UK

United Kingdom · Technology and data · Director/VP (16-20 years)

Director, AI Solutions

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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  • Experience bandDirector/VP (16-20 years)
  • Direct reports25-100+ reports
  • Reports toVP, AI Strategy & Solutions
  • UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as Head of AI Delivery · VP of AI Engineering · Senior Director of Machine Learning

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 3 of 7 standards
ATHE Level 7 Extended Diploma in Computing ATHE Ltd · Level 7 · covers 1 of 7 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 3 of 7 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 3 of 7 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 7 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Science Foundations OTHM Level 7 Diploma in Data Science
Applications of Machine Learning and Artificial Intelligence ATHE Level 7 Extended Diploma in Computing
Artificial Intelligence NCC Education Level 5 Extended Diploma in Computing with Data Science
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)

The future skills this job leans on

AI Fluency working with AI as a thinking partner
AI Governance Fluency using AI responsibly
Frontier Fluency the next wave, beyond mainstream AI
Systems Fluency seeing the whole picture
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Your Plan Illustration

Built for Director, AI Solutions

6 units that map to this job, from the qualifications that cover it.

  1. Data Science Foundations OTHM Qualifications · covers 3 of 7 standards Level 7
  2. Applications of Machine Learning and Artificial Intelligence ATHE Ltd · covers 1 of 7 standards Level 7
  3. Artificial Intelligence NCC Education Limited · covers 3 of 7 standards Level 5
  4. Data Analytics Pearson Education Ltd · covers 3 of 7 standards Level 5
  5. Data-led Decision Making Institute of Sales Professionals · covers 1 of 7 standards Level 6
  6. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 7 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Director, AI Solutions?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Ethical AI & Responsible Governance
  • Quantum Machine Learning (Strategic Awareness)
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Director, AI Solutions plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Director of AI Solutions sets the strategy for a portfolio of AI projects and oversees how they're delivered to clients.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Cloud ML Platforms (AWS SageMaker, GCP Vertex AI, Azure ML Studio) Strategic

Leading platform selection decisions, designing enterprise-wide MLOps governance and security policies on the chosen platform, and overseeing cost optimisation strategies. You're setting the standards for how we use these.

Python ML Ecosystem (TensorFlow, PyTorch, Hugging Face) Strategic

Setting standards for library usage across your teams, evaluating emerging frameworks for their potential business impact, and driving the 'build vs. buy' decisions for core ML capabilities. You're defining the toolkit.

Data Platforms (Snowflake, Databricks, Collibra) Architect

Designing the end-to-end data flow for enterprise AI solutions, ensuring integration with data governance tools like Collibra, and influencing the broader enterprise data strategy to support AI initiatives.

Containerization & Infra (Docker, Kubernetes, AWS Lambda) Strategic

Architecting scalable, resilient MLOps infrastructure, making strategic decisions on Kubernetes vs. serverless approaches for model serving, and ensuring our deployment pipelines are robust and secure.

Collaboration Suite (Jira, Confluence, Tableau Server, Domo) Strategic

Integrating project management data with executive dashboards (e.g., Tableau Server, Domo) to provide portfolio-level visibility on AI initiatives, setting standards for documentation, and ensuring effective cross-team communication.

Demo & Viz Tools (Streamlit, Gradio, Power BI, Tableau) Strategic

Defining the standards and toolkits for solution demonstrations across the organisation to ensure a consistent, high-impact client experience, and ensuring your teams can effectively communicate complex AI results visually.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Strategic AI Initiative Approval No authority. Inform supervisor of ideas. Propose initiatives to manager. Lead proposal development, recommend to Director.
Team Hiring & Organisational Structure None. Provide input on candidate fit. Interview candidates, provide strong recommendations.
Technology Stack & Platform Selection Use approved tools. Recommend new tools for specific projects. Evaluate and propose new tools/platforms for workstreams, with Director approval.
Budget Allocation & P&L Management Manage personal expenses. Manage project-level budgets (e.g., £5K). Manage workstream budgets (e.g., £50K).

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

AI Solutions Portfolio Revenue Contribution
The direct revenue generated or influenced by the AI solutions under your remit.
Target · Exceed £5M in new or retained revenue annually.

In Q2, new client deployments of our AI-powered recommendation engine added £1.5M to the top line, contributing to a total of £6.2M for the year.

