Forward Deployment Engineer - Agentic AI

EU or US · Travel required across both regions 

Most AI roles keep you at arm’s length from the people the agents are supposed to help. This one puts you in the room with them. 

We’re building AI agents for risk managers, internal auditors, and compliance professionals, not assistants that surface suggestions, but agents that own complex, multi-step workflows end to end. Agents that an audit team can hand a task to and trust it will come back done. Getting from a promising agent prototype to something a Chief Audit Officer depends on is a completely different discipline to building the prototype. That’s what this role is about. 

As a Forward Deployed Engineer, roughly 80% of your time is with our biggest enterprise customers across Europe and the US. You’re embedded in their environments, sitting with internal audit teams as they plan an audit programme, with risk functions assessing their control landscape, with compliance teams navigating regulatory obligations. You’re not there to show them what the agents already do. You’re there to understand their world well enough to discover what the agents need to do next. 

You run discovery workshops, identify which workflows are genuinely ripe for agentic automation, prototype rapidly, test with real practitioners, and stay until the agent is reliable enough to be trusted. 

The other 20% is feeding everything you’ve learned back into the platform. The goal isn’t to accumulate bespoke agent builds, it’s to identify the patterns across risk and audit functions that should be generalised, so every subsequent engagement is faster and the agents get better for everyone. 

You sit in Product with a matrix into Engineering , which means you shape both the agent roadmap and the technical decisions that make agents work in production. 

This is not a sales role and it’s not consulting. 

You write code. You build evaluation infrastructure. You design golden datasets grounded in real audit and risk workflows. You catch agent regressions before a customer’s compliance team does. You’re accountable for outcomes. 

The Hard Parts of Agentic AI Are Your Domain 

Silent regressions when a model updates. Context window degradation across long audit workflows. Prompt instability under varied user inputs. Non-deterministic outputs in environments where a compliance officer needs to explain every decision to a regulator. You know these failure modes and you know how to build the guardrails, tracing, and evaluation infrastructure that prevents them. 

The Customer Environment 

Enterprise GRC, global banks, large regulated corporates, sophisticated internal audit and risk functions across Europe and the US. 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. These are people whose professional reputations depend on getting this right; that’s a good reason to make the agents actually reliable. 

Travel is a meaningful part of this role. You’ll be on-site regularly with enterprise customers across EU and US markets. If you’re energised by variety, different industries, different regulatory cultures, different stages of agent maturity - this will suit you well. 

These are the essentials you’ll need to get an interview: 

Apply If You… 

• 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 

People who do this kind of work go on to exceptional careers in product creation, product leadership, and founding companies. There is no faster path to understanding how to build agentic AI that creates real value than embedding directly with the people it needs to serve.