Founding AI Engineer: Build Production Agents & Systems

Trayo; New York (NY); Hybrid; USD 150,000 - 250,000; Full time

Benefits offered by this job

Founding-level equity

Small team impact

Hybrid work with Bay Area hub

Job summary

Trayo, a VC-backed startup, is seeking a founding engineer to own end-to-end product areas—from design to ship and iteration. You will focus on AI agents operating over large, messy data, building the backend, surfaces customers use, and guiding technical decisions with the founders.

You’ll work directly with the founders and customers to decide what to build next, ship features end to end, run production systems, and uphold strong tests and reviews in a small, high-ownership team with hybrid

Responsibilities

• Own a product area: choose what to build with founders and customers, ship it, run it in production, and answer for how it works
• Run many coding-agent sessions in parallel, and keep the tests, reviews and checks strong enough that what they produce is safe to ship
• Design, build and run production AI agents: orchestration, tool use, memory, and the evals that tell us whether they work
• Build the backend and distributed systems behind them: APIs, data models, pipelines, queues and background jobs
• Turn large, noisy datasets into signals customers can act on
• Ship customer-facing features end to end, across backend and frontend
• Improve reliability, observability and performance as usage grows
• Set the engineering standards and hiring bar for the team that comes after you
• Work directly with the founders and customers to decide what to build next

Job description

Trayo, a VC-backed startup, is seeking a founding engineer to own end-to-end product areas—from design to ship and iteration. You will focus on AI agents operating over large, messy data, building the backend, surfaces customers use, and guiding technical decisions with the founders.

You’ll work directly with the founders and customers to decide what to build next, ship features end to end, run production systems, and uphold strong tests and reviews in a small, high-ownership team with hybrid