/roles — ROLE_302
Product Engineer (Senior/Staff)
Growth-stage industrial staffing and AI company automating how workers are sourced, vetted and matched to shifts
The role
- COMP
- $200K - $300K
- EQUITY
- Competitive
- LOCATION
- San Francisco · New York
- WORKPLACE
- On-site
- EXPERIENCE
- 5 - 10 years
- VISA
- None, Visa transfers
- STACK
- TypeScript, JavaScript, React, Python, NodeJS, PostgreSQL, Kafka, RabbitMQ
- INDUSTRY
- AI, Logistics, Marketplace, Manufacturing
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 senior or staff engineering role with two tracks, both partnering with the CTO on core architecture. On the applied AI track you apply current LLMs and existing agents across a large staffing marketplace and own the backend platform underneath, with priorities moving between infrastructure, matching and scale. On the agents track you join a new team as a founding staff engineer and design the underlying agent platform: model strategy, orchestration, evals and harnesses.
What you'll do
- Applied AI track: decide where agents go in the product to automate sourcing, vetting, matching and placement of workers
- Applied AI track: architect key systems such as live worker matching and automated vetting built on ML and agents
- Applied AI track: plan the platform a year or two ahead and keep the backend fast, stable and scalable
- Agents track: design the full agent platform: runtime, observability, evals, and links into customer WMS, TMS and ERP systems
- Agents track: make the core calls on retrieval, memory, harness design, tool and MCP exposure, and model choice
- Agents track: run evals like any other engineering system, with regression suites, graders, curated datasets and experiment tools
- Agents track: visit customer sites, hire and mentor engineers, and help set the long-range platform plan
What they're looking for
- 5 to 10 years of experience building fast, scalable backend systems
- Real depth in distributed systems, API design, data modeling and query tuning
- Applied AI track: you have put LLMs and agents into real products and know where early shortcuts are acceptable
- Agents track: a history of running agent systems in production at real scale, owning harnesses, orchestration, evals and on-call
- Agents track: firm views on prompt versioning, eval data, agent observability, and when to prompt, retrieve, fine-tune or code
- Comfort on customer sites as well as in design docs, letting field observations shape architecture