What Does an AI Deployment Team Cost?

Most budgets for AI deployment go wrong in the same way: they price the model and the prototype, and forget the team that has to make it work inside real systems. This guide gives ranges for the four common ways to staff a deployment and explains what moves the number.

The four staffing models

Internal team. You hire AI or forward deployed engineers onto your payroll. In North America and Western Europe a senior AI engineer with production experience costs roughly $160K–$250K in salary before benefits, plus recruiting fees and three to six months of hiring time. The first productive month often arrives five months after you decide to hire.

Embedded FDE or FDE pod. A provider places one engineer or a small pod (typically two to four people) inside your team and tools. Published monthly rates on this platform cluster between $8K and $30K per engineer depending on region and seniority, with pods from $25K to $60K per month. Engagements run three to nine months and usually include a handover.

Staff augmentation. Engineers billed hourly or monthly under your management. Rates range widely by region: roughly $40–$70 per hour from South Asia and Latin America, $80–$150 in Europe and $120–$220 in the United States. The hidden cost is your own management time, which is real and should be in the model.

AI implementation partner. The provider owns delivery to a defined scope. Fixed-scope projects for a single production deployment commonly land between $60K and $250K, with enterprise programmes well beyond that. Post-launch support is usually a separate retainer.

What actually drives cost

1. Integration count. Every system the AI must read from or write to adds design, auth, testing and failure handling. Three integrations is a different project from one.
2. Deployment count. One internal assistant is a project. Twenty customer deployments is a function, which is why companies with repeat deployments end up hiring FDEs.
3. Security and hosting. VPC, on-prem or regulated data can add 30–50% to timelines through review cycles and environment work.
4. Evaluation and monitoring. Teams that skip this ship faster and then pay for it in incidents. Budget for it explicitly.
5. Ongoing iteration. Prompts, retrieval and integrations drift. Someone has to own it after launch.

A quick way to compare

The cost calculator on this platform puts the four models side by side using your numbers, including hiring delay and ramp-up for the internal option. Use it as a sanity check rather than a quote, then take the assessment to see which model fits your situation.

Where providers publish pricing

A minority of providers in our directory publish pricing. Where they do, we show it on the profile and use it in matching. Where they don't, ask early: minimum engagement, monthly rate per engineer, what "pod" means in headcount and seniority, and what is excluded.