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You will build and ship product features for an AI agent evaluation platform while engaging with the developer community to gather feedback. The role requires balancing technical feature development with marketing, customer demos, and community building.
This is a Product Engineer role on an AI agent evaluation product, sitting at the intersection of engineering and community. You will ship features that help agent builders build more reliably, while creating in public to close the loop between what the community needs and what gets built. Invisible shipping is shipping that does not matter, so distribution is part of the job.
Build and ship product features across evals, replay, cohorts, and developer experience, with strong judgment about what is sharp versus theater.
Create in public on X and GitHub, posting, demoing, and engaging with the AI engineering community to surface signal that feeds back into the product.
Wear whatever hat the week demands, whether that is feature work, a marketing motion, customer demos, or community engagement.
Stay close to the target users: AI agent builders, eval practitioners, and developers working with agent frameworks and custom runtimes.
Close the loop between community feedback and product decisions, ensuring no wall exists between build and distribution.
3+ years building or shipping production software, with demonstrated experience building or evaluating agents in production environments.
Strong Python proficiency for production code.
Hands-on experience with agent frameworks such as LangGraph, or equivalent tools.
Experience building or working with evaluation systems for LLM or agent outputs.
Experience with trace data, observability, or debugging agent execution.
Experience shipping developer tools, SDKs, or APIs with attention to documentation, ergonomics, and demos.
Open-source contributions with measurable adoption or usage by other developers.
Active public presence on X, GitHub, or similar platforms demonstrating the ability to communicate and market technical work.
Comfort operating in early-stage, high-uncertainty environments and wearing multiple roles concurrently.
Experience with LLM observability platforms or production ML infrastructure is a plus.
Salary range: $125,000 to $190,000 USD annually.
This role is fully remote. The primary location is Munich, Bavaria, Germany, though the team also has presence in San Francisco and across Western Europe.
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