Engineering Manager (AI)
Aiprise · San Jose, CA
About this role
**ABOUT AIPRISE** AiPrise is a YC-backed, Series A company building global compliance infrastructure for financial services. We help banks, fintechs, cross-border payment providers, stablecoin/crypto companies, and marketplaces gain a 360° view of every business they onboard—anywhere in the world. Through a single integration, we connect **800+ data sources** and **80+ verification partners** across **200+ countries**, powering **KYB, KYC, AML, sanctions screening, and ongoing monitoring**. Our AI Agents help compliance teams do more with less—resolving more cases, catching more fraud, and scaling operations without scaling headcount. We’re ~60 people, Series A funded, and obsessed with one problem: **making compliance feel simple**. --- **ABOUT THE ROLE** We’re hiring an **Engineering Manager (AI)** to lead and grow the team that builds AiPrise’s AI agents. This is a **player-coach** role: you’ll manage, hire, and develop engineers, while staying close enough to the code to design agent architectures, review prompts/tool definitions, and debug failing evals yourself. In a regulated domain like **KYC/KYB**, confidently wrong agents can create real customer risk and audit exposure—so **quality and observability matter as much as speed**. --- **WHAT YOU’LL DO** **Lead the team (5–6 AI + backend engineers)** - Run weekly 1:1s, set clear goals, provide honest feedback, and build career growth plans. - Hire the next wave of AI engineers; own the interview loop for agent-engineering roles and raise the bar. - Drive planning and delivery for the AI roadmap with Product so the team ships on predictable cycles without burnout. - Build a culture where engineers write **evals before claiming wins**, and incidents lead to fixes—not blame. **Build the agents (hands-on)** - Design and review compliance agents—from single-document checks to multi-step investigations that hand off to human reviewers. - Build reusable **skills, tools, and memory** that agents rely on to call registries/data vendors and maintain context across a case. - Own the eval stack: golden datasets (with compliance experts), regression tests in CI, and production monitoring. - Write/review code ~**50%** of the time; choose models based on **accuracy, cost, and latency**. --- **WHAT WE’RE LOOKING FOR** **People leadership** - **2+ years** managing engineers directly (hiring, performance reviews, and at least one hard conversation handled well). - A track record of growing engineers (promotions or expanded scope due to your support). - Experience running planning and delivery in a fast-moving startup/scale-up. **Hands-on agent engineering** - **6+ years** as a software engineer with strong backend skills in **Python or TypeScript**. - Built and shipped **LLM agents to production** (not just prototypes), and can explain what broke and how you fixed it. - Practical experience with: - Tool/function-calling interface design - Packaging reusable skills/prompt modules - Agent memory (short-term context, long-term stores, retrieval) - Building evals that gate releases - Comfort with at least one major model API (**Anthropic, OpenAI, or similar**) and understanding trade-offs between agent frameworks and plain code. - A measurement mindset: show an eval you built, the metric it tracked, and the decision it changed. **How you work** - Clear written communication; can explain agent failures to both compliance stakeholders and engineers. - Strong judgment on when to build
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.