UK

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

Director of Computer Vision / AI

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.

Start my Director of Computer Vision / AI plan, free

Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

Keep this job description

Where should we send it?

One email: what AI is changing in this job, the new skills it asks for, where it leads, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

Upskilling a team in this role? Talk to us

  • Experience bandDirector/VP (16-20 years)
  • Direct reports25-100+ reports
  • Reports toVP of Engineering or Chief Technology Officer (CTO)
  • UK framework levelUsually a director, accountable for a division and its numbers

Also advertised as Head of Computer Vision Engineering · VP of AI Engineering (Computer Vision) · Director of Machine Vision

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 1 of 2 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 2 of 2 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 2 standards
Qualifi Level 5 Extended Diploma in Computer Science Qualifi Ltd · Level 5 · covers 1 of 2 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 2 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
Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
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)
Introduction to Artificial Intelligence Qualifi Level 5 Extended Diploma in Computer Science

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Start my Director of Computer Vision / AI plan, free
Your Plan Illustration

Built for Director of Computer Vision / AI

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

  1. Data Science Foundations OTHM Qualifications · covers 1 of 2 standards Level 7
  2. Introduction to Data Science and Big Data NCC Education Limited · covers 2 of 2 standards Level 5
  3. Data-led Decision Making Institute of Sales Professionals · covers 1 of 2 standards Level 6
  4. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 2 standards Level 5
  5. Introduction to Artificial Intelligence Qualifi Ltd · covers 1 of 2 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 of Computer Vision / AI?

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

  • AI Governance & Responsible AI Leadership
  • Generative AI for Synthetic Data & Content Creation
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 of Computer Vision / AI 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.

Start my Director of Computer Vision / AI plan, free Ready to pay? Subscribe for £70 a month

3What this role really is

This role leads computer vision strategy, deciding how visual AI is used to solve business problems. It means building capability, leading multiple teams, and setting a technical roadmap for computer vision that meets market and customer needs.

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) Strategic

You'll be making decisions about which cloud platforms to standardise on, negotiating enterprise agreements, and overseeing the cost optimisation strategies for our entire cloud ML infrastructure.

Containerisation & Orchestration (Docker, Kubernetes) Architect

You'll dictate the strategy for containerisation and Kubernetes deployment for all ML workloads, ensuring security, scalability, and efficient resource allocation across the organisation.

Experiment Tracking & MLOps Tools (MLflow, Weights & Biases, Kubeflow) Strategic

You'll be responsible for selecting and integrating enterprise-grade MLOps platforms, ensuring consistent experiment tracking, model registry, and deployment pipelines across all computer vision teams.

Data Annotation Platforms (Labelbox, Scale AI) Strategic

You'll select and manage relationships with strategic data annotation vendors, developing long-term strategies for data acquisition, quality control, and cost optimisation.

Project Management & Collaboration Tools (Jira, Confluence, Asana) Advanced

You'll oversee the programme management of multiple computer vision initiatives, ensuring clear communication, tracking progress, and removing blockers for your managers and their teams.

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
Computer Vision Strategy & Roadmap N/A N/A N/A
Budget Allocation (CV Function) N/A N/A N/A
Organisational Design & Hiring N/A N/A N/A
Major Technology/Platform Selection N/A N/A N/A
Ethical AI & Governance Policies N/A N/A N/A

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.

Revenue/Cost Savings from CV Solutions
The direct financial impact of computer vision products or internal automation tools deployed under your leadership.
Target · Generate £2M+ in new revenue or £1M+ in cost savings annually.

In Q4, a new CV-powered quality control system reduced material waste by 15%, saving £300K, and a new product feature drove £500K in subscription upgrades.

R&D Investment ROI
The return on investment for the R&D budget allocated to computer vision, measured by successful product launches, patent filings, or significant internal efficiency gains.
Target · Achieve a 3x return on R&D spend within 24 months for major initiatives.

An £800K investment in 3D vision research led to a new product line projected to generate £2.5M in its first year, representing a 3.1x ROI.

