Lead AI Engineer

About Hilbert AI

Hilbert is building the demand intelligence platform used by world-class B2C companies — including the world's largest retailer — to unlock compounding growth outcomes. The product sits at the intersection of AI, data, and commercial activation for retail and e-commerce. The AI stack is not just a feature — it is the product.

The platform is fully agentic by design, orchestrating multi-step inference over messy, high-stakes enterprise data to turn months-long decision cycles into minutes. The team is small, talent-dense, and low-ego. Engineering leadership here has direct, measurable impact on enterprise customers and revenue.

The Opportunity

Hilbert is looking for a Lead AI Engineer to own the technical direction of the AI stack, ship production-grade systems hands-on, and elevate a growing engineering team. This is not a manage-from-a-distance role. You will write code every day, make architecture calls, set the bar for quality and velocity, and help build the engineering culture as the company scales.

You are the person the team looks to when the problem is ambiguous, the stakes are high, and the path forward hasn't been written yet. If you combine deep technical craft with the ability to lead people and communicate with conviction, this role is built for you.

What You'll Do

• •      Design, build, and maintain AI-driven features and pipelines serving enterprise customers at scale
• •      Architect and implement agent-based workflows using LangChain, LangGraph, or equivalent orchestration frameworks
• •      Own critical 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
• •      Define and own the technical roadmap for the AI stack in partnership with the founding team
• •      Make architecture and infrastructure decisions that balance speed today with scalability tomorrow
• •      Set engineering standards across code quality, review practices, testing, documentation, and deployment
• •      Prioritize across competing demands and keep the team focused on highest-impact work
• •      Communicate technical strategy, tradeoffs, and progress clearly to founders and non-technical stakeholders
• •      Hire, mentor, and develop AI engineers as the team scales
• •      Create an environment of ownership, intellectual honesty, and high-velocity shipping

You Should Have

• •      Strong Python engineering fundamentals — clean, testable, production-ready code; you lead from inside the codebase
• •      Deep hands-on experience with LangChain, LangGraph, or equivalent agent and orchestration frameworks, including experience hitting their limits and designing around them
• •      A track record of owning AI systems end-to-end in production, not just prototyping
• •      Prior experience as a tech lead, engineering manager, or founding engineer — you have led teams and raised the bar around you
• •      Strong communication skills — you can align a team on a technical direction, explain a tradeoff to a non-technical founder, and give direct feedback to an engineer, all in the same day
• •      Comfort operating in high-autonomy, high-ambiguity environments and helping others do the same

Nice to Have

• •      Experience building evaluation pipelines — defining metrics, running systematic evals, and using results to drive iteration
• •      Backend engineering experience building APIs, services, or data infrastructure beyond the ML layer
• •      Exposure to retrieval-augmented generation, vector databases, or LLM-powered search and recommendation systems
• •      Track record of hiring and developing engineers, not just managing them

Compensation

Competitive salary and equity reflecting the seniority and scope of the role. Details shared during the hiring process.

The hiring process is short form, intro call, technical working session, team conversations, and offer. Fast, human, no bureaucracy.