Hire AI Developers

When you hire an AI engineer, look for delivery evidence rather than a long tool list. Relevant use-case experience matters, along with solid software and data engineering, since most work sits in preparation, integration, and evaluation. Ask how they have tested output quality, deployed a feature, and handled its costs and failures. Communication counts too: the developer needs to explain trade-offs to your team.

Yes. Our embedded AI developers join your existing engineers and work to your process. That means sharing your backlog, repositories, and code review, and attending the meetings where priorities are set. We agree responsibilities up front so it is clear who leads technical decisions and who coordinates delivery. Reporting and collaboration expectations are set before the engagement starts.

Yes. You can interview the developers we propose before the engagement begins. Use the time to look at relevant projects, how they approach a technical problem, and how they communicate with a team that is not their own. Ask about the part of your scope that worries you most. The interview is a fit check for both sides, and you decide whether to proceed.

Yes. Part-time engagement is available, and the working pattern is agreed to your project rather than a fixed template. A specialist might cover a few days a week, or join at a set point in the delivery to handle one part of the scope. Capacity, duration, and hours are set during scoping, once the work and the required skills are clear.

Cost depends on the expertise, capacity, and engagement model the work requires. Scope, data preparation, and integration effort all move the estimate, and a bounded task costs far less than a multi-role build. Development fees are separate from ongoing costs such as model or API usage, hosting, and maintenance. We prepare a figure once we understand the scope; no rates are published until that discussion.

Before work starts, we agree the working-hour overlap, the communication channels, and how often you get updates. Access to your repositories, environments, and tools is set up with the permissions your team approves, and technical ownership is written down rather than assumed. If you hire remote AI developers, the delivery cadence is the same as any embedded team: agreed checkpoints, shared visibility, and clear points of contact.

These are two different timelines. Staffing and onboarding depend on the skills your scope needs and how quickly access and setup can be arranged. Project duration depends on scope, data readiness, and how many review cycles the work requires. We give you a realistic view of both after the first scoping conversation, based on the skills available at that time.

Yes, on either route. A proof of concept can be scoped as a bounded feasibility or evaluation task that answers a specific question before you commit to a larger build. If you already have an AI product, we can scope an improvement, such as better retrieval, stronger evaluation, or fixes to how it handles failure. Any later build or ongoing maintenance is agreed separately.

Access is scoped to what the work needs, and provider and hosting choices are made against your privacy and cost requirements. Quality is managed by evaluating the feature on representative inputs, then setting review and fallback paths for cases where the output is uncertain. Monitoring continues after release, so behavior and cost stay visible. We plan these controls with your team and document them.

You own the code we implement for you, and that ownership takes effect after implementation. That covers the application code, not third-party software, pre-trained models, or libraries, which stay under their own licenses and terms. The contract sets out the details of what transfers and when. If you have a standard agreement or specific IP requirements, we can work within it.

Advisory support is available where it helps, usually around scoping, architecture, and evaluation. In many engagements this sits inside the development work rather than as a separate service. If you need dedicated AI consultants for a period, we can discuss availability and dedicated capacity during scoping, since it depends on the skills involved and current commitments. The main offer remains implementation.