Talent Retention & Development
How well we retain our top computer vision talent and grow their capabilities, measured by voluntary attrition rates and internal promotions.
Target · Maintain voluntary attrition below 10% and achieve a 20% internal promotion rate within the CV organisation.

Our CV team saw only 8% voluntary attrition last year, and 5 key engineers were promoted to Senior or Lead roles, demonstrating strong career pathways.

Time-to-Market for New CV Capabilities
The efficiency with which new computer vision features or products move from concept to production deployment.
Target · Reduce average time-to-market for major CV features by 15% year-over-year.

We launched our new real-time object tracking module in 6 months, compared to 8 months for a similar feature last year, thanks to improved MLOps pipelines.

Strategic Influence & Board Confidence
Your ability to articulate the computer vision strategy to senior leadership and the Board, gaining their trust and securing buy-in for key initiatives.
  • Regularly invited to present at Board meetings on AI strategy
  • your proposals for major R&D investments are typically approved
  • C-suite actively seeks your input on strategic partnerships or M&A related to AI.
Organisational Health & Culture
The overall health, morale, and effectiveness of the computer vision teams under your leadership, fostering a culture of innovation, collaboration, and accountability.
  • High scores in team engagement surveys for your department
  • unsolicited positive feedback from direct reports and cross-functional peers about team dynamics
  • your teams consistently deliver high-quality work and attract top external talent.
Technical Vision & Innovation Pipeline
Your ability to foresee future technical trends in computer vision and translate them into a robust innovation pipeline that keeps us ahead of the competition.
  • Our product roadmap includes several 'first-to-market' CV features based on your strategic foresight
  • we're actively exploring and prototyping next-generation AI technologies (e.g., foundation models for vision, neuromorphic computing)
  • external recognition for our innovative AI work.
Cross-Functional Collaboration
How effectively your computer vision teams work with Product, Engineering, Sales, and other departments to deliver integrated solutions.
  • Product launches involving CV components are smooth and well-coordinated
  • other departments proactively involve your teams early in their planning cycles
  • you're seen as a trusted partner, not just a service provider, by peer VPs/Directors.

7Would you like it

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

What people enjoy
Building and Nurturing High-Performing Teams

You'll spend a significant portion of your week in 1:1s with your managers, coaching them, helping them unblock their teams, and discussing their career development. You'll be actively involved in hiring senior talent and shaping the organisational structure to maximise impact.

Spending an afternoon crafting a new career ladder for Principal Engineers, then discussing it with your managers to get their input, knowing it will help retain top talent.

Shaping Business Strategy through Technology

You'll be in strategic meetings with Product and other VPs, influencing the multi-year product roadmap and identifying new market opportunities where computer vision can provide a competitive edge. You'll be thinking about how our AI capabilities can drive the entire company forward.

Presenting a proposal to the executive team on how investing in 3D computer vision over the next two years could unlock a completely new product category worth £10M+ in annual revenue.

Driving Large-Scale Impact and Innovation

You'll get a real kick out of seeing your teams' work deployed at scale, knowing it's impacting millions of users or saving the company significant money. You'll be excited by the challenge of pushing the boundaries of what our computer vision can do, and seeing those innovations translate into tangible business results.

Celebrating with your team when a new, complex computer vision system goes live across all our production facilities, knowing it will reduce errors by 25% and save £1.5M annually.

What frustrates people
  • Navigating complex organisational politics to get buy-in for your vision.
  • Budget constraints that force tough trade-offs between innovation and immediate delivery.
  • Explaining the nuances and limitations of AI to non-technical executives and the Board.
  • Dealing with underperforming managers or difficult team dynamics.
  • The constant tension between long-term strategic R&D and short-term business demands.
  • Recruiting and retaining top-tier computer vision talent in a highly competitive market.
What this role does not give you
  • Daily hands-on coding or model training (this is for your teams now).
  • A predictable, unchanging strategic roadmap (it's always evolving).
  • Guaranteed success for every initiative (some will fail, and you'll own that).
  • Isolation from organisational politics (you're at the heart of it).

