{"schemaVersion":"jobsearcher.job.v1","id":"3b68ae18e673e7de5c3fb5cc","url":"https://jobsearcher.com/jobs/3b68ae18e673e7de5c3fb5cc","canonicalUrl":"https://jobsearcher.com/jobs/3b68ae18e673e7de5c3fb5cc","title":"Founding Engineer - Tech Lead","description":"About Us\n\nDouble Blind Bio automates administrative work so clinical staff can focus on patient care and advancing science. We're building a future where clinical trials run more autonomously by connecting sites, sponsors, and their data with AI, accelerating the path from drug development to market. We've raised over $7 million from co-lead investors SignalFire and Define Ventures. We're used by 400+ clinical research sites and and growing.\n\nThe Vision\n\nWe exist to accelerate scientific development and improve human well-being by making medicines more effective, worldwide. Bringing a drug to market today takes over 10 years and $1-2 billion, most of it spent on clinical trials, not drug discovery. Now imagine cutting that time and cost in half. Per the Jevons paradox, as costs drop, demand rises: more candidate therapies and niche treatments could reach the market. Clinical trial operations sit at the center of that shift, and that's the problem we're solving.\n\nAbout the Role\n\nDouble Blind Bio is looking for a Staff-level product engineer to serve as Tech Lead. You'll stay hands-on, writing and reviewing code daily and owning AI-powered features end-to-end, while acting as technical anchor for a small, growing team: setting day-to-day direction, unblocking teammates, and giving feedback that helps people grow. This is technical and organizational leadership, not people management.\n\nYou bring genuine depth in AI systems: not just building with LLMs, but measuring, evaluating, and improving them in production. You know when AI is working, when it isn't, and how to tell the difference, backed by evals wired into real systems rather than notebook experiments. You're a strong partner to product, GTM, and founders, helping shape solutions and pushing back on scope and sequencing rather than just taking specs. This role suits engineers who thrive at the intersection of AI, healthcare, and product, and who want high ownership, rapid iteration, and close collaboration with users.\n\nResponsibilities\n\nDesign, build, and deploy agentic AI systems that power web experiences and automate clinical workflows\n\nOwn the full eval lifecycle in production: define what \"good\" looks like, build evaluation datasets, author metrics, and wire evals into CI, monitoring, or release gating\n\nInstrument AI systems for observability: trace LLM calls, monitor output quality, detect regressions, and build tooling for visibility into production behavior\n\nArchitect and optimize full-stack applications: frontend, backend, infrastructure, and data pipelines\n\nPartner closely with product, founders, and customers: shape solutions and push back on scope and sequencing rather than just executing specs\n\nHelp establish best-in-class engineering processes, architecture, and best practices\n\nParticipate in customer conversations to understand workflows and improve the product\n\nQualifications\n\nStaff+ level product engineer with deep, current hands-on ability. You still write and review code daily\n\nHas built LLM-powered product features and has production evals experience: designed eval sets, defined metrics, and wired them into CI, monitoring, or release gating, not just offline experiments\n\nFull-stack ownership: can carry a feature end-to-end, not just one layer\n\nHas led a team's day-to-day before, as tech lead, project lead, or de facto anchor, keeping a team on the right work and giving feedback that helped people grow\n\nStrong PM and GTM collaborator: partners on shaping solutions and pushes back on scope and sequencing, not just taking specs\n\nStrong observability instincts: instrument pipelines, trace model calls, and build feedback loops that surface problems before users do\n\nComfort working across disciplines and learning new domains (healthcare, life sciences, data systems)\n\nAbility to work in a fast-paced, evolving environment with high ownership and autonomy\n\nStrong communication skills and willingness to collaborate across teams and with customers\n\nPreferred\n\nSmall startup experience (seed/Series A, small teams, high ambiguity)\n\nHas been the senior person on a junior team and raised its bar\n\nGenuine interest in bio/life sciences\n\nExperience with ML evaluation frameworks or LLM observability tooling (e.g., LangSmith, Braintrust, Weights & Biases, Honeyhive, or similar)\n\nFamiliarity with statistical thinking around model evaluation: confidence intervals, human-in-the-loop review, A/B testing\n\nExperience building agentic workflows or multi-step AI pipelines","company":"Double Blind Bio","rawCompany":"double blind bio","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-01T09:31:48.305Z","occupations":[{"code":"11-9041.00","title":"Architectural and Engineering Managers","slug":"architectural-and-engineering-managers"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541714","title":"Research and Development in Biotechnology (except Nanobiotechnology)","slug":"research-and-development-in-biotechnology-except-nanobiotechnology"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Founding Engineer - Tech Lead","description":"About Us\n\nDouble Blind Bio automates administrative work so clinical staff can focus on patient care and advancing science. We're building a future where clinical trials run more autonomously by connecting sites, sponsors, and their data with AI, accelerating the path from drug development to market. We've raised over $7 million from co-lead investors SignalFire and Define Ventures. We're used by 400+ clinical research sites and and growing.