Senior capability, inside your team.In the building — not at the end of a statement of work.
For organisations that need the expertise in the building rather than delivered at arm's length. A fixed monthly commitment, working in your tools, in your stand-ups, against your roadmap — and deliberately raising the standard of what your own team can build without us.
Three ways to embed.
Each is a named individual with a defined commitment, not a pool of interchangeable resource.
Fractional AI Engineer
An LLM engineer embedded in your team, building and maintaining your AI systems alongside your existing developers. Reviews their code, sets the standards, and leaves the team more capable than they found it. The measure of success is that you need less of us over time, not more.
- Architecture & hands-on build
- Code review & standards
- Upskilling your engineers
- In your tools and stand-ups
Forward Deployed LLM Engineer
Our most senior engagement. An engineer who sits with your operators, watches the actual work, and builds against what they observe rather than what a specification claims. Most of the value is in the gap between those two things.
- On-site discovery & build
- Direct operator feedback loop
- Documented handover
- Senior, named, single point of contact
Fractional CMO
Marketing leadership for the AI era — owning brand, discovery and the content systems that generate demand, with the engineering capability to automate them rather than just recommend it. Senior content and audience leadership inside Google and Adobe; delivery for Microsoft.
- AI brand & positioning
- SEO and GEO strategy
- Owned-channel growth
- Board-level reporting
What a fractional engagement looks like.
Fixed monthly commitment, reviewed quarterly. No minimum term beyond the first quarter, because an embedded engagement that is not working should be endable.
- A named individual, introduced before you commit
- An agreed number of days per month, in your calendar
- Working in your repository, your tracker and your stand-ups
- Against your roadmap, not a parallel SimpleAI workstream
- Code review and standards-setting as an explicit part of the role
- Quarterly review of whether the commitment is still the right size
- Documented handover if and when the engagement ends
- No lock-in: the work is yours throughout, not on completion
Common questions.
How is this different from hiring a contractor?
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Scope and accountability. A contractor delivers a defined piece of work; a fractional engineer owns a capability — the architecture, the standards, and whether your own team is getting better. It also comes with the rest of the firm behind it when a specialism is needed.
What happened to Hire AI Workers?
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It has been retired as a brand. The same offer — senior capability embedded rather than delivered at arm's length — is now Fractional AI, described in language that matches the organisations we work with.
Can a fractional engagement turn into a build?
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Frequently. An embedded engineer often surfaces the thing genuinely worth building, having watched the actual work rather than read a specification. When that happens it moves onto a normal fixed scope and price.
We can help.
Tell us what's hard, expensive, or taking too long — and we will help you identify, optimise and deploy AI for innovation, efficiency and growth.