8Who you work with

This role directly shapes the technical capabilities and strategic direction of our computer vision efforts, influencing multi-year product roadmaps and R&D investments. Your decisions will impact our market competitiveness, revenue generation, operational efficiency, and our reputation as an innovator. You'll be accountable for delivering tangible business value through AI, managing substantial budgets (typically £2M-£10M+), and building a high-performing, resilient team.

Inside the business
  • VP of Product Management (for product roadmap alignment)
  • VP of Engineering (for overall technical strategy and resource allocation)
  • CFO and Finance Leadership (for budget approvals and ROI reporting)
  • Head of Sales and Marketing (for understanding market needs and product positioning)
  • Legal and Compliance (for ethical AI and data privacy guidelines)
  • Other Directors/VPs within the business unit (for cross-functional collaboration)
Outside the business
  • Key Technology Partners (e.g., cloud providers, hardware vendors)
  • Industry Analysts and Press (as a company representative)
  • Academic Research Institutions (for potential collaborations)
  • Major Customers (for understanding their long-term needs and feedback)
  • Recruitment Agencies (for talent acquisition strategy)

9What you need before you start

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

  • Proven track record of building and leading large (25+ person) computer vision or AI engineering teams, including managing managers.
  • Extensive experience (16+ years) in the full lifecycle of computer vision product development, from research to large-scale production deployment.
  • Demonstrable experience managing significant budgets (£2M+ P&L responsibility) and delivering measurable business impact through technology.
  • Deep technical expertise in computer vision and deep learning, with a strong understanding of MLOps and cloud-native AI architectures.
  • Exceptional strategic thinking, communication, and influence skills, with experience presenting to C-suite and Board-level stakeholders.
  • A history of fostering a strong engineering culture and developing technical talent.

10What to practise next

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

Edge AI & Efficient Model Deployment at Scale

The demand for real-time, on-device computer vision is growing rapidly (e.g., smart cameras, autonomous systems). You'll need to lead the strategy for optimising models for resource-constrained environments and deploying them reliably across thousands, if not millions, of devices.

Model Quantisation & Pruning · Hardware Acceleration (e.g., NPUs, TPUs, GPUs on Edge) · Federated Learning & On-Device Training · Robustness to Real-World Conditions · Over-the-Air (OTA) Updates for Edge Models

  • This month: Review our current edge deployment strategy. Where are the bottlenecks? What are the biggest cost drivers?
  • Next quarter: Engage with hardware vendors to understand the roadmap for next-generation edge AI chips and their implications for our products.
  • Month 3-6: Fund a proof-of-concept project for federated learning or on-device model adaptation for a specific use case.
  • Month 6-12: Develop a comprehensive strategy for model optimisation and secure OTA updates across our entire edge device fleet.

Quick win: Identify one existing cloud-deployed model that could benefit from edge deployment and initiate a project to explore its feasibility and potential cost savings.

Foundation Models & Large Multi-Modal Models (LMMs)

Foundation models (like CLIP, DINO, Segment Anything) and LMMs are changing how we approach computer vision, allowing for more generalisable models and zero/few-shot learning. You'll need to lead the charge on how we integrate these powerful new paradigms into our strategy, identifying where they offer significant advantages and where they're overkill.

Zero-Shot & Few-Shot Learning · Prompting & Fine-tuning LMMs · Model Compression & Efficiency for LMMs · Data Efficiency & Active Learning with FMs · Ethical Implications of General-Purpose AI

  • This month: Dedicate time to understanding the latest research papers and industry applications of LMMs. Have your managers brief you on key developments.
  • Next quarter: Sponsor a hackathon or internal competition for teams to explore how foundation models could solve existing problems or unlock new features.
  • Month 3-6: Develop a strategy for integrating foundation models into our core computer vision platform, identifying key areas for investment.
  • Month 6-12: Establish partnerships with leading research institutions or companies developing next-generation foundation models.

Quick win: Identify one current computer vision task that requires extensive labelled data and explore if a pre-trained foundation model can achieve comparable performance with significantly less data.

