Engineering Manager, Labs

Engineering Manager, Labs

About the role

At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications.

Anthropic Labs serves as our internal accelerator. We're looking for the next breakout hits that bring substantial revenue or transform an industry. We operate in close partnership with research and build through fast iteration cycles. Past successes include Claude Code and MCP.

We're seeking an Engineering Manager to lead and grow our team of software engineers working on early-stage AI capabilities. You'll create an environment where engineers can thrive in the inherently uncertain world of zero-to-one development while maintaining clear direction and psychological safety for the team. Success in this role requires exceptional people leadership, the ability to facilitate rapid learning cycles, and skill in helping teams navigate the natural ups and downs of early-stage exploration.

You'll partner closely with designers, product managers, and research teams to transform emerging AI capabilities into potential products—and you'll need to be as comfortable shutting down projects that aren't working as you are championing the ones that are.

Responsibilities

• Lead and coach a high-performing team of software engineers through the complexities of zero-to-one development, creating an environment that rewards experimentation and learning over attachment to specific outcomes

• Hire and develop a team of versatile, entrepreneurial engineers who thrive in ambiguity and can flex across problem spaces

• Partner effectively with design, product, and research leaders to align on direction and execution

• Create a balanced environment that encourages both creative exploration and rigorous evaluation of what's working

• Help teams develop structured approaches to testing hypotheses, making kill decisions, and extracting learnings from both successes and failures

• Facilitate effective collaboration between Labs engineers and research teams across Anthropic

• Provide clear, actionable feedback and support engineer growth and development in an environment where projects shift frequently

• Drive adoption of Labs' prototypes and learnings to inform company-wide product strategy

• Represent the Labs perspective and roadmap in discussions with research, product, and leadership stakeholders

• Maintain team stability and morale through the inherent uncertainty of early-stage work

You may be a good fit if you

• Have 5+ years of engineering management experience, with significant time leading teams in ambiguous, early-stage, or zero-to-one environments

• Have a strong technical background as an IC prior to moving into management, ideally including startup or founding engineer experience

• Excel at creating psychological safety and helping teams navigate uncertainty without burning out

• Are skilled at facilitating decision-making rather than imposing solutions—you help your team develop good judgment

• Can model the behaviors you want to see: comfort killing projects, strong opinions loosely held, bias toward action

• Have experience building and retaining teams of generalists who can adapt as priorities shift

• Demonstrate exceptional interpersonal intelligence and can guide teams through rapid pivots while maintaining trust

• Have strong strategic thinking to identify high-potential research breakthroughs and viable paths to productization

• Communicate effectively and can tell the story of Labs' work and impact to leadership and the broader company

• Have a comprehensive technical understanding across full-stack engineering and modern product development, with familiarity in AI/ML concepts

• Care deeply about responsibly pushing the boundaries of AI capabilities in service of Anthropic's mission

Strong candidates may also have

• Experience managing teams that work directly with research organizations or in R&D-adjacent environments

• Track record of helping engineers grow in non-traditional career paths (where success isn't always tied to shipping features)

• Experience with AI/ML products or working knowledge of large language models

• Background in building teams from scratch or scaling early-stage organizations

• Experience managing through organizational change or frequent strategic pivots

What we're not looking for

• Managers who've only succeeded with well-defined roadmaps and stable, long-term projects

• Leaders who struggle to give critical feedback or make hard calls on underperforming projects or team members

• Those who need extensive process and structure to be effective

• Managers who are protective of their team's work rather than focused on learning and impact

Candidates need not have

• 100% of the skills listed above

• Formal certifications or education credentials

• Direct machine learning or AI research experience

Deadline to apply: None. Applications will be reviewed on a rolling basis.