Location requirements
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.
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.
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
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
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
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
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 expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
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. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
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