{"schemaVersion":"jobsearcher.job.v1","id":"60f2d165aaf6d2b1736eebeb","url":"https://jobsearcher.com/jobs/60f2d165aaf6d2b1736eebeb","canonicalUrl":"https://jobsearcher.com/jobs/60f2d165aaf6d2b1736eebeb","title":"Data Product Engineer","description":"Data Product EngineerLocation - San Francisco, CA (On-site – 5 Days Per Week)\r\nCompensation - $230,000 – $280,000 Base + Competitive Equity\r\nVisa - US Citizens & Green Card Holders Only (No Visa Sponsorship)\r\nCompany Stage - Seed ($10M Raised)\r\nIndustry - Artificial Intelligence, Enterprise AI, Data Infrastructure, Agentic AI, Insurance Technology, LLM Platforms\r\nEffective AI is building the operating system for the insurance industry by transforming fragmented enterprise knowledge into trusted, AI-native workflows.\r\nThe platform combines large language models, structured data, retrieval systems, and multi-agent architectures to help insurance organizations reason over complex documents, regulations, filings, legal records, and operational knowledge with significantly greater speed and accuracy.\r\nBacked by Lightspeed and Valor with a $10M seed round, Effective AI is one of the fastest-growing applied AI startups tackling one of the world's largest industries—a $6 trillion insurance market. The company is building production AI systems focused on long-context reasoning, formal verification, retrieval, and multi-agent coordination while working directly with customers solving real operational problems.\r\nAs the company's first Data Product Engineer, you'll own the complete data layer powering the platform—from ingesting raw external data sources to building production-grade pipelines, evaluation systems, retrieval infrastructure, and customer-facing product experiences consumed by AI agents.\r\nThis is a rare opportunity to become the founding data engineering leader at an AI-native startup, combining product engineering, backend development, data infrastructure, and applied AI into one highly impactful role.\r\nWhat You'll DoBuild and own the company's end-to-end data platform from ingestion through production deployment\r\nWork directly with enterprise customers to identify high-value external data sources and new product opportunities\r\nDesign, build, and operate production data pipelines for structured and unstructured datasets\r\nIntegrate legal records, financial documents, insurance filings, PDFs, and other complex enterprise data into the platform\r\nDevelop scalable ingestion, extraction, transformation, and orchestration systems supporting AI agents\r\nBuild evaluation harnesses to monitor data quality, agent performance, and production reliability\r\nDesign search infrastructure enabling fast, accurate retrieval for LLM-powered applications\r\nBuild data products that expose clean, production-ready information directly to AI agents and customers\r\nOwn schema evolution, monitoring, pipeline reliability, and production maintenance\r\nCollaborate closely with product, engineering, and customers to translate ambiguous business problems into scalable technical solutions\r\nBuild AI-powered workflows using modern LLMs, retrieval systems, and agent frameworks\r\nEstablish engineering best practices across data architecture, testing, deployment, and reliability\r\nOperate with founder-level ownership in a fast-moving startup environment while helping define the company's long-term data strategy\r\nIdeal Candidate BackgroundExperience Requirements5–8 years of professional software or data engineering experience\r\nExperience building and operating production data systems end-to-end\r\nExperience owning data platforms from initial ingestion through production deployment\r\nExperience at high-growth startups or rapidly scaling technology companies\r\nExperience building systems through both early-stage development and production scale\r\nStrong product mindset with the ability to connect technical decisions to customer value\r\nExperience working with AI-native products or modern machine learning systems\r\nComfortable operating independently without established processes or playbooks\r\nDemonstrated ownership of production infrastructure, reliability, monitoring, and maintenance\r\nLeadership potential with interest in growing into ownership of an engineering function\r\nTechnical RequirementsExpert Python engineering experience\r\nStrong SQL and relational database expertise\r\nDeep experience building production data pipelines and orchestration systems\r\nExperience with large-scale unstructured document processing (PDFs, filings, legal records, financial documents)\r\nExperience building AI-powered workflows using LLMs, retrieval systems, or agent frameworks\r\nExperience with evaluation frameworks, testing infrastructure, or model quality systems\r\nExperience designing scalable data architectures supporting production applications\r\nStrong backend software engineering fundamentals\r\nExperience integrating external APIs and complex third-party data