Hiring a fractional AI engineer: scope, cost and questions to ask
A fractional AI engineer is a part-time engineering engagement, not a full team or an on-call service by default. It fits a continuing roadmap with a clear owner and bounded priorities. For a single, well-defined project, a fixed-scope sprint may be easier to buy.
Marco's published offer: US$2,500/mo. See scope and separate costs below.
By Marco Lee · Applied AI Engineer
Start with the work, not the job title
Part-time engineering can make sense when your team has a backlog of AI features or integrations but is not ready for a full-time hire. Someone on your side still needs to set priorities, answer domain questions and approve access. Hiring an engineer does not remove those product decisions.
Separate ongoing engineering from a one-off assessment. If you do not yet know which process is worth improving, start by scoping a diagnostic. If you need continuous incident coverage or several parallel projects, discuss that explicitly: a limited weekly allocation should not quietly become an unlimited support commitment.
Ask for evidence at the right level
Ask a candidate to distinguish software delivery experience, AI-assisted coding and delivery of AI-powered systems. They are related, but not interchangeable. A useful walkthrough covers what the engineer actually built, the decisions they owned, what failed and how another person could maintain the result.
Request examples of repository work, integration design and technical communication that can be shared lawfully. Do not require confidential client data as proof. For a proposed AI feature, ask how they would evaluate outputs, constrain access and escalate uncertain results. A convincing answer is a plan you can inspect, not an unsupported accuracy claim.
Marco's service is an offer to work inside your team. His published product work and engineering background are evidence to inspect; they should not be read as a portfolio of delivered client AI deployments.
Define the first month before signing
Choose one outcome small enough to test with the agreed capacity. For example, a read-only internal assistant could answer a bounded set of questions with references and send unresolved requests to a person. That is an illustrative pilot, not a promise of what every first month can deliver.
Write down what is out of scope as carefully as what is included. Separate time for meetings, discovery, implementation and review. Ask how blocked access or changing priorities affect the delivery plan. Weekly written updates should make progress and decisions visible even when you cannot attend every meeting.
- One prioritized outcome and the examples used to accept it.
- Weekly capacity, working-hours overlap and communication expectations.
- Repository and cloud-account ownership, with least-privilege access.
- Model and API usage budgets, and who authorizes extra work.
- The owner of production incidents and any separate support agreement.
- Documentation, access removal and handover when the engagement ends.
Compare the commitment, not an imagined hourly bargain
Use the published monthly allocation as the starting point for a scope conversation. Do not infer an hourly rate or a full-time-equivalent salary from it: calendar months, meetings, support and delivery obligations need explicit terms. Ask which costs are separate and what happens if you need more hours.
Marco's fractional offer is month to month with about eight to ten hours a week; additional capacity is scoped separately. Compare that arrangement with the work you actually need. If one fixed deliverable is the whole requirement, ask whether a sprint would be a cleaner engagement.
Marco's published offer
These are this service's prices, not a market average. Scope and recurring costs are confirmed in the quote.
- Part-time
- US$2,500/mo
- About 8–10 hours a week · month to month
- More hours
- Custom
- Up to half-time · scoped in a free call
Pricing source: Fractional AI Engineer.
Common questions
Is fractional AI engineering the same as hiring a full-time employee?
No. This guide uses fractional to mean a part-time engineering engagement with agreed capacity and scope. It does not imply full-time availability, a particular employment classification or unlimited support.
What should we agree on before the first month?
Define a prioritized outcome, acceptance examples, weekly capacity, account ownership, usage budgets, communication and handover. Make production support responsibilities explicit.
When is a sprint a better fit?
When you have one bounded problem or need a diagnostic before committing to an ongoing roadmap. Continuing implementation and iteration may be a better fit for a fractional engagement.
From guide to scope
Check the fractional offer's weekly capacity, collaboration model and monthly terms against your roadmap.
Fractional AI Engineer