AI Transformation Lead

London
1 year ago
Applications closed

Related Jobs

View all jobs

AI Transformation Consultant: GenAI & MLOps at Scale

Head of Machine Learning

Head of Artificial Intelligence Impact

ML Engineer / Data Scientist, Applied AI

Consultant, Data Science and Business Analyst, AI & Data, Defence & Security

Lead Data Scientist

Job Title:

Senior AI Transformation Leader

Location:

London Remote / Flexible, with occasional travel as needed

About the Role:

Our client, a leading strategy and innovation consulting firm, is seeking a Senior AI Transformation Leader to join their AI Transformation practice. This role is designed for a visionary leader with deep expertise in AI strategy, digital transformation, and executive collaboration. The successful candidate will play a key role in delivering AI initiatives that drive significant business impact, aligning AI strategies with broader organisational goals to enable innovation and sustainable growth.

Key Responsibilities:

AI Strategy Development: Lead the design and execution of AI strategies that address complex business challenges and empower clients with data-driven insights.
Leadership of Cross-functional Projects: Oversee multi-disciplinary teams to ensure the successful integration of AI solutions, aligning projects with the client's strategic vision.
Senior Stakeholder Engagement: Collaborate closely with C-suite executives to communicate AI strategy, gain alignment, and advocate for the business impact of AI initiatives.
Thought Leadership in AI: Act as a thought leader, sharing expertise on AI trends and best practices, fostering a culture of innovation and responsible AI use within the client organisation.
Ethical and Regulatory Compliance: Ensure AI implementations adhere to ethical standards and regulatory requirements, supporting clients as they navigate responsible AI development.

Required Experience and Skills:

Extensive AI and Transformation Leadership: 15+ years in technology innovation, focusing on AI strategy, digital transformation, and executive engagement.
Strategic Vision: Proven success in defining and implementing AI strategies that drive tangible business outcomes.
Executive Relationship Management: Skilled in building and managing relationships with C-suite stakeholders, aligning AI projects with organisational objectives, and communicating complex ideas effectively.
Technical Proficiency in AI and Machine Learning: Strong understanding of AI models, frameworks, and analytics, with the ability to translate technical insights into actionable business recommendations.
Industry Recognition: Experience as a spokesperson or thought leader in AI, digital transformation, or innovation.
Education: Advanced degree in AI, Data Science, Computer Science, Business, or a related field.

Why Join?

This opportunity is ideal for an accomplished AI leader ready to work on transformative projects within a top-tier consulting environment. If you have a passion for AI innovation and strategic leadership, we would love to discuss this role with you

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.