Senior Product Manager

The role is about turning application security ideas into dependable AI agent features inside the tools developers already use. That means deciding which agents to build, what each one takes in and returns, and how to balance cost against speed. A strong candidate has product management experience with developer platforms, can talk technically with engineers and customers, and has shipped AI or agent features with clear guardrails and success measures.

The work sits right where AI coding meets security: agents write code quickly, and this product aims to check and fix it as it happens. AI can handle triage, pull request feedback and fix suggestions, but a person still has to choose what is worth building, set what counts as trustworthy, and decide where an agent should stop. Customer conversations and judgment about real security trade-offs stay human.

This role offers hands-on practice designing agent workflows that connect through hooks, skills and MCP into coding agents. Someone would learn how to define inputs, outputs, service levels and quality measures for AI features that security teams rely on. To prepare, a candidate could build a small agent that triages vulnerability reports, then measure how often its answers are right and how long it takes.

• Developer platform product launches
• Shipped AI or agent features
• Defining agent guardrails and metrics
• Application security fundamentals
• Technical depth with customers

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

Per the company, Endor Labs provides an agentic application security platform that secures AI-generated code, open source dependencies, and containers.