Director of Generative AI | Remote

Milton, Cambridgeshire

9 months ago

Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Product Data Scientist

Junior Data Scientist

Principal Data Scientist

Director of Software Engineering: Observability & AIOps

Head of Data Science -Telematics

Director of Generative AI | Fully remote | Great Comp

A pioneering technology organization is seeking a visionary Director of Generative AI Engineering. In this key leadership position, you will spearhead the integration of generative AI into sophisticated, science-based products and services. If you’re passionate about pushing the boundaries of innovation and eager to lead a talented, cross-disciplinary team, this role offers an exceptional opportunity to shape the future of AI-driven solutions.

Key Responsibilities
Strategic Innovation: Drive the company’s AI roadmap, adopting cutting-edge technologies and methodologies to enhance product capabilities.
Technical Leadership: Architect, develop, and deploy scalable generative AI solutions, integrating them with existing scientific and engineering platforms.
Cross-Functional Collaboration: Partner with diverse teams, from research and operations to finance and commercial, to ensure seamless AI adoption across the organization.
Team & Culture Building: Mentor and develop internal AI expertise, fostering an environment of continuous learning and scientific rigor.
Thought Leadership: Stay ahead of industry trends and serve as a visible advocate for generative AI, representing the company in external forums and shaping broader strategic initiatives.
Qualifications & Experience
Deep AI Expertise: Proven track record in designing and implementing generative AI and related ML technologies.
Scientific Rigor: Comfortable working with data-intensive, science-focused applications in fields like chemistry, process engineering, or similar domains.
Leadership & Collaboration: Demonstrated success leading interdisciplinary teams and aligning AI strategies with broader business goals.
Technical Background: Graduate degree (Ph.D. preferred) in AI, Machine Learning, Computer Science, Chemical Engineering, or a closely related field.
Innovation & Execution: Skilled in rapid prototyping and scalable deployment of AI solutions, balancing agility with robust scientific methodology.
Why Join?
High Impact: Shape mission-critical AI initiatives that redefine how complex scientific and engineering challenges are solved.
Innovative Culture: Work in an environment that values research excellence, collaboration, and continuous improvement.
Career Growth: Lead the charge on emerging AI technologies, positioning yourself at the forefront of innovation in a fast-evolving industry

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

Industry Insights

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

Jan 18, 2026

Jobs Careers

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.

Jan 13, 2026

Jobs

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.

Jan 5, 2026

Education Jobs

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.