{"id":127699,"url":"https://alion.io/job/elicit-ai-engineer","title":"AI Engineer","company":{"id":48045,"name":"Elicit","domain":"elicit.com","url":"https://alion.io/company/elicit","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Oakland, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":195000,"max":260000,"currency":"USD","period":"year","gross":null,"usd_annual":260000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Asyncio","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"CI/CD","optional":true},{"name":"GitHub","optional":true},{"name":"Next.js","optional":true},{"name":"Python","optional":true},{"name":"React.js","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2024-06-11T05:21:26Z","employer_posted_date":"2024-06-11","last_verified_at":"2026-10-17T19:34:14Z","board_verified":true,"closed_at":null,"days_open":858,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":857},"description":"About Elicit\nElicit is an AI research assistant that uses language models to help researchers figure out what’s true and make better decisions, starting with common research tasks like literature review.\nWhat we're aiming for:\nElicit radically increases the amount of good reasoning in the world.\nFor experts, Elicit pushes the frontier forward.\n\nFor non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit.\n\nElicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes. This expands our collective understanding of safe AGI architectures.\n\nVisit our Twitter to learn more about how Elicit is helping researchers and making progress on our mission.\nWhat is an \"AI Engineer\"?\nAI engineering is a new category of technical work. Its emergence is linked to the increasing availability of powerful new artificial intelligence tools: notably generative machine learning systems like large language models.\nThe term was suggested by swyx on the Latent Space podcast and we've written about it on our blog before.\nElicit predicted the rise of powerful ML systems even before GPT-1 was trained, and has the deepest experience of building trustworthy, capable, and transparent applications using these tools.\nIf you're a software engineer who relishes the more difficult parts of backend code-like concurrency, fault-tolerance, and distributed systems-you could be a great AI engineer.\nWhy we're hiring for this role\nSince launching the newest version of Elicit last fall, response has been strong. We introduced Elicit Plus, our monthly subscription plan, and added thousands of paying users in a matter of months as well as hundreds of thousands of new sign-ups. This has been energizing for our team, but we want to ship more useful functionality to our users even faster.\nWe believe that building great AI-powered products requires excellence across multiple parts of the tech stack: from frontend UX to infrastructure. But one of the crux areas is certainly how we prompt, invoke, respond to, and manage the suite of different ML models required to make Elicit work. This is what an AI engineer will be responsible for at Elicit.\nOur tech stack\nBackend: Node and Python.\n\nFrontend: Next.js and TypeScript (we expect you to be 80+% focussed on backend work, however).\n\nWe like static type checking in Python and TypeScript\n\nAll infrastructure runs in Kubernetes across a couple of clouds\n\nWe use GitHub for code reviews and CI\n\nAm I a good fit?\nConsider the questions:\nWhat's the difference between anyio, trio, and asyncio?\n\nWhat does the await keyword do in JavaScript?\n\nWhat is a Kubernetes pod, and how is it different from a container?\n\nHow would you manage state when using an LLM to power a conversation?\n\nIf you have a solid answer for these-without reference to documentation-then we should chat!\nWhat you'll own\nBackend implementation of our \"living document\"\nWe believe that user interactions with language models should be much deeper than yet more chatbot interfaces.\n\nWe wrote about our living document approach which is one way in which users can have much richer LLM-powered product experiences.\n\nYou would work on, curate, extend, and improve the backend part of that technology. This is fascinating and challenging distributed systems work.\n\nBuilding Elicit into a product researchers can’t live without\nWe ship useful, exciting features out to users on a weekly basis. Your focus will be on the code which exists between the BFF endpoints and the ML models we use.\n\nYou will work on a mix of known features / fixes, prototypes to validate ideas, and exploratory projects in between.\n\nOur team is small, so we expect you to appreciate the user needs underlying everything you work on. You should be comfortable making decisions and trade-offs that help us fulfill users’ needs best.\n\nKeeping Elicit’s bar for quality high\nYou’ll balance shipping features in the short term with building extensible and maintainable systems.\n\nYou will be responsible for your features in production: they need to be scalable, resilient, and easy to operate.\n\nYou’ll contribute to discussions around system design, performance evaluation, and architecture.\n\nProjects you'll contribute to\nYou can view sample projects here.\nWhat you bring to the role\nStrong technical aptitude that allows you to move comfortably around our back-end tech stack, with strong computer science fundamentals.