---
title: 'Product Engineer, AI Enablement at Ultra'
canonical: 'https://feeny.ai/job/product-engineer-ai-enablement-ultra-brooklyn-t0em53cpeqab'
type: 'job'
last_seen: '2026-11-09'
---

# Product Engineer, AI Enablement at Ultra

- **Company:** Ultra
- **Location:** Brooklyn, NY
- **Compensation:** $150k–$225k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-26
- **Last confirmed live:** 2026-11-09
- **Apply:** https://jobs.gem.com/ultra/am9icG9zdDq9lo-OiGVMn9E6WLSeTy_g

## Job description

## Overview

Ultra is looking for a Product Engineer, AI Enablement to build and roll out the tools that help Ultra use AI effectively across the company. You'll work with engineering, operations, deployment, data, people, and other teams to understand how people work, find where AI creates real leverage, and turn that into reliable internal tools and workflows.

You'll sit on the Software team next to infrastructure and developer productivity. Your users are your colleagues. Half the leverage is how we write and ship software — coding agents, review, testing, repo context, CI. Half is how the rest of the company gets work done — agents and automations people trust. Across both, you'll make the good path easy to reuse, so teams can build their own workflows without waiting on you for every request.

This is a production software role. You will evaluate commercial tools, compose what works, build what doesn't exist, measure adoption, and kill what doesn't earn its keep. This is an in-person NYC role with direct line of sight to how Ultra builds and operates.

## 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

## About Ultra

## Company Overview
- **One-liner**: Ultra builds practical, general-purpose industrial AI robots that automate repetitive warehouse tasks like packing, sorting, and kitting, with zero integration and rapid deployment.
- **Entity Type**: Private (Seed stage; $625K total funding)
- **Headquarters**: New York, NY, United States
- **Founded**: 2024
- **Founders**: Jon Miller Schwartz (CEO), Max Friefeld (COO), Chetan Parthiban (Co-Founder & Chief Scientist), Oliver Ortlieb (Co-Founder & CTO)

## Core Business
- **Primary industry**: Robotics Engineering / Industrial Automation
- **Target customers**: B2B – warehouses, fulfillment centers, and logistics operators (enterprise and SMB)
- **Mission or purpose**: To deploy practical, general-purpose robots that generate immediate ROI by handling repetitive, high‑volume work, and to scale intelligence through real‑world data.

## Products & Services
- **[Operator](https://www.ultra.tech/)**: A stationary industrial AI robot designed for e‑commerce order packaging, sorting, and kitting. It operates up to 24 hours a day, requires no fixed infrastructure, installs in hours, and covers a 5×5 ft footprint with a 10 ft vertical reach. The robot learns new tasks from example data and improves fleet‑wide as more units are deployed.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding of $625K (Seed: $125K in Aug 2024; Pre‑Seed: $500K in Sep 2024 led by Y Combinator)
- **Notable Investors/Partners**: Y Combinator (lead investor), three additional investors in Pre‑Seed round
- **Growth Signals**: 14 total employees (as of early 2025), 19 employees (latest) – **333% YoY headcount growth**; robots already deployed in real warehouses generating revenue and data; launched the Operator robot in April 2026 with 184 LinkedIn reactions; actively hiring across engineering, research, deployment, and people operations.

## Competitive Advantages
- **Zero‑integration deployment**: Robots can be rolled in, plugged in, and turned on within hours – no expensive infrastructure or lengthy integration.
- **Stationary, safe design**: No tipping risk, no battery swaps, no charging breaks – designed for continuous operation in real warehouse conditions.
- **AI trained with examples**: Uses neural nets trained on teleoperation data (≈2 hours) to learn new tasks, enabling rapid adaptation to variable items and changing workflows.
- **Fleet learning**: Every deployed robot feeds data back to improve the entire fleet – a data‑scale moat that compounds with more deployments.

## Strategic Focus
- Rapidly scale deployments across the US in 2025‑2026, building on proven field traction.
- Continue improving robot foundation models for faster, more robust task learning and execution.
- Expand from e‑commerce packaging into adjacent warehouse workflows (e.g., kitting, returns).
- Grow the team (targeting engineering, research, deployment, and people functions) to support production scaling.

## Why Work Here
- **Early‑stage impact**: Join a YC‑backed startup founded by three‑time entrepreneurs (previously founded Layer By Layer, Voodoo Manufacturing) with a decade of collaboration.
- **Fast‑paced, hands‑on culture**: Engineers and researchers directly own firmware, hardware, ML models, and deployment – from design to field support.
- **Real‑world robotics**: Work on robots that are already generating revenue in customer warehouses, not just lab prototypes.
- **Growth trajectory**: 333% headcount growth in the past year, with ambitious plans to scale from 19 to hundreds of employees.
- **Location & flexibility**: Based in New York City; roles span HQ (assembly, testing, R&D) and field deployment across the US.
- **Open roles** (as of early 2026): Robotics Firmware Engineer, Robotics Hardware Engineer, Data Operations Lead, Research Scientist, Product Engineer, Deployment Engineer, Head of People – offering broad ownership and career growth.

## Sources
1. [ultra.tech](https://www.ultra.tech/)
2. [Y Combinator – Ultra](https://www.ycombinator.com/companies/ultra)
3. [Built In – Ultra Company Profile](https://builtin.com/company/ultra-ultra-tech)
4. [Built In – Ultra Jobs](https://builtin.com/company/ultra-ultra-tech/jobs)
5. [LinkedIn – Ultra](https://www.linkedin.com/company/ultraroboticsco)

## Other roles at Ultra

- [Facilities & Office Manager](https://feeny.ai/job/facilities-office-manager-ultra-brooklyn-xpnsajcqy9v2) — Brooklyn, NY
- [Head of Hardware](https://feeny.ai/job/head-of-hardware-ultra-brooklyn-dtc2anggdp5p) — Brooklyn, NY
- [Senior Software Infrastructure Engineer](https://feeny.ai/job/senior-software-infrastructure-engineer-ultra-brooklyn-cag4a9js5h01) — Brooklyn, NY
- [Head of Marketing](https://feeny.ai/job/head-of-marketing-ultra-brooklyn-rarz21rtmbav) — Brooklyn, NY
- [Head of People](https://feeny.ai/job/head-of-people-ultra-brooklyn-g8frrbpfpq6d) — Brooklyn, NY
- [Founding Product](https://feeny.ai/job/founding-product-ultra-brooklyn-4tb57rm0cymn) — Brooklyn, NY
- [Supply Chain and Procurement Lead](https://feeny.ai/job/supply-chain-and-procurement-lead-ultra-brooklyn-p1brfk2ye8wc) — Brooklyn, NY
- [Research Scientist](https://feeny.ai/job/research-scientist-ultra-brooklyn-6ke5efe8x5qp) — Brooklyn, NY
- [Head of Pilot Operations](https://feeny.ai/job/head-of-pilot-operations-ultra-brooklyn-4w0cmp599g0n) — Brooklyn, NY
- [Robot Manufacturing Technician](https://feeny.ai/job/robot-manufacturing-technician-ultra-brooklyn-5y3tsgt9w29a) — Brooklyn, NY