Applied AI Engineer (Remote)
Straight from OpenRouter’s careers page. Apply on the company site — no recruiter, no middleman.
Applied AI Engineer
Department: Engineering
Location: Remote (US)
Compensation: $215K – $280K • Offers Equity
Employment Type: FullTime
About OpenRouter
OpenRouter is the AI routing and infrastructure layer that AI builders, AI-native startups, and enterprises use to access, manage, and optimize their AI usage through a unified API, billing interface, and analytics platform. We route billions of tokens every month and sit at the center of how organizations operationalize LLMs across research, product, and production workloads.
We are a small team that punches above its weight. Every person here has direct impact on the product and our users.
About the Role
Were hiring two Applied AI Engineers to build the internal agentic tooling that runs OpenRouter — one focused on support, one focused on go-to-market. The two roles operate the same way; the difference is which domain you go deep on.
We believe we can build software that fits our needs rather than buy software built for the masses. The best technical companies built proprietary tools, and youll have the chance to do that at OpenRouter.
This is not a zero-to-one role. The first 80% is easy. Getting the last 20% right — reliability, edge cases, the unglamorous finishing work — and earning adoption across a team that has other options is the actual job.
What Youll Do
Build internal agentic workflows end-to-end on OpenRouter, from prototype to production, that automate support and GTM operations
Integrate our systems with the tools the company runs on, and steadily replace those tools where it makes sense to
Own the reliability of what you ship: evals, guardrails, and monitoring, so automation is trustworthy rather than flashy
Drive measurable impact — deflect support volume, accelerate GTM motions, cut manual toil — and prove it with data
Work directly with support, GTM, and engineering to find the highest-leverage workflows to automate next
Iterate on real usage: ship, measure, improve
What Were Looking For
Build-over-buy conviction. You build on internal tools first and champion them over polished external options, even when the internal path is slightly more painful. You buy only for genuine expertise, never for something buildable in a day.
You push the last 20%. Youve worked on internally-built tooling and made it good enough that people chose it. Youre energized by reliability, edge cases, and polish, and you dont delegate the hard part.
Domain fluency in support or GTM. Hands-on with ticketing, CRM, sales ops, or customer-facing workflows, so you know which work is actually worth automating.
Architectural range. You understand systems end-to-end and can jump into any part of one. Deep backend orientation; front-end work is not the point here.
A security mindset. Youll be building integrations with broad internal access. You think about permissions, blast radius, and the second-order effects of what an agent is about to do before it does it.
Evals and data rigor. You measure automation impact quantitatively rather than asserting it.
Excellence, time-boxed. A near-perfect bar, but disciplined enough to ship rather than polish forever.
Nice To Haves
Experience across three or more agent harnesses. We dont need expertise in any one of them; we want to see that youve tried things.
Youve built your own agent harness for a workflow
Production LLM/agentic systems shipped with strong engineering fundamentals
Open-source contributions to dev tooling or agent frameworks
If you dont think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and were looking for someone who is excited to join the team.
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