sources\r\nExperience building production search infrastructure or retrieval systems preferred\r\nFamiliarity with modern multi-agent architectures, RAG pipelines, or AI orchestration frameworks is highly desirable\r\nEducationBachelor's or higher degree in Computer Science, Engineering, Mathematics, Physics, Electrical Engineering, or another STEM discipline preferred\r\nStrong technical foundation with demonstrated engineering excellence\r\nCandidates from top technical universities are preferred, though exceptional industry experience is equally valued\r\nSoft SkillsExceptional product thinking\r\nStrong customer empathy\r\nExcellent systems thinking\r\nHigh ownership mentality\r\nStrong communication skills\r\nAbility to simplify complex technical concepts\r\nComfortable working through ambiguity\r\nStrong execution orientation\r\nCollaborative, low-ego mindset\r\nPassion for building foundational AI infrastructure\r\nCuriosity around emerging AI technologies and modern engineering workflows\r\nCompensation & BenefitsBase Salary: $230,000 – $280,000\r\nCompetitive Equity Package\r\nFounding Data Product Engineer opportunity\r\nHigh ownership with direct influence over product architecture\r\nWork alongside experienced AI researchers and engineering leaders\r\nOpportunity to build foundational infrastructure powering enterprise AI agents\r\nExposure to cutting-edge LLM systems, multi-agent architectures, and retrieval infrastructure\r\nWell-funded Seed-stage company backed by Lightspeed and Valor\r\nSignificant career growth with opportunity to build and lead the future data organization\r\nWork onsite with a highly collaborative engineering team in San Francisco\r\nWhy JoinThis is an opportunity to become the first Data Product Engineer at one of the most ambitious applied AI startups in enterprise software.\r\nYou'll build the foundational data platform powering intelligent AI agents that reason over some of the world's most complex enterprise information, while helping define how production AI systems consume, validate, and reason over trusted data.\r\nIf you enjoy building production data systems, owning products from zero to one, working directly with customers, and operating at the intersection of data engineering, backend systems, and applied AI, this role offers exceptional ownership, technical depth, and long-term impact.","company":"Recruiting from Scratch","rawCompany":"recruiting from scratch","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:18:55.718Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Product Engineer","description":"Data Product EngineerLocation - San Francisco, CA (On-site – 5 Days Per Week)\r\nCompensation - $230,000 – $280,000 Base + Competitive Equity\r\nVisa - US Citizens & Green Card Holders Only (No Visa Sponsorship)\r\nCompany Stage - Seed ($10M Raised)\r\nIndustry - Artificial Intelligence, Enterprise AI, Data Infrastructure, Agentic AI, Insurance Technology, LLM Platforms\r\nEffective AI is building the operating system for the insurance industry by transforming fragmented enterprise knowledge into trusted, AI-native workflows.\r\nThe platform combines large language models, structured data, retrieval systems, and multi-agent architectures to help insurance organizations reason over complex documents, regulations, filings, legal records, and operational knowledge with significantly greater speed and accuracy.\r\nBacked by Lightspeed and Valor with a $10M seed round, Effective AI is one of the fastest-growing applied AI startups tackling one of the world's largest industries—a $6 trillion insurance market. The company is building production AI systems focused on long-context reasoning, formal verification, retrieval, and multi-agent coordination while working directly with customers solving real operational problems.\r\nAs the company's first Data Product Engineer, you'll own the complete data layer powering the platform—from ingesting raw external data sources to building production-grade pipelines, evaluation systems, retrieval infrastructure, and customer-facing product experiences consumed by AI agents.\r\nThis is a rare opportunity to become the founding data engineering leader at an AI-native startup, combining product engineering, backend development, data infrastructure, and applied AI into one highly impactful role.