Hiring
How to hire a forward-deployed AI engineer
To hire a forward-deployed AI engineer, write down the first workflow, test for production judgment, and agree who owns the code before work starts.
Updated / 3 min read
Short answer
Hire for one real workflow instead of a list of AI tools. Test discovery, product judgment, systems engineering, evaluation, and delivery. Agree acceptance criteria, code ownership, and handover before work starts.
Write the workflow brief before the job description
Before you look for an engineer, write down the workflow you want fixed. Name the people who do it, the systems they use, the decisions they repeat, the usual exceptions, and what the current process costs. A candidate can work with that brief. They can't work with a list of AI tools.
A strong candidate will push on the brief. They'll ask about ownership, data access, permissions, failure cases, and whether people will use it. They should help you make the first scope smaller.
Check five skills that have to work together
Model experience isn't enough. An FDE has to go from a user interview to an architecture decision to a failing API to a production rollout, and keep the business result in view the whole time.
- Workflow discovery: can they find the rules and edge cases?
- Product judgment: can they pick a useful first boundary?
- Systems engineering: can they build secure, reliable software?
- AI evaluation: can they measure quality and handle uncertainty?
- Delivery: can they launch with users and hand over ownership?
Test judgment on a real workflow
Give the candidate a real workflow with the sensitive details removed. Ask them to map it, list the unknowns, propose a small first release, and say what they wouldn't automate. That tests judgment without asking for free production work.
Then ask how they'd handle missing data, model errors, access control, human review, observability, and rollback. Good answers are usually specific and simple. Be wary if every problem leads to a new platform or a big data project.
Put the repository, controls, and handover in the contract
The contract should name the repository, the environments, the documentation, how credentials are handled, how it deploys, the monitoring, and the handover. It should also say which third-party services will keep costing money.
Define acceptance in terms of the workflow. For example: the system prepares a complete report from approved sources, sends uncertain cases to review, and records every decision. “Build an AI agent” isn't an acceptance test.
Keep the first release small enough to judge
A one-week sprint can map the workflow and prove the risky integration. A focused MVP can then take one path from input to production use. Keep the same internal owner involved through both.
At the end, look at adoption, quality, time saved, exceptions, and running cost. Expand only if the evidence holds up. This protects the budget and gives the engineer a clear target.
Key points
- Start from a workflow brief instead of a generic AI job description.
- Test judgment on a real problem with the sensitive details removed.
- Define acceptance by workflow results and failure handling.
- Name the internal owner before the engagement starts.
Common questions
What should I look for in a forward-deployed AI engineer?
Production engineering skill, good workflow discovery, sound product judgment, integration experience, and a track record of handing systems over to client teams.
Should an FDE have machine-learning research experience?
It helps on model-heavy work. For most implementations it isn't the main thing. Systems design, data, integrations, evaluations, and reliable delivery usually matter more.
How should I scope the first FDE project?
Pick one repeated workflow with a clear owner, known inputs, a result you can measure, and enough volume or cost to justify the work.
Who should own the system after launch?
Name an internal product or operations owner before work starts. The FDE team builds the system and hands it over. Someone on your side owns the result and the decisions that come after.