Employer description & source details
We are hiring an Engineering Manager to lead and grow the team that builds AiPrise's AI agents. This is a player-coach role: you will manage, hire and develop engineers, and you will also stay close enough to the code to design agent architectures, review prompts and tool definitions, and debug a failing eval yourself. You will own how our agents are built, measured and shipped: the skills and tools they call, how they remember context across a case, and the evals that tell us whether a change made them better or worse. In a regulated domain like KYC and KYB, an agent that is confidently wrong costs our customers real money and audit risk, so quality and observability matter as much as speed. Manage a team of 5-6 AI and backend engineers: weekly 1:1s, clear goals, honest feedback and career growth plans. Hire the next wave of AI engineers. You will own the interview loop for agent-engineering roles and raise the bar on it. Run planning and delivery for the AI roadmap with product, so the team ships on predictable cycles without burning out. Build a culture where engineers write evals before they claim a win, and where incidents lead to fixes, not blame. Design and review our compliance agents, from single document checks to multi-step investigations that hand off to human reviewers. Build the reusable skills, tools and memory our agents rely on to call registries and data vendors and carry context across a case. Own the eval stack: golden datasets built with compliance experts, regression tests in CI and production monitoring. Write and review code about 50% of the time, and choose models based on accuracy, cost and latency. 2+ years managing engineers directly, including hiring, performance reviews and at least one hard conversation you handled well. A track record of
Extracted skills: python, operations