{"id":947734,"url":"https://alion.io/job/everquote-ai-technical-lead-principal-engineer","title":"AI Technical Lead (Principal Engineer)","company":{"id":176179,"name":"EverQuote","domain":"everquote.com","url":"https://alion.io/company/everquote","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":202800,"max":238600,"currency":"USD","period":"year","gross":null,"usd_annual":238600},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"QLoRA","optional":false},{"name":"Rust","optional":false},{"name":"SFT","optional":false},{"name":"PEFT","optional":true}],"status":"live","first_seen_at":"2026-09-15T20:47:59Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-17T18:11:04Z","board_verified":true,"closed_at":null,"days_open":31,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":31},"description":"AI Technical Lead\nLocation: Cambridge, MA / Hybrid \n(This role requires working in-office 3 days per week: Tuesday, Wednesday, and Thursday.)\nAbout us:\nEverQuote is a leading AI-powered growth solutions partner for regulated property and casualty insurance entities, enabling the largest insurance carriers and thousands of agents to maximize customer acquisition across digital channels. Fueled by our proprietary data assets and our AI traffic engine, EverQuote is transforming the way providers attract and engage consumers to grow market share.\nJoining our team puts you at the forefront of this transformation. You will collaborate with a group of builders to solve complex problems and reshape a massive industry. If you want to drive real-world impact and do the best work of your career, you’ve found your home. We move fast, follow the data, and hold ourselves to high standards. If that's how you work too, this is the role for you.\nAbout the role:\nAs our Technical Lead, you will design and build a new kind of product: an insurance marketplace that AI agents use to shop on a person’s behalf. You will own the technical architecture end to end, from the models and how they run to the MCP server and tools that other AI platforms connect to. This is a hands-on senior role on a small team, and the decisions you make early will shape what agentic insurance shopping looks like before the market arrives.\nYou own the technical architecture for the agent: where the model’s reasoning runs, how we tune and serve it, how we keep cost and speed under control, and how the whole system stays reliable. We intend to run and tune our own open-weight models rather than depend only on hosted APIs, so we control cost, speed, and behavior as volume grows, and owning that is central to this role. You own the MCP server, the tools, and the data the agent works with, and you set the patterns the rest of the team builds on. You are the person who decides, with testing to back it up, how this is built, and then builds it.\nResponsibilities:\nOwn the architecture: decide where the agent’s reasoning runs, which models we use, how they are packaged, and how AI platforms connect to us, and back those calls with testing.\nBuild and tune the models: fine-tune open-weight models for our use, and decide when tuning, retrieval, or prompting is the right tool.\nStand up the serving and infrastructure: deploy the agent and MCP server so they are reliable, fast, and affordable to run, with versioning and a way to roll back.\nBuild the testing into the system: programmatic eval sets, guardrails, and monitoring for quality, drift, cost, and speed, so we catch problems before agents do.\nDesign the data model and tools with the AI product lead: the request and response payloads, the reasoning we expose, and the trust signals.\nSet the engineering patterns and standards the team builds on, and keep the code and architecture documented.\nKeep cost and speed honest: watch what inference costs, and make the trade-offs that keep it sustainable as volume grows.\nWork in the open. Help publish our code, architecture, and findings.\nMentor the engineers on the team and give leadership clear, regular visibility into technical progress and risks.\nWhat You Bring:\nDeep, current, hands-on experience in the AI and LLM space. You work on this every day, not from the sidelines.\nReal experience with open-weight models: you have fine-tuned them (LoRA, QLoRA, SFT, DPO, or similar) and run them yourself, not just called a hosted API.\nExperience owning an LLM system in production: you have served models reliably, pinned versions, rolled back a bad change, and explained why the bill moved.\nEnterprise-level design and architecture experience, with a track record of leading large, ambitious projects and delivering them.\nStrong grasp of evaluation and guardrails: building eval sets, catching failure modes, and monitoring quality, drift, cost, and speed.\nFluency with the serving and ops stack: model serving, containers and orchestration, and monitoring, on at least one major cloud.\nStrong communication. You can explain a technical trade-off to an engineer and to a non-technical leader, and lead with data.\nComfort with ambiguity and a bias for action in a space where the standards change month to month.\nQualifications:\n8+ years in engineering, with senior or lead ownership of complex technical systems, including hands-on work in machine learning or LLMs.\nA track record of leading large, ambitious projects with a small team and delivering them. We care more about what you have shipped and the judgment you showed than the revenue the project generated.\nHands-on fine-tuning and deployment of open-weight or open-source models, with real production experience.\nEnterprise design and architecture experience for complex, high-reliability systems.\nStrong Python, Rust, and fluency with the modern LLM stack (serving, retrieval, evaluation, monitoring).\nStrong strategic thinking paired with methodical execution. You can set the technical direction and then deliver it.\nExcellent communication across all levels of an organization, technical and non-technical.\nA history of teamwork and a bias for action.\nThe base salary offered for this position is determined by several factors, including the applicant's job-related skills, relevant experience, education or training, and work location. The base salary for this full-time hybrid role is $202,800-$238,600.\nIn addition to base salary, our total compensation package may include participation in variable cash bonus programs, equity, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility which are designated by role.\nYour recruiter can provide more details about additional compensation components, such as OTE structure, bonus targets, or equity, during the hiring process.\nThis role is not eligible for immigration sponsorship, now or in the future. Candidates must have current, unrestricted work authorization in the United States.\nEverQuote is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, genetic information, pregnancy or a pregnancy-related condition, veteran or military status, or any other protected characteristic. Reasonable accommodations are available for applicants with disabilities and for sincerely held religious beliefs or practices, upon request.\nFor more information, visit https://investors.everquote.com and follow on LinkedIn.","description_format":"text","description_chars":6590,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Insurance Brokers & Agencies","InsurTech"],"lifecycle":[{"event":"open","at":"2026-09-15T21:57:57Z"},{"event":"close","at":"2026-09-24T21:01:44Z"},{"event":"reopen","at":"2026-10-15T17:10:26Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 9 · green card filings: 4","filings_12m":9,"filings_prev_12m":15,"green_card_filings_12m":4,"median_offered_wage_usd":108654,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":5}],"liveness":{"score":68,"band":"ok","label":"Likely open","p_open":1,"p_active":0.761,"p_room":0.9,"age_days":31,"expected_fill_days":45,"reasons":["conf:0","win:mid"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":238600,"is_top_pay":true},"html_url":"https://alion.io/job/everquote-ai-technical-lead-principal-engineer","json_url":"https://alion.io/job/everquote-ai-technical-lead-principal-engineer.json","meta":{"generated_at":"2026-10-17T20:18:56Z","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":4039,"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":176179},"rest":"https://alion.io/mcp/rest/get_company?id=176179"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Feverquote-ai-technical-lead-principal-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%2Feverquote-ai-technical-lead-principal-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%2Feverquote-ai-technical-lead-principal-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/everquote-ai-technical-lead-principal-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Feverquote-ai-technical-lead-principal-engineer"}]}