\r\nWhat You'll DoBuild and own the company's end-to-end data platform from ingestion through production deployment\r\nWork directly with enterprise customers to identify high-value external data sources and new product opportunities\r\nDesign, build, and operate production data pipelines for structured and unstructured datasets\r\nIntegrate legal records, financial documents, insurance filings, PDFs, and other complex enterprise data into the platform\r\nDevelop scalable ingestion, extraction, transformation, and orchestration systems supporting AI agents\r\nBuild evaluation harnesses to monitor data quality, agent performance, and production reliability\r\nDesign search infrastructure enabling fast, accurate retrieval for LLM-powered applications\r\nBuild data products that expose clean, production-ready information directly to AI agents and customers\r\nOwn schema evolution, monitoring, pipeline reliability, and production maintenance\r\nCollaborate closely with product, engineering, and customers to translate ambiguous business problems into scalable technical solutions\r\nBuild AI-powered workflows using modern LLMs, retrieval systems, and agent frameworks\r\nEstablish engineering best practices across data architecture, testing, deployment, and reliability\r\nOperate with founder-level ownership in a fast-moving startup environment while helping define the company's long-term data strategy\r\nIdeal Candidate BackgroundExperience Requirements5–8 years of professional software or data engineering experience\r\nExperience building and operating production data systems end-to-end\r\nExperience owning data platforms from initial ingestion through production deployment\r\nExperience at high-growth startups or rapidly scaling technology companies\r\nExperience building systems through both early-stage development and production scale\r\nStrong product mindset with the ability to connect technical decisions to customer value\r\nExperience working with AI-native products or modern machine learning systems\r\nComfortable operating independently without established processes or playbooks\r\nDemonstrated ownership of production infrastructure, reliability, monitoring, and maintenance\r\nLeadership potential with interest in growing into ownership of an engineering function\r\nTechnical RequirementsExpert Python engineering experience\r\nStrong SQL and relational database expertise\r\nDeep experience building production data pipelines and orchestration systems\r\nExperience with large-scale unstructured document processing (PDFs, filings, legal records, financial documents)\r\nExperience building AI-powered workflows using LLMs, retrieval systems, or agent frameworks\r\nExperience with evaluation frameworks, testing infrastructure, or model quality systems\r\nExperience designing scalable data architectures supporting production applications\r\nStrong backend software engineering fundamentals\r\nExperience integrating external APIs and complex third-party data sources\r\nExperience building production search infrastructure or retrieval systems preferred\r\nFamiliarity with modern multi-agent architectures, RAG pipelines, or AI orchestration frameworks is highly desirable\r\nEducationBachelor's or higher degree in Computer Science, Engineering, Mathematics, Physics, Electrical Engineering, or another STEM discipline preferred\r\nStrong technical foundation with demonstrated engineering excellence\r\nCandidates from top technical universities are preferred, though exceptional industry experience is equally valued\r\nSoft SkillsExceptional product thinking\r\nStrong customer empathy\r\nExcellent systems thinking\r\nHigh ownership mentality\r\nStrong communication skills\r\nAbility to simplify complex technical concepts\r\nComfortable working through ambiguity\r\nStrong execution orientation\r\nCollaborative, low-ego mindset\r\nPassion for building foundational AI infrastructure\r\nCuriosity around emerging AI technologies and modern engineering workflows\r\nCompensation & BenefitsBase Salary: $230,000 – $280,000\r\nCompetitive Equity Package\r\nFounding Data Product Engineer opportunity\r\nHigh ownership with direct influence over product architecture\r\nWork alongside experienced AI researchers and engineering leaders\r\nOpportunity to build foundational infrastructure powering enterprise AI agents\r\nExposure to cutting-edge LLM systems, multi-agent architectures, and retrieval infrastructure\r\nWell-funded Seed-stage company backed by Lightspeed and Valor\r\nSignificant career growth with opportunity to build and lead the future data organization\r\nWork onsite with a highly collaborative engineering team in San Francisco\r\nWhy JoinThis is an opportunity to become the first Data Product Engineer at one of the most ambitious applied AI startups in enterprise software.\r\nYou'll build the foundational data platform powering intelligent AI agents that reason over some of the world's most complex enterprise information, while helping define how production AI systems consume, validate, and reason over trusted data.\r\nIf you enjoy building production data systems, owning products from zero to one, working directly with customers, and operating at the intersection of data engineering, backend systems, and applied AI, this role offers exceptional ownership, technical depth, and long-term impact.","datePosted":"2026-08-08T01:18:55.718Z","dateModified":"2026-08-08T01:18:55.718Z","hiringOrganization":{"@type":"Organization","name":"Recruiting from Scratch","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"60f2d165aaf6d2b1736eebeb"},"url":"https://jobsearcher.com/jobs/60f2d165aaf6d2b1736eebeb"}}