Operational Efficiency Gains from AI
Documented cost savings or efficiency improvements delivered to clients or internal operations through your team's AI solutions.
Target · Deliver >£2M in documented savings or efficiency gains annually.

An AI-driven fraud detection system implemented for a client reduced their manual review costs by £750K per quarter, hitting £3M in annualised savings.

AI Capability Uplift & Reusability
The number of reusable AI solution accelerators or frameworks developed and deployed, and their impact on future development time.
Target · Develop and deploy 2-3 significant reusable assets per year, reducing average project delivery time by 25%.

The new MLOps framework reduced the average time to deploy a new model from 6 weeks to 3 weeks for three subsequent projects.

Team Retention & Development
Retaining top talent within your teams and ensuring their professional growth.
Target · Maintain >85% voluntary retention rate, with at least 20% of team members advancing to the next level annually.

Despite a competitive market, your team's retention was 90% last year, and 15 specialists progressed to Senior roles.

Strategic Influence & Vision
How effectively you shape the AI strategy for the business unit and align it with overall company goals.
  • Being proactively invited to C-suite strategy sessions
  • your proposals for new AI initiatives consistently gain executive sponsorship
  • your team's work is regularly cited in investor presentations as a key differentiator.
Client & Stakeholder Trust
The level of confidence and reliance key internal and external stakeholders place in your team's ability to deliver complex AI solutions.
  • Clients specifically ask for your team on new, high-stakes projects
  • other Directors seek your input on their strategic roadmaps
  • you're seen as the go-to person for 'what's possible with AI' discussions.
Innovation & Market Leadership
Your contribution to positioning the company as an innovator in AI solutions within the industry.
  • Your teams are regularly experimenting with and integrating new AI techniques (e.g., LLMs, Generative AI)
  • your work leads to industry awards or recognition
  • you're asked to speak at industry conferences about our AI approach.
Organisational Health & Culture
Fostering a high-performing, collaborative, and inclusive culture within your teams and across the broader Technical_roles department.
  • High engagement scores in team surveys
  • strong cross-functional collaboration on complex projects
  • your teams are actively contributing to knowledge sharing and community building
  • a visible commitment to diversity and inclusion.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building High-Impact AI Capabilities

You'll be spending your days defining what our AI solutions look like in 2-3 years, making sure we have the right people and tech to get there. This means shaping the team, setting technical direction, and seeing your vision become a reality that genuinely changes how our clients operate.

You'll lead the charge on developing our next-gen generative AI platform, seeing it evolve from a strategic concept to a deployed product used by hundreds of clients.

Driving Business Transformation & P&L Growth

Your focus will be on the bottom line. You'll be constantly looking for opportunities where AI can unlock new revenue streams, drastically cut costs, or create a significant competitive advantage. This means working closely with sales, product, and finance to identify and prioritise the most impactful initiatives.

You'll oversee the launch of an AI-powered service that generates £3M in new annual recurring revenue within its first year.

Mentoring & Developing Future AI Leaders

A big part of your role is growing your people. You'll be spending time coaching your managers, identifying high-potential individuals, and creating career pathways for your teams. You'll get satisfaction from seeing your team members succeed and take on bigger challenges.

You'll establish a leadership development programme for your Lead and Senior Specialists, helping them prepare for management roles.

What frustrates people
  • Getting executive buy-in for long-term AI investments when short-term pressures are high
  • Dealing with legacy systems and data silos that hinder AI deployment
  • Managing the expectations of non-technical stakeholders who think AI is magic
  • Recruiting and retaining top-tier AI talent in a highly competitive market
  • The slow pace of change in large organisations when you're trying to innovate quickly
What this role does not give you
  • Daily coding opportunities
  • A predictable, unchanging technical roadmap
  • Low-pressure, low-stakes work
  • Complete autonomy without strategic alignment
  • A small, intimate team environment

8Who you work with

This role directly shapes the AI capabilities of a business unit, influencing its market position, revenue streams, and operational effectiveness. Your decisions will affect millions in P&L and the careers of dozens of technical professionals.

