{"schemaVersion":"jobsearcher.job.v1","id":"c7dac9941a6c9ab851afffc5","url":"https://jobsearcher.com/jobs/c7dac9941a6c9ab851afffc5","canonicalUrl":"https://jobsearcher.com/jobs/c7dac9941a6c9ab851afffc5","title":"Forward Deployed Data Engineer (Integration)","description":"Hilbert is a scalable, data science-first growth engine that gives B2C teams predictive clarity into user behavior, revenue drivers, and the actions that drive sustainable growth. Fully agentic by design, Hilbert shrinks months-long decision cycles to minutes.\nFrom Fortune 10 enterprises to beloved brands like FreshDirect, Blank Street, and Levain Bakery, operators run their growth on Hilbert. We're also co-building alongside leading AI companies.\nWe’re looking for a Forward Deployed Data Engineer who can bridge the gap between our customers’ messy data ecosystems and Hilbert’s AI Growth Engine. This isn’t a \"ticket-taker\" role. You are the architect of the bridge. You will own the entire integration lifecycle from the first technical discovery call with a mid-market retailer to deploying custom stacks within a massive enterprise’s own infrastructure.\nYou’ll be the one listening to the customer, mapping their unique data schemas to our canonical models, and ensuring that when our AI/ML models \"wake up,\" they have a clean, high-fidelity view of the business.\nTHE ROLE\nThe \"Translator\" Ability: You can speak \"Engineer\" and \"Business\" equally well. You can extract the logic of a custom dimension table from a customer who doesn't have documentation.\nArchitecture Mindset: You understand the difference between a quick-and-dirty batch sync and a robust, incremental pipeline.\nTech Proficiency: Deep experience in Python and SQL. You’ve ideally worked with modern orchestration (Dagster, Airflow) and ingestion tools (Airbyte, Fivetran).\nAdaptability: You are comfortable working with MongoDB and Clickhouse, but you don't blink if a customer asks you to deploy on their specific cloud infra.\nAvailability: You are based in or aligned with US timezones and are ready to hop on a plane for an enterprise site visit when the stakes are high.\n\nWHO THRIVES IN THIS ROLE\nOwn the technical onboarding for new customers, transforming source data into Hilbert’s canonical models.\nDesign and implement incremental syncs for massive fact tables and full syncs for dimensions.\nNavigate enterprise-level complexity: custom data models, on-prem/private cloud deployments, and unique security requirements.\nCollaborate with the AI/ML team to ensure the data pipelines provide the exact context needed for agentic flows and insights.\nBuild the \"Last Mile\": Making sure the deployment of your customer is successful and the portal is setup and ready to be used by them.\nBonus Points\nExperience in E-commerce or Retail sectors (understanding what a \"SKU\" or \"Attribution Window\" is without being told).\nExperience with product event usage data.\nWorking with Data Scientists or ML Engineers\nExperience integrating B2B solutions for enterprise companies\nHaving Fullstack Software Development skills\nHaving experience with multiple different cloud infra providerse care about how you think and how you ship - not how many years are on your resume.\nThe profile:\nYou're a strong Python engineer. Your code is clean, testable, and production-ready.\nYou have real experience with LangChain, LangGraph, or equivalent agent/orchestration frameworks. You've built with them, hit their limits, and worked around them - not just followed tutorials\nYou communicate with clarity and conviction. You can explain a technical decision to a non-technical founder and debate architecture tradeoffs with a senior engineer . Communication is not a nice-to-have here - it's core to the role\nYou take ownership. You don't wait for tickets. You see what needs to be built, raise your hand, and ship it\nYou thrive in ambiguity. AI products evolve fast. Requirements change. You're energized by figuring it out.\nYou move at startup speed. You understand what it means to be available, responsive, and biased toward action in a fast-moving, early-stage environment\nStrong pluses:\nExperience building evals pipelines — designing metrics, running systematic evaluations, and using results to drive iteration on AI systems\nBackend software engineering experience — building APIs, services, data infrastructure, or production systems beyond the ML/AI layer\nExposure to retrieval-augmented generation (RAG), vector databases, or LLM-powered search and recommendation systems\nExperience at early-stage startups or high-growth environments where you wore multiple hats\nYou might be:\nA backend engineer who went deep on LLMs and never looked back. An ML engineer who realized they love building products, not just models. A startup CTO who wants to go deep on AI at a company where the stack is the product. Someone who's been hacking on agents and pipelines nights and weekends and wants to do it full-time with real enterprise stakes. What matters: you ship, you own it, and you communicate like a teammate — not a silo.\n\nLocation\nSan Francisco, with occasional travel for team meets, offsites or customer engagements.\n\nCompensation\nCompetitive salary + equity package, commensurate with experience.\nPerformance-based bonuses tied to project milestones and customer impact.