Product Engineer, AI Enablement
Software Engineering, Product, Data Science · Full-time
Brooklyn, NY, USA · brooklyn, ia, usa
USD 150k-225k / year + Equity
About Ultra
Overview
Who You Are
- You have strong software engineering fundamentals and you ship quickly — backend services, internal tools, integrations, automation, and interfaces (Python and/or TypeScript)
- You've shipped agentic systems or LLM-powered tools that real people used, and you can explain where they fail
- You're fluent with modern AI coding tools and you have strong opinions about how they should be used
- You know when to build, when to buy, and when a conventional script beats an agent
- You treat evaluations, permissions, secrets, and safe rollout as part of the product — not a follow-up
- You like working with people who aren't engineers; you can turn an ambiguous workflow into something scoped and useful
- You write clearly and you're comfortable driving adoption, not just writing code
- 4+ years of production software is a reasonable bar; evidence you've shipped this kind of system matters more than the year count
What You’ll Do
- Own AI tooling adoption across Ultra: find where AI improves velocity, build or integrate the solution, teach people to use it, and drive adoption until it sticks
- Build the internal AI stack: services, workflows, interfaces, model integrations, and the agent infrastructure behind them
- Make agents competent and trustworthy in Ultra's codebase and systems — context, tool access, review, testing, CI — so the good path is the easy path
- Partner with operations, deployment, data, and business teams on workflows that give them leverage, then hand off maintainable systems with clear owners
- Build the reusable layer: connectors, shared context, templates, examples, and guardrails so other people can extend what you ship
- Evaluate the AI tooling ecosystem and decide what Ultra should adopt, compose, or build
- Partner with infrastructure and security so AI tools have useful access without becoming a liability
- Measure adoption, productivity, and whether the tool is actually trusted; expand what works and kill what doesn't
Bonus Points
- You're a former startup founder
- You’ve built self-improving, agentic systems in the past that eventually ran without you in the loop
- You have a strong product sense and know all about UX in HIL systems
- You've redesigned a business workflow and measured the gain, not just automated the existing mess
