AI Engineering & Talent
Forward-Deployed AI Engineering
Senior AI engineers working inside your organization, close enough to the business to find the opportunities and skilled enough to build them. The model suits environments where the useful work is not yet specified.
The business problem
The specification requires the expertise
Conventional delivery needs a defined scope. But knowing which problems AI can solve, and how, is exactly the expertise most organizations lack, so scoping becomes a chicken-and-egg problem. Requirements documents get written by people guessing at what is feasible, and the resulting projects build the wrong thing competently.
What we do
Embed, find, build, repeat
Engineers work alongside your teams rather than from a statement of work. They spend time with the people doing the work, identify where AI genuinely helps, prototype quickly, and take what proves out into production. Because they are inside the organization they see the constraints that never make it into a brief, and because they build, the assessment of what is feasible is grounded.
Forward-Deployed AI Engineering
Capabilities
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AI Solution Architect
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AI Engineer
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ML Engineer
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Data Engineer
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AI Product Engineer
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AI Business Analyst
Common use cases
Common use cases
- Establish where AI helps in an organization that has not started.
- Work through a backlog of candidate use cases without scoping each as a project.
- Give a business unit AI capability without waiting on a central function.
- Build capability in your own team by working alongside them.
How we deliver
How we deliver
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Scope
Agree the role, the stack, the seniority and how success will be judged.
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Select
You interview. Nobody joins the team without your agreement.
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Embed
They work in your tools, your process and your review cycle, reporting to your lead.
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Sustain
Capacity flexes with the roadmap; knowledge stays documented rather than in one head.
Technology
Technology
- TypeScript
- Python
- Go
- React
- Node.js
- Kubernetes
- GitHub Actions
- Terraform
Security & governance
Security & governance
Engineers work under your access model and your code of conduct, on your infrastructure, with the same review and approval gates as your own staff. Intellectual property in the work is yours. Where AI coding assistance is used, it passes through the same review as anything else, and the provenance of generated code is recorded.
Engagement models
Engagement models
Forward-Deployed AI Team
A cross-functional AI team works inside your organization to continuously find and deliver opportunities.
Dedicated AI Team
Long-term dedicated engineering capacity built around your stack and delivery model.
Managed AI
We operate, monitor and continuously improve production AI systems.
Why TeamExtension.ai
Senior people, not a pyramid
This model only works with engineers who can talk to a business owner in the morning and ship in the afternoon. We staff it with people who have done both, which is also why we cannot staff it in large numbers at short notice.
Selected clients
Frequently asked questions
Frequently asked questions
How is this different from a dedicated team?
How many people?
What does success look like?
How long is a typical engagement?
Related capabilities
Related capabilities
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Long-term AI engineering capacity built around your stack, your standards and your delivery model.
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AI Agents
Software that completes multi-step work inside your systems, under your access controls and your approval rules.
Learn moreAI Applications & Knowledge
Custom AI Development
Production AI applications built for your business, not configured from a template.
Learn moreDiscuss Your AI Initiative
Senior AI engineers embedded alongside your teams to find opportunities and put them into production.