We are seeking an entrepreneurial
Senior Applied Agent Engineer to join as a founding member of the Agents team and help us build the next layer of Traba's product-an agentic platform that synthesizes the data flowing through our marketplace and operates autonomously inside our customers' supply chain workflows. You'll 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 0-to-1 ideas to scaled deployments.
About You- Builder with an AI operator's instinct. You've shipped real product on top of LLMs-not just chat wrappers. You've 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 "does the model say the right thing."
- Domain-immersed. You enjoy spending time with the people who actually do the work. You learn an industry's vocabulary, edge cases, and operational tempo, and let that knowledge shape what you build. Bonus points if you've done this for a vertical AI or AI-agent company before (e.g., Nash, HappyRobot, Augment, Pallet, Harvey, Legora, ElevenLabs).
- High-agency in ambiguity. You're comfortable being dropped into a fuzzy problem with a customer, a half-formed hypothesis, and a deadline. You scope, build, evaluate, and ship without waiting for someone to hand you the spec.
- Sweat both ends of the stack. You can move between prompt iteration, eval design, backend services, data modeling, and the customer-facing UI in the same week. You care about the small details-evals that actually catch regressions, prompts that fail gracefully, traces that are easy to debug.
You Will- Embed with our customers and operators to deeply understand how supply chains run today-then design and ship agents that take meaningful work off their plate.
- Build production agent systems on top of frontier LLMs: tool use, sub-agents, retrieval, structured outputs, MCP servers, and the orchestration layer that ties them together.
- Own evaluation as a first-class discipline. Build datasets from real traces, write rubrics and graders, run experiments, and ship improvements that you can prove move the needle.
- Architect and build the data, services, and APIs the agent layer depends on-integrating with our internal systems and our customers' WMS, TMS, and ERP environments.
- Codify repeatable deployment patterns so each new customer rollout is faster and more reliable than the last.
- Be a key player on a scrappy founding team-contributing to product direction, hiring, and the engineering culture as we grow.
You Have- 5+ years of professional software engineering experience, with at least 1+ year shipping LLM- or agent-based features into production.
- Strong proficiency in Python and/or TypeScript/Node.js, and comfort designing APIs, distributed systems, and data models in PostgreSQL.
- Hands-on experience with the modern agent stack: prompt engineering at production scale, evaluation frameworks (e.g., Langfuse, Braintrust, internal harnesses), agent orchestration patterns, and frontier model APIs (Anthropic, OpenAI, etc.).
- A track record of building and shipping in fast, ambiguous environments-ideally at an early-stage vertical AI, AI-agent, FDE-style (Palantir, Scale), or data-product company (Hex, Omni, dbt).
- Excellent written and verbal communication-you can run a customer workshop in the morning and write a clean design doc in the afternoon.
- A genuine excitement about industrial operations and the chance to use applied AI to make them dramatically better.
Benefits- Start-up equity
- Competitive Salary
- 100% Paid health, dental & vision coverage
- Dinner Provided via DoorDash, free DashPass & stocked kitchen for NY employees
- 🚍 Commuter benefit
- 🏋 Gympass Benefit
- ✚✚ Additional: One Medical Membership, Gympass, HSA via Optum, Talkspace, HealthAdvocate, Teledoc Health
Salary Range DetailsThe compensation range for this position is set between $200,000 and $240,000, reflecting our market analysis and other relevant considerations. However, exceptions may be made for candidates with qualifications that significantly differ from those outlined in the job description.
