AI Engineer - Enterprise

HILBERT IS BUILDING A REASONING ENGINE THAT MUST NAVIGATE NON-DETERMINISTIC USER BEHAVIOR ACROSS DATA SILOS — TURNING MONTHS-LONG DECISION CYCLES INTO MINUTES. FULLY AGENTIC BY DESIGN, OUR DEMAND INTELLIGENCE PLATFORM DOESN'T JUST CALL APIS; IT SOLVES THE HARD PROBLEM OF ORCHESTRATING MULTI-STEP INFERENCE OVER MESSY, HIGH-STAKES ENTERPRISE DATA WHERE DETERMINISTIC ANSWERS DON'T EXIST. From Fortune 500 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. We're looking for an AI Engineer who can build production-grade AI systems end-to-end and serve as the technical AI counterpart for our largest enterprise customers — understanding their workflows, translating their challenges into agentic solutions, and earning their trust through clarity, rigor, and results. All with the ownership and urgency of a startup culture. This is not a "wire up a prompt chain and move on" role. You'll own core pieces of the AI stack that power Hilbert's demand intelligence platform — designing agent architectures, building evaluation systems, and making hard tradeoffs between accuracy, latency, and cost in production. You'll also be the person our biggest customers look to when they want to understand what the AI is doing, why it made a particular decision, and how it can be shaped to solve their specific problems. If you think in systems, have opinions about how agentic workflows should actually work, can hold your own in a room full of enterprise stakeholders, and want to build AI products that drive real outcomes, we want to meet you. THE ROLE You'll work directly with the founding team and across product, data, and GTM to design, build, and improve the AI systems at the heart of Hilbert — with a particular focus on our largest enterprise accounts. You'll be hands-on every day — building agents, designing workflows, shipping to production — but you'll also be the technical AI voice in customer conversations: understanding their business context firsthand, shaping how we apply our agentic systems to their problems, presenting capabilities and results, and building the trust that turns a vendor relationship into a strategic partnership. The environment is high-autonomy and high-ambiguity — the nature of building AI-native products means requirements shift, approaches evolve, and the person closest to the problem often makes the call. In this role, you're often the person closest to both the technology and the customer. WHAT YOU'LL DO: Build - Design, build, and maintain AI-driven features and pipelines that serve enterprise customers at scale - Architect and implement agent-based workflows using LangChain, LangGraph, or equivalent orchestration frameworks - Own systems end-to-end — from experimentation through production deployment and monitoring - Build and improve evaluation pipelines to measure, validate, and iterate on AI system performance - Make pragmatic engineering decisions under ambiguity — ship, learn, iterate - Shape the technical direction of the AI stack as the company scales Partner with enterprise customers - Be the technical AI counterpart for our largest accounts — understanding their workflows, data environment, and business challenges firsthand, and translating them into agentic solutions - Present AI capabilities, results, and roadmap to senior customer stakeholders with clarity, conviction, and appropriate nuance — you're the person they trust to explain what the system does and why - Translate customer context into engineering decisions — what you learn in customer conversations directly informs how you design agents, workflows, and integrations. You don't build in a vacuum; you build with deep knowledge of how the output will be used - Hold the line on what AI can and can't do — when customers want a simpler story than reality supports, or push for capabilities that aren't ready, you find a way to be hones