Partner closely with research teams to identify emerging capabilities with transformative potential and translate them into compelling prototypes
- Create a culture that embraces experimental failure as a path to breakthrough success, while maintaining momentum through rapid iteration cycles
- Develop frameworks for evaluating prototype success beyond traditional metrics, focusing on capability breakthroughs and research learnings
- Build strong partnerships across Product and Research teams to ensure smooth transitions for successful prototypes
- Champion lightweight, prototype-first development practices that maximize learning velocity
- Guide the team in building "living evals" that provide rapid feedback loops between product experiences and model development
- Represent the voice of ambitious, transformative product possibilities in research planning discussions
- Foster an environment where engineers feel empowered to pursue bold ideas and pivot quickly based on learnings — without falling in love with ideas that are no longer yielding learnings
You may be a good fit if you:
- Have 5+ years of engineering management experience, with significant time leading teams in highly ambiguous, research-oriented environments
- Excel at managing high-variance outcomes and helping teams navigate the emotional rollercoaster of experimental work
- Have deep technical expertise across full-stack development, ML/AI systems, and emerging technologies
- Demonstrate exceptional ability to identify high-potential ideas from a sea of possibilities
- Can context-switch rapidly between multiple experimental projects while maintaining strategic clarity
- Have experience translating research breakthroughs into user-facing products or demos
- Are passionate about pushing the boundaries of what's possible with AI
- Have strong communication skills to articulate the value of failed experiments and successful breakthroughs alike
- Care deeply about the societal impacts of advanced AI systems
Strong candidates may also have experience with:
- Building and leading teams focused on emerging technologies or R&D
- Creating developer tools, AI agents, or other productivity-enhancing systems
- Working directly with machine learning researchers on productization efforts
- Managing portfolios of high-risk, high-reward technical projects
- Building prototyping infrastructure and frameworks that accelerate experimentation
- Leading through extreme pivots and helping teams maintain morale through failure
- Creating compelling demos that communicate complex technical capabilities
- Working with LLMs, multi-agent systems, or other frontier AI technologies
Deadline to apply: None. Applications will be reviewed on a rolling basis.
