Staff Software Engineer (Applied AI)

Traba•San Francisco, CA

4d•$240,000 - $300,000

About The Position

Traba is building the AI operating system for the industrial supply chain. We started by tackling labor, supplying industrial businesses with consistent, reliable temporary workforces, and quickly became the fastest growing staffing company in America. Since then, we've expanded our suite of AI agents to help logistics providers, manufacturers, 3PLs, and other industrial businesses fully automate their manual workflows, derive insights from their data streams, and transform their decision intelligence. Our mission is to build a world where the global supply chain operates at peak efficiency. We’re proud to be backed by some of the world’s best investors, including Founders Fund, Khosla Ventures, and General Catalyst. You'll build Traba's product on top of AI agents—and set the standard for how we do it. You'll put frontier models and existing agents to work across our staffing marketplace to automate the pipeline that sources, vets, matches, and places workers on millions of shifts—and own the core backend services and platform it all runs on. (Our AI Agents team builds the agent platform; you make it real across the stack.) This is a platform-engineering role first, so you'll go where the priorities are: the infrastructure an agent needs one quarter, a matching, data, or scaling problem the next. You'll join the founding team, partner with our CTO on key architectural decisions, iterate on the roadmap, and build the foundational platform that scales over the next several years.

Requirements

7+ years with TypeScript/Node.js or Python, PostgreSQL, and messaging (Kafka or RabbitMQ).
A track record of shipping and leading projects at scale with high velocity.
Comfort owning ambiguity and direction in an early-stage environment.

Nice To Haves

Experience building or integrating AI/LLM systems in production is a plus—what matters most is the judgment to lead the team into it.

Responsibilities

Set the standard for how we apply agents across the stack to automate the staffing pipeline—and for how the team builds with AI-assisted tooling.
Architect and lead core systems—from real-time matching to autonomous vetting pipelines powered by ML and agents.
Own architecture for the platform, thinking ahead to what the company will need a year or two out.
Drive backend performance, reliability, and scale.