AI Transformation Manager

AI Innovation Manager £700-£750 per day - Inside IR35 6-month contract | London / Hybrid PCR Digital is working with a large global technology business that is building a small, highly autonomous AI & Automation…

Inside IR35 Hybrid Business Support
Pay rate £700 – £750/day
Contract type Contract
Posted 7 September 2026

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About this contract

AI Innovation Manager

£700-£750 per day - Inside IR35

6-month contract | London / Hybrid

PCR Digital is working with a large global technology business that is building a small, highly autonomous AI & Automation Innovation Lab within its commercial organisation.

We're looking for an AI Innovation Manager to lead the Lab alongside a hands-on AI Innovation Specialist.

This isn't a traditional AI strategy role, and it isn't a pure engineering position. You'll work directly with Commercial and Operations teams to identify high-value opportunities, turn them into working AI and automation prototypes, test them with real users and quickly establish what is worth taking into full delivery.

You'll need the commercial and consulting skills to find and frame the right problems, but you'll also be expected to build and experiment yourself.

What you'll be doing

Identify AI and automation opportunities across Commercial, Operations and other business functions.
Build and manage a pipeline of prototypes and pilots, prioritised around measurable business value.
Turn ambiguous business problems into practical AI and automation use cases.
Build hands-on alongside an AI Innovation Specialist, rather than simply handing requirements to an engineering team.
Rapidly prototype, test and iterate solutions with real users.
Define success measures for pilots across revenue, cost, risk, efficiency and speed.
Explore emerging AI tools, agent frameworks and automation platforms outside the existing technology stack.
Compare new technologies against existing platforms across capability, cost, security and integration effort.
Present findings, recommendations and business cases to senior stakeholders.
Stop experiments quickly where the evidence doesn't support further investment, and move successful pilots towards wider delivery.

What we're looking for

You'll need demonstrable experience building AI-enabled solutions, prototypes, agents or automations, combined with the ability to work directly with senior business stakeholders.

We're particularly interested in people who have worked within consulting, technology or similarly fast-moving environments and are comfortable operating with a high degree of autonomy.

You'll ideally bring:

Hands-on experience with Generative AI, LLMs, AI agents and/or intelligent automation.
Experience rapidly taking ideas from discovery through prototype, pilot and evaluation.
Strong understanding of the capabilities, limitations and risks of LLM-based solutions.
Commercial awareness and the ability to quantify an opportunity through revenue, cost, risk or efficiency.
Strong stakeholder engagement across non-technical Commercial and Operations teams.
Structured problem-solving and consulting skills.
Confidence presenting findings and recommendations to senior stakeholders.
The curiosity to continually explore new AI tools and technologies rather than being tied to a single platform.
The ability to work independently and make sensible decisions around value, risk, complexity and speed.

Technology

You don't need to tick every box or be tied to a particular technology stack.

Relevant experience could include:

Generative AI & Agents: LLMs, agentic AI, AI agent frameworks, AI coding tools
Cloud & Data: AWS, data platforms, Snowflake
Enterprise Platforms: Salesforce, Microsoft ecosystem
Automation: workflow automation, intelligent automation and low-code/no-code platforms

Experience within payments, fintech or financial services would be useful but isn't essential.

The environment

This is a small innovation team designed to move quickly.

You'll have considerable freedom to explore new technology, build working solutions and test ideas directly with the people who would use them. The focus is on evidence and outcomes rather than lengthy strategy documents.

The initial objective is to create a strong pipeline of AI and automation opportunities, prototype and test a number of high-value pilots, and identify which technologies and solutions should progress into wider enterprise delivery

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