\n\nThe Hiring Journey\nShort form Intro call Technical working session Team conversations Offer\nFast, human, no bureaucracy.","company":"Hilberts Ai","rawCompany":"hilberts ai","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-04-14T11:17:15.874Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Forward Deployed Data Engineer (Integration)","description":"Hilbert is a scalable, data science-first growth engine that gives B2C teams predictive clarity into user behavior, revenue drivers, and the actions that drive sustainable growth. Fully agentic by design, Hilbert shrinks months-long decision cycles to minutes.\nFrom Fortune 10 enterprises to beloved brands like FreshDirect, Blank Street, and Levain Bakery, operators run their growth on Hilbert. We're also co-building alongside leading AI companies.\nWe’re looking for a Forward Deployed Data Engineer who can bridge the gap between our customers’ messy data ecosystems and Hilbert’s AI Growth Engine. This isn’t a \"ticket-taker\" role. You are the architect of the bridge. You will own the entire integration lifecycle from the first technical discovery call with a mid-market retailer to deploying custom stacks within a massive enterprise’s own infrastructure.\nYou’ll be the one listening to the customer, mapping their unique data schemas to our canonical models, and ensuring that when our AI/ML models \"wake up,\" they have a clean, high-fidelity view of the business.\nTHE ROLE\nThe \"Translator\" Ability: You can speak \"Engineer\" and \"Business\" equally well. You can extract the logic of a custom dimension table from a customer who doesn't have documentation.\nArchitecture Mindset: You understand the difference between a quick-and-dirty batch sync and a robust, incremental pipeline.\nTech Proficiency: Deep experience in Python and SQL. You’ve ideally worked with modern orchestration (Dagster, Airflow) and ingestion tools (Airbyte, Fivetran).\nAdaptability: You are comfortable working with MongoDB and Clickhouse, but you don't blink if a customer asks you to deploy on their specific cloud infra.\nAvailability: You are based in or aligned with US timezones and are ready to hop on a plane for an enterprise site visit when the stakes are high.\n\nWHO THRIVES IN THIS ROLE\nOwn the technical onboarding for new customers, transforming source data into Hilbert’s canonical models.\nDesign and implement incremental syncs for massive fact tables and full syncs for dimensions.\nNavigate enterprise-level complexity: custom data models, on-prem/private cloud deployments, and unique security requirements.\nCollaborate with the AI/ML team to ensure the data pipelines provide the exact context needed for agentic flows and insights.\nBuild the \"Last Mile\": Making sure the deployment of your customer is successful and the portal is setup and ready to be used by them.\nBonus Points\nExperience in E-commerce or Retail sectors (understanding what a \"SKU\" or \"Attribution Window\" is without being told).\nExperience with product event usage data.\nWorking with Data Scientists or ML Engineers\nExperience integrating B2B solutions for enterprise companies\nHaving Fullstack Software Development skills\nHaving experience with multiple different cloud infra providerse care about how you think and how you ship - not how many years are on your resume.\nThe profile:\nYou're a strong Python engineer. Your code is clean, testable, and production-ready.\nYou have real experience with LangChain, LangGraph, or equivalent agent/orchestration frameworks. You've built with them, hit their limits, and worked around them - not just followed tutorials\nYou communicate with clarity and conviction. You can explain a technical decision to a non-technical founder and debate architecture tradeoffs with a senior engineer . Communication is not a nice-to-have here - it's core to the role\nYou take ownership. You don't wait for tickets. You see what needs to be built, raise your hand, and ship it\nYou thrive in ambiguity. AI products evolve fast. Requirements change. You're energized by figuring it out.\nYou move at startup speed. You understand what it means to be available, responsive, and biased toward action in a fast-moving, early-stage environment\nStrong pluses:\nExperience building evals pipelines — designing metrics, running systematic evaluations, and using results to drive iteration on AI systems\nBackend software engineering experience — building APIs, services, data infrastructure, or production systems beyond the ML/AI layer\nExposure to retrieval-augmented generation (RAG), vector databases, or LLM-powered search and recommendation systems\nExperience at early-stage startups or high-growth environments where you wore multiple hats\nYou might be:\nA backend engineer who went deep on LLMs and never looked back. An ML engineer who realized they love building products, not just models. A startup CTO who wants to go deep on AI at a company where the stack is the product. Someone who's been hacking on agents and pipelines nights and weekends and wants to do it full-time with real enterprise stakes. What matters: you ship, you own it, and you communicate like a teammate — not a silo.\n\nLocation\nSan Francisco, with occasional travel for team meets, offsites or customer engagements.\n\nCompensation\nCompetitive salary + equity package, commensurate with experience.\nPerformance-based bonuses tied to project milestones and customer impact.\n\nThe Hiring Journey\nShort form Intro call Technical working session Team conversations Offer\nFast, human, no bureaucracy.","datePosted":"2026-04-14T11:17:15.874Z","dateModified":"2026-04-14T11:17:15.874Z","hiringOrganization":{"@type":"Organization","name":"Hilberts Ai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c7dac9941a6c9ab851afffc5"},"url":"https://jobsearcher.com/jobs/c7dac9941a6c9ab851afffc5"}}