Product Engineer (Junior/Mid)
About this role
Applied AI
You will build Traba's product on top of AI agents, taking frontier models and existing agents and putting them to work across our staffing marketplace to automate the pipeline that sources, vets, matches, and places workers on millions of shifts. The AI Agents team builds the agent platform; your job is to apply it where it creates leverage. This is a product-engineering role, so priorities will shift – some quarters that is an agent that automates vetting or matching, others it is a payments flow or platform work. You will partner with our CTO on architecture and roadmap, and build the platform the rest of the company runs on.
About You
You take frontier models and existing agents and wire them into real product across the stack, shipping reliable automation rather than owning the orchestration internals. You do not need every task to be an AI task: you take the highest-priority problem, model or not. You move easily between API design, UX, and deployment infrastructure, and you have a track record of shipping scalable, performant applications from frontend interfaces to backend distributed systems.
You Will
Apply existing agents and frontier models across the stack – worker app, business app, ops platform, marketplace – to automate vetting, matching, and fulfilment.
Lead frontend and backend development, mentoring other engineers.
Architect and build core systems: real-time matching, autonomous vetting pipelines, distributed systems, and APIs.
Own product surfaces end to end, partnering closely with product and design.
AI Agent (Neo AI)
You will build the AI agents themselves: the harnesses, evals, orchestration, and model strategy that the rest of Traba's product runs on. We are looking for a Senior AI Agent Engineer to join as a founding member of the Agents team and build the next layer of Traba's product – an agentic platform that synthesises the data flowing through our marketplace and operates autonomously inside our customers' supply chain workflows. The Applied AI team puts these agents to work across the product; you own the agents and infrastructure they depend on. You will embed deeply in our customers' operations, design and ship production agent harnesses on top of frontier models, and turn what you learn in the field into durable product. You will partner closely with our CTO, product, and our operators to take early-stage ideas to scaled deployments.
About You
You have shipped real product on top of LLMs – not just chat wrappers. You have designed agent harnesses, structured tools, written evals, and tuned prompts against production traces. You think in terms of capability, reliability, and unit economics, not just whether the model says the right thing. You enjoy time with the people who do the work, learning an industry's vocabulary, edge cases, and operational tempo, and you let that shape what you build. Dropped into a fuzzy customer problem with a half-formed hypothesis and a deadline, you scope, build, evaluate, and ship without waiting for a spec. You move between prompt iteration, eval design, backend services, and customer-facing UI in the same week, and you care about evals that catch regressions and traces that are easy to debug.
You Will
Embed with customers and operators to understand how supply chains run today, then design and ship agents that take meaningful work off their plate.
Build production agent systems on frontier LLMs: tool use, sub-agents, retrieval, structured outputs, MCP servers, and the orchestration that ties them together.
Own evaluation as a first-class discipline: datasets from real traces, rubrics and graders, experiments, and improvements you can prove move the needle.
Architect the data, services, and APIs the agent layer depends on, integrating our internal systems with customers' WMS, TMS, and ERP environments.
Codify repeatable deployment patterns so each new customer rollout is faster than the last.
Neo Further Reading
https://traba.work/resources/case-studies/how-shipsmarter-put-its-operation-on-autopilot-with-neo
https://finance.yahoo.com/technology/ai/articles/traba-launches-neo-ai-decides-191600907.html
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IMPORTANT NOTE: From now until Monday 24th August, candidates that the Traba team would like to interview will now be invited to the event below (next Wednesaday 26th August) at the Traba offices instead of a traditional recruiter screen.
Please ensure candidates are aware of this change in process but it should be an exciting opportunity to meet the team and hear more about the technical aspects of what they are building. Strong candidates with insightful questions and positive interactions may be accelerated through the process. If they are unable to attend, we can run a normal process.
Please reach out to **[email protected]** if there are any questions and we look forward to meeting candidates in-person.
Company at a glance
Traba develops autonomous AI workflows connecting industrial businesses with vetted workers, aiming to optimize global supply chain labor management. Backed by top-tier VCs, the company positions itself as foundational infrastructure for labor management.
What happens next
Skip the application pile. I get you in front of the people who decide.
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
A meeting lands on your calendar
When the company wants to meet, I get the call on your calendar. You just show up.
Culture & values
Company culture inspired by the early days of tech giants with emphasis on going above and beyond
Every team member is considered a critical part of the company's journey
Collaborative environment focused on crafting the future together
Dream Big value: creating bold direction that inspires life-changing vision and prioritizing long-term value over short-term results
Olympian's Work Ethic value: commitment to working harder, longer, and smarter with full dedication
Growth Mindset value: confronting tough challenges head-on, persevering through failure, and learning from setbacks
Customer Obsession value: going the extra mile for workers and businesses with focus on high-quality solutions
Culture emphasizes resilience and adaptation in the face of challenges
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