JetBrains

AI startup

ResearchEngineer

Amsterdam, Netherlands Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Research Engineer at JetBrains. Skills: engineering, ML, LLMs, agents. Ship AI product features that combine engineering and ML. Build and improve agent workflows (tooling, retries, guardrails, fallbacks)”

What You'll Achieve.

own outcomes end to end; improve the product over time

Industry & Context.

AI startup
Problems you'll solve

reliability work; handle failures

What They're Looking For.

Must Have

Shipped real systems, not just demos or prototypes, Built software with LLMs (structured outputs/function calling, tool use, reliability work), Built agents (multi-step workflows that call tools, keep states, and handle failures), Set up evals to track quality (tests, regression checks, eval harnesses), Comfortable moving fast, iterating, and owning outcomes end to end

What You'll Do.

Ship AI product features that combine engineering and ML

Build and improve agent workflows (tooling

and reliability of our systems

Track what’s new in the AI space (agent teams

tooling) and turn it into shipped products

Build self-improving loops: systems that run experiments

learn from feedback and evals

and improve the product over time

Full Job Description

Kineto (kineto.app) is an AI startup backed by JetBrains. We’re building the next creator stack – tools that help creators talk to their audience in new ways, turn ideas into content, and build sustainable businesses – powered by LLMs and agents. We’re now looking for a Research Engineer with a strong grounding in engineering or ML who wants to turn ideas into shipped products. How we work We move fast and iterate. We ship early, measure results, and improve quickly. If something works, we double down. If it doesn’t, we cut it. Delivery and measurement are part of the culture, and everyone owns outcomes end to end. In this role, you will: Ship AI product features that combine engineering and ML. Build and improve agent workflows (tooling, retries, guardrails, fallbacks). Improve the latency, cost, and reliability of our systems. Track what’s new in the AI space (agent teams, methods, tooling) and turn it into shipped products. Build self-improving loops: systems that run experiments, learn from feedback and evals, and improve the product over time. We’d be happy to have you on our team if you: Have shipped real systems, not just demos or prototypes. Have built software with LLMs (structured outputs/function calling, tool use, reliability work). Have built agents (multi-step workflows that call tools, keep states, and handle failures). Have set up evals to track quality (tests, regression checks, eval harnesses). Feel comfortable moving fast, iterating, and owning outcomes end to end. #LI-MP1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

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