Inside the business
  • C-Suite (CTO, CEO, CPO)
  • Heads of Product Management
  • Sales & Marketing Leadership
  • Finance Director
  • Legal & Compliance Teams
  • Other Business Unit Directors
Outside the business
  • Strategic Client Executives
  • Key Technology Vendors
  • Industry Analysts
  • Potential Acquisition Targets
  • Regulatory Bodies

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven track record of leading and scaling large technical teams (25+ people) in an AI/ML context.
  • Extensive experience (16+ years) in designing, building, and deploying complex AI solutions from PoC to production at an enterprise level.
  • Demonstrable experience managing significant P&L (£2M+) and budgets for technical departments or product portfolios.
  • A deep understanding of MLOps principles and practices, with experience in establishing governance and best practices.
  • Exceptional executive communication skills, with a history of presenting to C-suite, board members, and major clients.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Prompt Engineering & LLM Orchestration

Generative AI is rapidly becoming a core component of many solutions. Your teams will need to move beyond basic prompting to orchestrate complex LLM workflows, integrate them with proprietary data (RAG), and ensure reliable, hallucination-free outputs at scale.

Multi-Agent LLM Systems · Advanced RAG Architectures · LLM Evaluation & Guardrails · Fine-tuning & Custom Model Development · Cost Optimisation for LLM Inference

  • This quarter: Ensure all your teams have access to and are actively using advanced AI coding assistants and LLM APIs for daily tasks.
  • Next 6 months: Mandate that new projects explore LLM integration where appropriate, and allocate dedicated R&D time.
  • Within 12 months: Establish a centre of excellence or a dedicated working group focused on LLM best practices, prompt engineering, and safety.
  • Regularly review the market for new LLM providers and open-source models that could offer a competitive advantage.

Quick win: Challenge your teams to automate one significant internal reporting or documentation task using LLMs within the next month.

11Staying current once you are in

What people here do to keep up
  • Regularly attending and speaking at major AI/ML conferences (e.g., NeurIPS, ICML, KDD, Re:Invent).
  • Participating in executive leadership programmes focused on technology and innovation.
  • Engaging with industry consortia or working groups on AI standards and ethics.
  • Mentoring emerging leaders within the organisation and externally.
  • Publishing thought leadership pieces on AI strategy, MLOps, or specific industry applications.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Ethical AI & Responsible Governance

Regulators are getting serious about AI ethics, and clients are demanding transparency and fairness. A single AI bias incident can cause massive reputational and financial damage. This isn't just a technical problem; it's a leadership challenge.

  • AI Fairness & Bias Detection
  • Explainable AI (XAI) for Decision-Making
  • AI Auditability & Traceability
  • Privacy-Preserving AI
  • Human-Centred AI Design

Quantum Machine Learning (Strategic Awareness)

While still nascent, quantum computing has the potential to revolutionise certain AI tasks (e.g., optimisation, complex pattern recognition) far beyond what classical computers can do. As a Director, you need to understand its potential and limitations to inform long-term R&D investments and strategic partnerships.

  • Quantum Computing Fundamentals
  • Quantum Algorithms for ML
  • Hybrid Quantum-Classical Approaches
  • Quantum Machine Learning Libraries
  • Strategic Implications & Use Cases

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Enterprise AI Solution Architecture
  • MLOps Strategy & Governance
  • Proof of Concept to Production (Portfolio Management)
  • Business-to-Technical Translation (Executive Level)
  • Model Evaluation & Selection (Strategic Alignment)
  • AI Use Case Discovery & Prioritisation (Market & Business Unit)

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    From Principal AI Solutions Specialist

    3-5 years as a Principal

    Skills to master

    • Moving from deep technical leadership to broader team and portfolio management, strategic decision-making, and executive communication.

    You're ready to move on when

    • Consistently delivering highly complex, impactful AI solutions
    • Mentoring multiple Senior/Lead Specialists
    • Influencing cross-functional strategy
    • Demonstrating strong client relationship skills at a senior level
  2. 2

    From Head of AI Engineering / MLOps

    4-6 years in a similar leadership role

    Skills to master

    • Expanding from an engineering focus to include broader business strategy, P&L management, and client engagement.

    You're ready to move on when

    • Successfully built and scaled MLOps platforms
    • Managed large engineering teams
    • Demonstrated strong architectural decision-making
    • Proven ability to translate technical capabilities into business value
  3. 3

    From Senior AI Product Lead (with strong technical background)

    5-7 years in senior product leadership

    Skills to master

    • Deepening technical understanding of AI implementation, leading large technical delivery teams, and managing the operational aspects of AI solutions.