11Staying current once you are in

What people here do to keep up
  • Regularly attend and speak at leading computer vision and AI conferences (e.g., CVPR, ICCV, NeurIPS, AAAI) to stay abreast of cutting-edge research and build your professional network.
  • Participate in executive leadership programmes focused on technology strategy, change management, or organisational behaviour.
  • Engage with industry consortiums or standards bodies related to AI, robotics, or your specific industry vertical.
  • Mentor emerging leaders and high-potential individual contributors within and outside your organisation.
  • Publish thought leadership articles or whitepapers on strategic computer vision topics, positioning yourself and the company as an industry leader.

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.

AI Governance & Responsible AI Leadership

With increasing regulatory scrutiny (like the EU AI Act) and growing public awareness of AI's societal impact, leading with responsible AI principles isn't optional—it's a business imperative. Getting this wrong can lead to huge fines, reputational damage, and loss of customer trust. Frankly, it's a board-level concern now.

  • AI Risk Management Frameworks
  • Explainable AI (XAI) for Transparency
  • Data Lineage & Auditability
  • Fairness & Bias Detection/Mitigation
  • AI Policy & Ethics Committees

Generative AI for Synthetic Data & Content Creation

Generative AI, especially for vision, is exploding. It's not just for pretty pictures; it's a game-changer for synthetic data generation (reducing annotation costs and improving model robustness), rapid prototyping, and even creating new product experiences. If we don't master this, we'll be left behind in data efficiency and content innovation.

  • Diffusion Models & GANs for Image Synthesis
  • Synthetic Data Generation for Training
  • Prompt Engineering for Visual AI
  • Ethical Considerations of Generative AI
  • Multi-modal Generative Models

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Deep Learning Architectures (Strategic Understanding)
  • MLOps & Production AI Systems (Architectural Oversight)
  • 3D Computer Vision & Robotics (Strategic Application)
  • Data-Centric AI Methodologies (Organisational Implementation)
  • Ethical AI & Bias Mitigation (Governance & Policy)

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

    Principal Computer Vision Engineer

    3-5 years as Principal

    Skills to master

    • Deep technical expertise, architectural design for complex systems, strong influence without direct authority, mentorship of senior ICs, strategic technical problem-solving across multiple projects.

    You're ready to move on when

    • Successfully architected and delivered several large-scale, impactful computer vision systems.
    • Recognised as a company-wide expert and go-to person for complex technical challenges.
    • Consistently provides technical leadership and guidance to multiple teams.
    • Demonstrates strong communication skills with executive stakeholders on technical strategy.
  2. 2

    Computer Vision Engineering Manager (managing multiple teams)

    4-7 years as Manager (including managing managers)

    Skills to master

    • People leadership, team building, performance management, budget oversight for multiple teams, cross-functional programme management, strategic planning for a larger department.

    You're ready to move on when

    • Consistently built and retained high-performing computer vision teams.
    • Successfully managed multiple engineering managers and their respective teams.
    • Demonstrated ability to deliver complex programmes on time and within budget.
    • Proven ability to resolve inter-team conflicts and foster a collaborative environment.
  3. 3

    Head of AI Research (from an academic or research lab background)

    5-8 years in a research leadership role

    Skills to master

    • Translating cutting-edge research into practical applications, building research teams, securing grants/funding, strong publication record, strategic vision for future technologies.

    You're ready to move on when

    • Led a significant AI research group with demonstrable real-world impact.
    • Proven ability to bridge the gap between pure research and product development.
    • Strong network within the academic and industrial AI research community.
    • Demonstrates strategic thinking beyond pure scientific discovery, focusing on business value.

15Where this role leads

The long view: This work can lead to a Chief Technology Officer role, a Chief Product Officer role, or founding an AI startup.

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 of Computer Vision / AI is actually changing.

Where it leads

Roles this leads to

Also named as a next step, with no page in the catalogue yet:

  • VP of Engineering (with AI/CV focus)

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 of Computer Vision / AI.

