Software Engineer, Labs

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. 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 versatile, entrepreneurial engineers to join Labs. In this role, you'll work at the intersection of cutting-edge research and real-world application, rapidly building and testing new experiences, working directly with researchers and users, and generating the insights that shape Anthropic's product future. You'll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory. Responsibilities Rapidly prototype full-stack applications that showcase emerging AI capabilities, shipping early and often to maximize learning Collaborate closely with research teams to understand new model capabilities and translate them into intuitive user experiences Work directly with internal test users and external partners to gather feedback, iterate quickly, and validate (or invalidate) product concepts Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation Generate documentation and insights to guide successful prototypes toward full product teams Advocate for user experience and product considerations early in the research process Provide feedback to research teams about model effectiveness and where capabilities can be improved Flexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities—context from one project should inform the next You may be a good fit if you Have 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments Thrive in ambiguity and are energized (not anxious) by uncertainty—you're comfortable working on projects that might not exist in three months Have a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it's the right tradeoff Are deeply user-centric—you validate ideas with actual users before over-investing and talk about problems before solutions Can articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments Hold strong opinions loosely—you advocate forcefully for ideas but change your mind based on evidence Are a generalist who can transition between different problem spaces as priorities shift Work independently with good judgment about what matters, without needing constant direction Have strong technical skills across modern web development stacks (React, Node.js, Python, etc.) and are comfortable with APIs, databases, and cloud technologies Communicate effectively and translate complex AI capabilities into intuitive experiences Care about the societal impacts and ethics of your work Strong candidates may also have Experience building products that involve AI/ML components or working with large language models Experience collaborating directly with research teams in AI/ML environments Background conducting user research, interviews, and usability testing Experience across both B2B and B2C product development, or in multiple industries Design sensibility or hands-on experience with UI/UX for AI-powered applications Experience with real-time applications, WebSocket implementations, or complex frontend interactions What we're not looking for at this stage Deep specialists who can't adapt if their domain becomes irrelevant Engineers who've only succeeded in big-company structures with well-defined processes and long timelines People who are precious about their work or frame all past projects as successes Those who need clear roadmaps and get stressed by shifting priorities 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. The annual compensation range for this role is listed below.  For sales roles, the rang