Engineering Manager (AI)

AiPrise • San Jose, CA

1d • $185,000 - $230,000

About The Position

AiPrise is hiring an Engineering Manager to lead and grow the team building its AI agents. This is a player-coach role combining people management, hiring, and engineer development with hands-on work designing agent architectures, reviewing prompts and tool definitions, and debugging evaluations.

The manager will own how agents are built, measured, and shipped, including their skills and tools, case-context memory, and evaluations. Because AiPrise operates in regulated KYC and KYB compliance, agent quality and observability are critical alongside delivery speed. The role manages a team of 5–6 AI and backend engineers and spends about 50% of the time writing and reviewing code.

Requirements

• At least 2 years of direct engineering management experience, including hiring, performance reviews, and handling a difficult conversation effectively.
• A track record of developing engineers, with at least one person managed being promoted or taking on a larger scope as a result of the candidate’s support.
• Experience running team planning and delivery at a fast-moving startup or scale-up.
• At least 6 years of software engineering experience, with strong backend skills in Python or TypeScript.
• Experience building and shipping LLM agents to production, and ability to explain failures and how they were fixed.
• Practical experience designing tool and function-calling interfaces.
• Practical experience packaging reusable skills or prompt modules.
• Practical experience implementing agent memory, including short-term context, long-term stores, and retrieval.
• Practical experience building evaluations that gate releases.
• Familiarity with at least one major model API, such as Anthropic or OpenAI, and the trade-offs between agent frameworks and plain code.
• A habit of measurement, including the ability to show an evaluation built, the metric tracked, and a decision it changed.
• Clear written communication, including the ability to explain agent failures to compliance leads and engineers.
• Good judgment about when to build, buy, or keep a human in the loop.

Nice To Haves

• Experience in fintech, regtech, fraud, identity verification, or another regulated domain where AI decisions need an audit trail.
• Document AI experience, such as OCR, document classification, or extraction across many languages and formats.
• Experience with LLM observability and tracing tools, and with cost and latency optimization at scale.
• Contributions to open-source agent, evaluation, or retrieval projects, or public writing on the topic.

Responsibilities

• Manage a team of 5–6 AI and backend engineers through weekly one-on-ones, clear goals, feedback, and career growth plans.
• Hire AI engineers and own the interview loop for agent-engineering roles.
• Plan and deliver the AI roadmap with product, supporting predictable delivery cycles and sustainable workloads.
• Build a culture of writing evaluations before claiming improvements and responding to incidents with fixes rather than blame.
• Design and review compliance agents, from document checks to multi-step investigations handed off to human reviewers.
• Build reusable agent skills, tools, and memory for calling registries and data vendors and carrying context across a case.
• Own the evaluation stack, including golden datasets developed with compliance experts, regression tests in CI, and production monitoring.
• Write and review code about 50% of the time, and select models based on accuracy, cost, and latency.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed