Applied AI
You will build Traba's product on top of AI agents and set the standard for how we do it. You will 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, then own the core backend services and platform it all runs on. The AI Agents team owns the agent platform itself; your job is to make it real across the product. This is a platform-engineering role, so priorities will shift: infrastructure one quarter, matching or scaling problems the next. You will join the founding team, partner with our CTO on key architectural decisions, and build the platform that the company runs on for the next several years.
About You
You wire frontier models and existing agents into production across the stack. You do not need to own the orchestration internals, but you know how to make them real, and you know which corners are safe to cut early on. You move easily from API design to deployment infrastructure, and you have designed performant, scalable systems with real expertise in APIs, data modelling, query optimisation, and distributed systems.
You Will
AI Agents (Neo AI)
You will build the AI agents themselves: the harnesses, evals, orchestration, and model strategy that the rest of Traba's product depends on. We are looking for a Staff Agent Engineer to join as a founding member of the Agents team and lead development of Traba's agentic platform – the layer that synthesises data flowing through our marketplace, integrates with customers' operational systems, and acts autonomously inside the workflows that run their facilities. The Applied AI team puts these agents to work across the product; you own the agents, evals, and model strategy they depend on. You will partner with our CTO on the core architectural decisions around how agents are built, evaluated, and deployed at Traba, and bring the technical depth and customer immersion this product needs at this stage.
About You
You have shipped agent systems into production at scale. You have designed the harness, chosen the orchestration patterns, owned the evals, and carried the on-call. You have strong opinions on where to draw the line between prompting, fine-tuning, retrieval, and code. You are as comfortable on a customer site as in a design doc, and you let what you see in the field shape architecture. You raise the bar by writing the canonical example: picking the foundational tools, integrating the right model providers, designing the eval infrastructure. You have strong opinions on eval datasets, prompt versioning, and observability for agents, and a good instinct for where a clean abstraction tips into over-engineering.
You Will
Neo Further Reading
Traba is the AI operating layer for the industrial supply chain. We started in workforce—temp staffing, the biggest operational pain point for the manufacturing and logistics customers we serve—and used it to embed ourselves inside their daily operations and create a far better customer experience through technology. Now those same customers are pulling us beyond staffing into the broader operational workflows that run their facilities. That foundation gave us proprietary data from millions of shifts and deep enterprise relationships. But our edge is more than data: by connecting to the systems running across every facility and activating the workers already on our platform to execute against them, we are building applied AI that drives real productivity gains and transforms how the global supply chain operates at scale.
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.
Additional positioning:
Salary
$200,000 - $300,000
Location
San Francisco, New York
Experience
8+ years
Total raised
$45.6M
Last stage
Series A
Investors
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.