Founding Engineer

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 is a VC-backed startup building an AI-powered product for enterprise teams, focused on data, automation and workflows. Our CEO has scaled analytics services before. Our CTO is a multi-time founder with deep developer-product experience.

The Role

You will be one of Trayo's founding engineers. You will own whole product areas end to end, from design to build to ship to iterate, and help make the technical decisions everything else is built on. The core of our product is AI agents working over large, messy data, so you will spend most of your time on agents, the backend systems behind them, and the product surfaces customers use.

Owning an area here means nobody hands you tickets. You decide with the founders and customers what to build, ship it, watch it in production, and fix it when it breaks. If a customer hits a bug in your area, you hear about it first and you close it.

We build with coding agents. Our engineers run several Claude Code and Codex sessions at the same time, each on its own task in its own worktree, and spend their own time on specs, review and verification. That is how a small team ships like a large one, and we expect you to work this way or want to learn it fast.

What You'll Do

• 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

Who We're Looking For

In order of importance:

• Startup builder and owner. You have thrived at an early-stage company as a founding engineer, early engineer or co-founder, not only in large corporate settings. You have owned something end to end, including what happened after it shipped.
• High throughput with AI. You already ship most of your code through coding agents, run several sessions at once, and have your own habits for keeping their output correct: tests, review, small PRs.
• AI agent experience. You have built AI agents hands-on, including agent orchestration and evals, not just LLM features.
• Backend and distributed-systems depth. You have strong backend and distributed-systems engineering skills, not only frontend web-app development.
• Product-minded. You think in terms of users and outcomes, and you have shipped user-facing products.
• Data fluency. You have worked with real data and know how to make sense of it.
• Hands-on IC today. You are currently an individual-contributor engineer, not a long-tenured founder running your own company.

You also work well in ambiguous, fast-moving environments and communicate clearly with engineers, founders and customers.

Nice to Have (not required)

• Experience with LLM providers and agent frameworks in production
• AWS or GCP, plus monitoring and logging tooling

What We Offer

• Competitive salary and meaningful founding-level equity
• A small team where your work shapes the company
• Hybrid flexibility, with a hub in San Mateo