\n\nThe Vision\n\nWe exist to accelerate scientific development and improve human well-being by making medicines more effective, worldwide. Bringing a drug to market today takes over 10 years and $1-2 billion, most of it spent on clinical trials, not drug discovery. Now imagine cutting that time and cost in half. Per the Jevons paradox, as costs drop, demand rises: more candidate therapies and niche treatments could reach the market. Clinical trial operations sit at the center of that shift, and that's the problem we're solving.\n\nAbout the Role\n\nDouble Blind Bio is looking for a Staff-level product engineer to serve as Tech Lead. You'll stay hands-on, writing and reviewing code daily and owning AI-powered features end-to-end, while acting as technical anchor for a small, growing team: setting day-to-day direction, unblocking teammates, and giving feedback that helps people grow. This is technical and organizational leadership, not people management.\n\nYou bring genuine depth in AI systems: not just building with LLMs, but measuring, evaluating, and improving them in production. You know when AI is working, when it isn't, and how to tell the difference, backed by evals wired into real systems rather than notebook experiments. You're a strong partner to product, GTM, and founders, helping shape solutions and pushing back on scope and sequencing rather than just taking specs. This role suits engineers who thrive at the intersection of AI, healthcare, and product, and who want high ownership, rapid iteration, and close collaboration with users.\n\nResponsibilities\n\nDesign, build, and deploy agentic AI systems that power web experiences and automate clinical workflows\n\nOwn the full eval lifecycle in production: define what \"good\" looks like, build evaluation datasets, author metrics, and wire evals into CI, monitoring, or release gating\n\nInstrument AI systems for observability: trace LLM calls, monitor output quality, detect regressions, and build tooling for visibility into production behavior\n\nArchitect and optimize full-stack applications: frontend, backend, infrastructure, and data pipelines\n\nPartner closely with product, founders, and customers: shape solutions and push back on scope and sequencing rather than just executing specs\n\nHelp establish best-in-class engineering processes, architecture, and best practices\n\nParticipate in customer conversations to understand workflows and improve the product\n\nQualifications\n\nStaff+ level product engineer with deep, current hands-on ability. You still write and review code daily\n\nHas built LLM-powered product features and has production evals experience: designed eval sets, defined metrics, and wired them into CI, monitoring, or release gating, not just offline experiments\n\nFull-stack ownership: can carry a feature end-to-end, not just one layer\n\nHas led a team's day-to-day before, as tech lead, project lead, or de facto anchor, keeping a team on the right work and giving feedback that helped people grow\n\nStrong PM and GTM collaborator: partners on shaping solutions and pushes back on scope and sequencing, not just taking specs\n\nStrong observability instincts: instrument pipelines, trace model calls, and build feedback loops that surface problems before users do\n\nComfort working across disciplines and learning new domains (healthcare, life sciences, data systems)\n\nAbility to work in a fast-paced, evolving environment with high ownership and autonomy\n\nStrong communication skills and willingness to collaborate across teams and with customers\n\nPreferred\n\nSmall startup experience (seed/Series A, small teams, high ambiguity)\n\nHas been the senior person on a junior team and raised its bar\n\nGenuine interest in bio/life sciences\n\nExperience with ML evaluation frameworks or LLM observability tooling (e.g., LangSmith, Braintrust, Weights & Biases, Honeyhive, or similar)\n\nFamiliarity with statistical thinking around model evaluation: confidence intervals, human-in-the-loop review, A/B testing\n\nExperience building agentic workflows or multi-step AI pipelines","datePosted":"2026-09-01T09:31:48.305Z","dateModified":"2026-09-01T09:31:48.305Z","hiringOrganization":{"@type":"Organization","name":"Double Blind Bio","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3b68ae18e673e7de5c3fb5cc"},"url":"https://jobsearcher.com/jobs/3b68ae18e673e7de5c3fb5cc"}}