{"id":1134378,"url":"https://alion.io/job/anthropic-software-engineer-labs","title":"Software Engineer, Labs","company":{"id":5,"name":"Anthropic","domain":"anthropic.com","url":"https://alion.io/company/anthropic","size_band":"1001-5000","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":78,"open_postings":133,"ghost_share":0,"stale_share":0.895,"repost_share":0,"time_to_fill_p50_days":54,"computed_at":"2026-09-23T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":320000,"max":485000,"currency":"USD","period":"year","gross":null,"usd_annual":485000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"Claude Code","optional":false},{"name":"Interpretability","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Node JS","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"WebSockets","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2025-12-08T21:38:47Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T13:45:06Z","board_verified":true,"closed_at":null,"days_open":288,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":288},"description":"About Anthropic\nAnthropic’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.\nAbout the role\nAt 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.\nAnthropic 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.\nWe'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.\nResponsibilities\nRapidly prototype full-stack applications that showcase emerging AI capabilities, shipping early and often to maximize learning\n\nCollaborate closely with research teams to understand new model capabilities and translate them into intuitive user experiences\n\nWork directly with internal test users and external partners to gather feedback, iterate quickly, and validate (or invalidate) product concepts\n\nDesign and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation\n\nGenerate documentation and insights to guide successful prototypes toward full product teams\n\nAdvocate for user experience and product considerations early in the research process\n\nProvide feedback to research teams about model effectiveness and where capabilities can be improved\n\nFlexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities-context from one project should inform the next\n\nYou may be a good fit if you\nHave 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments\n\nThrive in ambiguity and are energized (not anxious) by uncertainty-you're comfortable working on projects that might not exist in three months\n\nHave a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it's the right tradeoff\n\nAre deeply user-centric-you validate ideas with actual users before over-investing and talk about problems before solutions\n\nCan articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments\n\nHold strong opinions loosely-you advocate forcefully for ideas but change your mind based on evidence\n\nAre a generalist who can transition between different problem spaces as priorities shift\n\nWork independently with good judgment about what matters, without needing constant direction\n\nHave strong technical skills across modern web development stacks (React, Node.js, Python, etc.) and are comfortable with APIs, databases, and cloud technologies\n\nCommunicate effectively and translate complex AI capabilities into intuitive experiences\n\nCare about the societal impacts and ethics of your work\n\nStrong candidates may also have\nExperience building products that involve AI/ML components or working with large language models\n\nExperience collaborating directly with research teams in AI/ML environments\n\nBackground conducting user research, interviews, and usability testing\n\nExperience across both B2B and B2C product development, or in multiple industries\n\nDesign sensibility or hands-on experience with UI/UX for AI-powered applications\n\nExperience with real-time applications, WebSocket implementations, or complex frontend interactions\n\nWhat we're not looking for at this stage\nDeep specialists who can't adapt if their domain becomes irrelevant\n\nEngineers who've only succeeded in big-company structures with well-defined processes and long timelines\n\nPeople who are precious about their work or frame all past projects as successes\n\nThose who need clear roadmaps and get stressed by shifting priorities\n\nCandidates need not have\n100% of the skills listed above\n\nFormal certifications or education credentials\n\nDirect machine learning or AI research experience\n\nDeadline to apply: None. Applications will be reviewed on a rolling basis.\nThe annual compensation range for this role is listed below. \nFor sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\nAnnual Salary:\n$320,000—$485,000 USD\nLogistics\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\nLocation-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.\nVisa 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.\nWe 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.\nYour safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links-visit anthropic.com/careers directly for confirmed position openings.\nHow we're different\nWe 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.\nThe 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.\nCome work with us!\nAnthropic 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.","description_format":"text","description_chars":8572,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Flexible schedule","Generous vacation","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Code Intelligence","Foundation Models","AI Safety & Alignment","AI Research Labs"],"lifecycle":[{"event":"open","at":"2026-09-23T06:56:22Z"}],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.341,"p_room":0.28,"age_days":288,"expected_fill_days":54,"reasons":["conf:1","win:tail","crowd:brand"],"computed_at":"2026-09-23T15:37:52Z"},"pay":{"stated_usd_annual":485000,"is_top_pay":true},"html_url":"https://alion.io/job/anthropic-software-engineer-labs","json_url":"https://alion.io/job/anthropic-software-engineer-labs.json","meta":{"generated_at":"2026-09-23T15:37:52Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}