Responsibilities
- Run discovery workshops with enterprise customers to understand their workflows and needs.
- Identify which workflows are genuinely ripe for agentic automation.
- Prototype AI agents rapidly and test with real practitioners.
- Stay with customers until the agent is reliable enough to be trusted.
- Feed learnings back into the platform to identify patterns for generalization.
- Write code to build and improve AI agents.
- Build evaluation infrastructure for agent performance and reliability.
- Design golden datasets grounded in real audit and risk workflows.
- Catch agent regressions before customers do.
- Shape the agent roadmap and technical decisions in collaboration with Product and Engineering.
Requirements
- Have shipped at least one production agent and know what the reliability cliff feels like.
- Understand the full Agent Development Life Cycle: evaluation, guardrails, observability, regression — not just deployment.
- Are as comfortable in a room with a Chief Risk Officer as you are debugging a failing agent trace.
- Are genuinely curious about how risk managers, internal auditors, and compliance professionals work.
- Can tell the difference between a workflow that needs an agent and one that needs a button.
- Want to be the person who makes enterprise agentic AI actually land, not the person who hands it off.
Work Arrangement
Hybrid — EU, US
Additional Information
- Travel is a meaningful part of this role. You’ll be on-site regularly with enterprise customers across EU and US markets.
- The role involves understanding enterprise GRC, global banks, large regulated corporations, and sophisticated internal audit and risk functions.
- You don’t need a compliance background, but you need the curiosity to learn it fast and the presence to earn trust with senior risk and audit professionals.