\n\nA genuine curiosity and enthusiasm for the capabilities of language models.\n\nA defensive, fault-first mindset.\n\nAbove-average communication skills. Elicit is a small, highly-collaborative team, so you’ll frequently be tapped to communicate complex engineering topics with stakeholders across the company.\n\nA sense of joy in what you do. One thing we love about our team at Elicit is that everybody’s a craftsperson who cares deeply about their field.\n\nYour first week\nStart building foundational context\nGet to know your team, our stack, and the product roadmap.\n\nYou’ll get to know our company documentation and other supporting resources like Supporting Process, not Outcomes.\n\nMake your first contribution to Elicit\nBy the end of your first week, you’ll have completed your first Linear issue, have a PR merged into our monorepo, gained understanding of our CI/CD pipeline, and learned about our monitoring and logging tools.\n\nYour first month\nYou’ll complete your first multi-issue project\nAs you learn the ropes, you’re able to tackle more impactful projects, with input from domain experts where you need it.\n\nYou’re actively improving the team\nYou’ll have gotten into the swing of contributing to regular team meetings and hack days, and you’ve demoed something you’ve worked on during a team sync.\n\nYou’ve added some documentation, how-to guides, diagrams, or other resources meant to help us and new hires in the future.\n\nYou’ve suggested an improvement to our development process.\n\nYour first quarter\nYou’re flying solo\nWith the context you’ve gained, you’re able to implement changes independently and you’re comfortable making big, impactful decisions in the course of your work.\n\nYou’ve developed an area of expertise\nOur engineering team is just a few people, so each person quickly becomes a go-to resource in some area of the tech. Within your first quarter, we expect that there’s a part of Elicit you’ll become the domain expert for that others reach out to for support when working in this area.\n\nYou actively research and improve the product\nBy the end of your first quarter, you’ll have gotten to know Elicit and our users well. We expect that you’ll have thought about and scoped some user-facing improvements to the product as well as identified technical improvements to implement.\n\nLocation and travel\nWe have a great office in Oakland, CA, and we'd love to see you there if you're local. That said, we're just as happy for you to work remotely. We do get the whole team together for a quarterly retreat somewhere fun, because in-person time matters to us.\nBenefits and perks\nIn addition to working on important problems as part of a productive and positive team, we also offer great benefits (with some variation based on location):\nFlexible work environment: work from our office in Oakland or remotely with time zone overlap (between GMT and GMT-8), as long as you can travel for in-person retreats and coworking events\n\nFully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your family\n\nFlexible vacation policy, with a minimum recommendation of 20 days/year + company holidays\n\nEvery Elician receives a $200 monthly wellbeing stipend to spend on whatever supports your health and wellbeing.\n\n401K with a 6% employer match\n\nA new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter\n\n$1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools to incorporate into your workflow, take courses, purchase educational resources, or attend AI-focused conferences and events\n\nA team administrative assistant who can help you with personal and work tasks\n\nYou can find more reasons to work with us in this thread!\n\nCompensation\nFor all roles at Elicit, we use a data-backed compensation framework to keep salaries market-competitive, equitable, and simple to understand. For this role, we target starting ranges of:\nSenior (L4): $195-260k + equity\n\nExpert (L5): $250-300k + equity\n\nPrincipal (L6): >$270 + significant equity\n\nWe're optimizing for a hire who can contribute at a L4/senior-level or above.\nWe offer above-market equity for all roles at Elicit, as well as employee-friendly equity terms.","description_format":"text","description_chars":8852,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Flexible schedule","Flexible vacation policy","Home office","Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI for Science"],"lifecycle":[{"event":"open","at":"2024-06-11T05:21:26Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.199,"p_room":0.28,"age_days":858,"expected_fill_days":33,"reasons":["conf:2","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":260000,"is_top_pay":true},"html_url":"https://alion.io/job/elicit-ai-engineer","json_url":"https://alion.io/job/elicit-ai-engineer.json","meta":{"generated_at":"2026-10-17T20:31:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":4441,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":48045},"rest":"https://alion.io/mcp/rest/get_company?id=48045"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Felicit-ai-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Felicit-ai-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Felicit-ai-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/elicit-ai-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Felicit-ai-engineer"}]}