    You're ready to move on when

    • Successfully launched multiple AI-powered products
    • Demonstrated strong understanding of AI capabilities and limitations
    • Effectively managed product P&L
    • Proven ability to work closely with engineering teams

15Where this role leads

The long view: This role can lead to positions such as Chief Technology Officer or Chief Product Officer, overseeing technology or product strategy across a whole organisation.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Director, AI Solutions is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • VP, AI Strategy & Solutions (L7)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Science Foundations, worked against Director, AI Solutions.

Data Science Foundations Level 7

Applied to your work in Director, AI Solutions

1. To enable the learner to define the scope and landscape of Data Science and differentiate the roles of Data Scientists from other IT professionals. 2. To enable the learner to evaluate key topics within Data Science, including data administration, governance, and big data sources. 3. To enable the learner to describe the architecture and core elements of Apache Hadoop. 4. To enable the learner to analyse the advantages and disadvantages of utilising Artificial Intelligence techniques in a business context. 5. To enable the learner to critically analyse the impact of Big Data on digital transformation within organisations and its effects on users. 6. To enable the learner to review strategies for ensuring data compliance and explain the responsibilities and challenges faced by data specialists.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

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See Your Progress Grow Illustration
Director, AI Solutions
  • Enterprise AI Solution Architecture
  • MLOps Strategy & Governance
  • Proof of Concept to Production (Portfolio Management)
  • Business-to-Technical Translation (Executive Level)
  • Model Evaluation & Selection (Strategic Alignment)
  • AI Use Case Discovery & Prioritisation (Market & Business Unit)
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Director, AI Solutions is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. VP, AI Strategy & Solutions (L7)

    3-5 years in the Director role

    From business unit leadership to enterprise-wide strategic leadership.

    • Defining company-wide AI policy and ethical frameworks
    • Driving strategic partnerships and ecosystem development
    • Influencing industry standards and regulatory bodies
    • Managing multi-million-pound P&L across the entire enterprise AI portfolio
Working with AI on the job

Working with AI

Where AI is starting to help

As a Director, your time is gold. You're constantly juggling strategic planning, team leadership, client engagements, and operational oversight. What if you could offload some of the heavy lifting to AI, freeing you up for truly impactful, high-level work?

We're not talking about AI writing your code (though your teams will use it for that). We're talking about AI as your strategic co-pilot, helping you synthesise market intelligence, analyse portfolio performance, and even draft those tough board-level communications. This isn't just about efficiency; it's about giving you superpowers to lead more effectively.

Strategic Portfolio Analysis with AI

Use AI to automatically analyse performance data across all your AI solutions, identifying trends, risks, and opportunities. Get instant summaries of project health, budget burn rates, and client satisfaction, allowing you to make data-driven decisions faster.

Executive Communication Drafts

Leverage generative AI to create first drafts of board reports, investor updates, strategic proposals, and even tricky internal communications. Provide a few key points, and get a polished, professional draft that saves you hours of writing and editing.

Market Intelligence & Competitor Insights

AI can continuously scan industry news, analyst reports, and competitor announcements, summarising key developments and highlighting potential impacts on your AI strategy. Stay ahead of the curve without drowning in information.

Team Performance & Skill Gap Analysis

Use AI-powered analytics to identify skill gaps across your large team, recommend personalised learning paths, and even predict potential attrition risks. This helps you proactively manage talent and build a stronger, more capable workforce.

Common questions

Common questions

How do you become a Director, AI Solutions?

Common routes in include From Principal AI Solutions Specialist (3-5 years as a Principal), From Head of AI Engineering / MLOps (4-6 years in a similar leadership role) and From Senior AI Product Lead (with strong technical background) (5-7 years in senior product leadership). Times vary with prior experience.

Where can a Director, AI Solutions progress to?

This role can lead on to VP, AI Strategy & Solutions (3-5 years in the Director role), depending on the skills you build.

What new skills matter most for a Director, AI Solutions?

Increasingly, Ethical AI & Responsible Governance and Quantum Machine Learning (Strategic Awareness). These are the skills our record of this role lists as growing.

Free tools

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Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

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17Where to go from here

Other roles at Level 7

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in technology and data

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built in this role apply across industries adopting AI, from finance and healthcare to retail and manufacturing. Some move into venture capital, backing AI start-ups, or start their own AI company.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Director, AI Solutions plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.