The role
- COMP
- $140K - $200K
- EQUITY
- Competitive
- LOCATION
- New York
- WORKPLACE
- On-site
- EXPERIENCE
- 3 - 4 years
- VISA
- None, Visa transfers
- STACK
- TypeScript, JavaScript, React, Python, NodeJS, PostgreSQL
- INDUSTRY
- AI, Logistics, Marketplace, Manufacturing
/roles — ROLE_303
Product Engineer (Mid-Senior)
Venture-backed staffing and supply chain AI company building agents for warehouses, factories and logistics teams
The company
AI-driven operations platform for warehouses and industrial logistics, supplying both the workforce that runs facilities and the software that makes them more efficient.
- STAGE
- growth-stage
- FUNDING
- $40M+ raised
- TEAM
- ~80 people
- FOUNDED
- 2021
- BACKING
- backed by Founders Fund, Khosla Ventures, General Catalyst
JD — the work
About the role
A mid-to-senior engineering role with two possible tracks, both working closely with the CTO. On the applied AI track you build features using LLMs and existing agents across the staffing marketplace, tackling whatever matters most, with or without AI, from agent automation for vetting and matching to payments and platform projects. On the agents track you join the founding agents team as a senior engineer, building the harnesses, evals and infrastructure that let agents operate autonomously inside customers' supply chains.
What you'll do
- Applied AI track: bring LLMs and ready-made agents into the worker and business apps, the ops tooling and the marketplace
- Applied AI track: lead UI and backend work, own whole product surfaces with design and product, and mentor peers
- Applied AI track: design core services, including APIs, live matching, distributed backends and automated vetting
- Agents track: spend time with operators in the field to learn their workflows, then build agents that remove real work
- Agents track: ship production agents using retrieval, MCP servers, sub-agents, tool calling and structured outputs
- Agents track: treat evals as core engineering, with rubrics, graders and datasets drawn from real traces, and prove each improvement
- Agents track: build the services and APIs that tie agents into customer ERP, TMS and WMS systems, and standardize rollouts
What they're looking for
- 3 to 4 years building fast, scalable software across both frontend and backend
- Range across the stack: interface design, APIs and deployment infrastructure
- Applied AI track: experience turning LLMs and existing agents into reliable product automation
- Agents track: LLM products shipped beyond chat wrappers, including harness design, tool schemas, evals and trace-driven prompt work
- Agents track: you weigh unit economics and reliability as heavily as raw model capability
- Comfort turning an unclear customer problem into a shipped solution without a spec, and enjoying time with frontline operators