From the requirements call to a monitored feature in production. Here is how we vet, match and onboard every AI engineer we place.
Before an engineer joins our bench, they are tested on data handling, model integration, deployment practices, and a hands-on task taking a small feature from raw data to a working endpoint. Only engineers who pass are shortlisted to clients.
We match engineers to your specific requirements: the type of feature you are building, your data sources, and the timezone overlap that works for your team. You see 2 to 3 fitting profiles, not fifty.
The engineer gets access to your data and systems, reviews any existing work, and starts on your backlog in the first week. You manage priorities directly from there.
Works only on your account, not shared across other clients' work.
Access to the engineer on your own tools, with no account manager relay.
Full time, part time, or a fixed scope, adjustable with notice as your roadmap changes.
Review and testing on every pipeline and deployment before it reaches production.
Working hours arranged to overlap with your team for stand-ups and reviews.
A new engineer at no extra cost if the current one is not the right fit.
Tell us what you need built, and we will shortlist AI engineers who fit your project and your timezone.
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