Hiring nowAI solution delivery, consulting and architecture

AI Technical Programme Manager

Also called AI TPM

An AI Technical Programme Manager coordinates dependencies, people and release evidence across teams so AI work ships on a predictable path with quality gates met. It matters because AI delivery fails at the seams between teams.

What they do

They run the delivery programme for AI products that cut across research, engineering, data, security and customer teams. They map dependencies, sequence the work and keep a live record of risks and decisions. They chase the evidence that a release is ready: evaluation results, integration tests, safety reviews and sign-offs. They spot when a model change, a tool integration or a vendor limit will knock the plan sideways, and they raise it early. They run the cadence of planning, check-ins and release reviews, and they explain trade-offs to technical and non-technical people in plain language.

What a strong hire delivers

In the first months, a strong hire gives leadership one trusted view of what is shipping, what blocks it and who owns each decision. They set up quality gates that teams actually follow. They bring a messy cross-team dependency under control, cut surprises at release, and leave a risk and decision log people refer to without being asked.

How you can tell they are good

Ask them to walk through a programme that nearly slipped. Listen for named dependencies, the evidence they asked for, and the decisions they forced. Ask how they judge whether an AI release is ready. Strong people talk about evaluation results and risk, not just dates and status colours. They can explain the technical issues without hiding behind jargon.

Why it is hard to fill

The title is used loosely, so CVs look similar but the work differs. Many programme managers have never run AI delivery, and many AI engineers have never owned cross-team execution. The best people sit between the two, often with a background in solution architecture, consulting or systems integration. They are rarely looking, and they are often called something else.

Where to find them

Look at technical programme managers from software and platform companies, and delivery leads from systems integrators and consultancies. Solution architects who have moved into running delivery are a good source. So are engineering managers who ran integration-heavy projects. Applied AI start-ups and enterprise AI teams are the most likely places to find people already doing this.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Technical Programme Manager

  1. Tell me about an AI programme where dependencies across teams threatened delivery. What did you do?

    Strong answers name specific dependencies, how they were mapped and who owned them. They show early escalation and clear decisions. Worry if the story is about chasing updates, or if they credit everything to the team without describing their own actions.

  2. What evidence would you want before signing off an AI release?

    Look for evaluation results, regression checks, integration testing, security and safety review, and a rollback plan. They should tie gates to risk. Worry about answers that rely only on delivery dates or a verbal assurance from engineers.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are building AI products that depend on many teams working in step. We need a Technical Programme Manager to coordinate dependencies, resources and release evidence so we ship predictably and to the quality we have promised. You will work closely with engineering, research, data and security.

What you will do

  • Run delivery programmes across several teams, with clear plans, owners and milestones
  • Map and manage dependencies, including tool and protocol integrations
  • Keep a live log of risks and decisions and drive them to resolution
  • Define and enforce quality gates with the evidence needed for each release
  • Run planning, check-ins and release reviews
  • Report progress and trade-offs clearly to technical and non-technical stakeholders

What you will bring

  • Delivered a cross-team technical programme with several interdependent workstreams
  • Experience with AI or machine learning products, including how evaluation shapes release decisions
  • Can explain integration and technical risks in plain language
  • Track record of managing risk and making decisions visible
  • Background in solution architecture, consulting, systems integration or technical delivery
  • Comfortable holding a quality line under pressure

Nice to have

  • Experience with agent frameworks or tool integration protocols
  • Pre-sales or solution design experience
  • Experience in a regulated or security-sensitive setting

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Sales and solution architectureAdvancedMatch technical solutions to validated customer needs
  • Tool and protocol integrationAdvancedConnect models to external data and capabilities
  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks
  • Technical communicationWorkingExplain evidence and limitations to relevant readers

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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