The honest comparison, from a firm that does one of these for a living. A senior US AI hire runs $300K+ all in (salary, benefits, equity, recruiting) and takes about six months to land, bidding against the AI labs for the same people. A forward deployed AI engineer is $9,500 a month inside your team in 7 to 10 days. Those are different bets, and each is right for a different situation.
| Hiring in house | Forward deployed | |
|---|---|---|
| Time to start | About six months to fill the role | 7 to 10 days to deployed |
| Year one cost | $300K+ all in | $114K ($9,500 per month) |
| If it is not working | Severance, restart the six month search | 120 day replacement guarantee |
| Accountability | An individual's output | A system reaching production, proven with evals |
| Knowledge stays when they leave | Often walks out the door | Built in your codebase, run by your team, no handoff cliff |
| Best for | A permanent AI platform team, multiple systems, long horizon | Your first one or two production AI systems, this year |
If AI becomes core product and you need a standing platform team, hire. An employee compounds in ways no engagement can: equity alignment, institutional depth, always there. The mistake is making the $300K hire your first move, before you know what to build. Most mid market companies need one working system and the evidence it produces before a hiring case even exists. Forward deploy first, hire from strength later, often with our engineer training your new hires during the overlap.
Not the resume. The workflow. If you do not yet know which workflow AI pays back in, neither path is ready: start with the AI Readiness Assessment ($2,500, two weeks, ranked plan with ROI and TCO), credited in full toward the forward deployed engagement. New to the model? What a forward deployed AI engineer actually does.
One senior AI engineer, inside your team, accountable for a system reaching production. 96% client retention, Clutch verified.
See the Forward Deployed AI Engineer