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Job description
Requirements
You've already built agents that survived contact with reality. You've shipped agent systems into production at meaningful scale—designed the harness, picked the orchestration patterns, owned the evals, and lived with the on-call
You have strong opinions on where to draw the line between prompting, fine-tuning, retrieval, and code, and why
Domain depth meets technical breadth. You're as comfortable in a warehouse on a customer site as you are in a design doc
You learn an industry's actual operations—WMS quirks, shift cadence, exception handling—and let that knowledge shape architecture decisions
Ideal: prior experience at a vertical AI or AI-agent company (Nash, HappyRobot, Augment, Pallet, Harvey, Legora, ElevenLabs), Palantir/Scale-style FDE, or an AI-native data company (Hex, Omni, dbt)
Set direction by shipping. You raise the engineering bar by writing the canonical example, not just the doc
You pick the foundational tools, integrate the right model providers, design the eval infrastructure—and you bring others along
Sweat the small stuff at staff scale. You have strong opinions on design patterns, eval datasets, prompt versioning, observability for agents, and the difference between a clean abstraction and an over-engineered one
You understand that how we do one thing is how we do everything
7+ years of professional software engineering experience, with 2+ years of hands‑on production work on LLM‑ or agent‑based systems
Deep proficiency in Python and/or TypeScript/Node.js, and a strong track record designing distributed systems, APIs, and data models on PostgreSQL and modern messaging (Kafka, RabbitMQ, or equivalent)
Demonstrated ownership of a non‑trivial production agent system: orchestration, tool use, retrieval, evals, observability, cost/latency tuning, and the operational lessons that come with all of it
Background that maps to at least one of: vertical AI / AI‑agent company, Palantir/Scale‑style FDE, or an AI‑native data company (Hex, Omni, dbt). Bonus for supply chain, logistics, or industrial operations exposure
A history of leading 0‑to‑1 product builds in early‑stage environments—comfortable with ambiguity, pragmatic about tradeoffs, and high‑agency by default
Strong written and verbal communication. You can run a customer workshop, write the design doc, and recruit your future teammates—often in the same week
A genuine excitement about industrial operations and the chance to use applied AI to make them dramatically better
What the job involves
We are seeking an entrepreneurial Staff Applied Agent Engineer to join as a founding member of the Agents team and lead the development of Traba's agentic platform—the layer that synthesizes the data flowing through our marketplace, talks to our customers' operational systems, and acts autonomously inside the workflows that run their facilities
You'll partner with our CTO to make the core architectural calls on how agents are built, evaluated, and deployed at Traba; set the bar for quality and reliability; and bring the outside perspective on agent-building, FDE‑style customer immersion, and data‑product craft that this 0‑to‑1 product needs
Architect Traba's agent platform end‑to‑end—the orchestration runtime, the eval and observability stack, the integration layer to internal services and customer systems (WMS/TMS/ERP), and the patterns that every agent we ship is built on
Own the foundational technical decisions for this part of the business: model strategy, agent harness design, retrieval and memory architecture, tool/MCP surface, and how we measure quality
Spend real time in the field with customers and operators. Translate what you see into durable product and codify repeatable deployment patterns so each rollout compounds on the last
Build evaluation as a real engineering discipline—datasets, graders, regression suites, experimentation tooling—so we ship agent improvements with the same confidence we'd ship backend code
Hire and mentor the engineers who will build alongside you. Set the technical standards that define what "good" looks like for applied AI at Traba
Partner with the CTO, product, and ops leadership on the multi‑year platform roadmap. Think ahead to what the company and the agent layer will need a year or two from now, and start building it today
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.