Data Science Foundations Level 7

Applied to your work in Director of Computer Vision / AI

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.

Start my Director of Computer Vision / AI plan, free
See Your Progress Grow Illustration
Director of Computer Vision / AI
  • Deep Learning Architectures (Strategic Understanding)
  • MLOps & Production AI Systems (Architectural Oversight)
  • 3D Computer Vision & Robotics (Strategic Application)
  • Data-Centric AI Methodologies (Organisational Implementation)
  • Ethical AI & Bias Mitigation (Governance & Policy)
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 of Computer Vision / AI is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. VP of Engineering (with AI/CV focus)

    3-5 years in Director role

    From L6 to L7 (Executive Leadership)

    • Holistic software development lifecycle management across diverse tech stacks.
    • Strategic vendor management for enterprise software and infrastructure.
    • Driving cultural transformation across a much larger engineering organisation.
    • Global team management and distributed development strategies.

  2. Chief AI Officer (CAIO)

    5-7 years in Director role

    From L6 to L7 (C-Suite Executive)

    • Expertise in other AI domains (NLP, Reinforcement Learning, Generative AI beyond vision).
    • Developing and managing AI partnerships and ecosystems at an enterprise level.
    • Leading AI research and development across multiple business units.
    • Defining company-wide data strategy to support all AI initiatives.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, at the Director level, your time is precious. You're not coding models anymore, but you're drowning in strategic documents, market analyses, budget reviews, and team performance reports. The good news? AI isn't just for engineers; it's a powerful co-pilot for leaders too. We're integrating cutting-edge AI tools to help you reclaim your time and sharpen your strategic edge.

Imagine having an intelligent assistant that can summarise market trends, draft strategic proposals, or even help you prepare for tough board meetings. That's the reality we're building. Our AI productivity hub isn't just a nice-to-have; it's designed to give you back precious hours, allowing you to focus on what truly matters: setting vision, leading your teams, and driving business growth.

Strategic Document Drafting

Use LLMs to draft initial versions of multi-year computer vision strategies, market analysis reports, or competitive landscape overviews. Provide key inputs and let AI generate a structured, comprehensive document for you to refine. It's like having a team of junior strategists working at lightning speed.

Performance Review & Feedback Generation

Feed in bullet points about a manager's performance, and AI can help you draft structured, constructive performance reviews and development plans. It ensures consistency, saves you hours of writing, and helps you focus on the substance of the feedback rather than the phrasing.

Board Presentation & Q&A Prep

Upload your presentation deck and ask an AI to anticipate tough questions from the Board, suggesting data-driven answers and potential counter-arguments. It's like having a sparring partner to sharpen your messaging and ensure you're ready for anything. You'll walk into that boardroom with more confidence, honestly.

Market & Technology Trend Analysis

Point an AI at a collection of industry reports, academic papers, and competitor announcements. Ask it to summarise key emerging computer vision technologies, identify market shifts, and highlight potential threats or opportunities for our business. Get insights in minutes, not days.

Common questions

Common questions

How do you become a Director of Computer Vision / AI?

Common routes in include Principal Computer Vision Engineer (3-5 years as Principal), Computer Vision Engineering Manager (managing multiple teams) (4-7 years as Manager (including managing managers)) and Head of AI Research (from an academic or research lab background) (5-8 years in a research leadership role). Times vary with prior experience.

Where can a Director of Computer Vision / AI progress to?

This role can lead on to VP of Engineering (with AI/CV focus) (3-5 years in Director role) and Chief AI Officer (CAIO) (5-7 years in Director role), depending on the skills you build.

What new skills matter most for a Director of Computer Vision / AI?

Increasingly, AI Governance & Responsible AI Leadership and Generative AI for Synthetic Data & Content Creation. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

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

Or try another one

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 involved in this work apply across industries investing in visual AI, including automotive, healthcare, retail, manufacturing and defence. Building and scaling AI teams, setting strategy and driving business impact stay much the same, even as the applications differ.

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 of Computer Vision / AI 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.