Head of Artificial Intelligence

Thales
Crawley
1 year ago
Applications closed

Related Jobs

View all jobs

Head of Artificial Intelligence

Head of Artificial Intelligence (AI)

Data Scientist

Reader in Artificial Intelligence (Machine Learning, NLP, Reinforcement Learning, and AI Security)

Reader in Artificial Intelligence

Reader in Artificial Intelligence

Head of AI



Responsibilities


  • Strategic Leadership
  • Be the face of AI for Thales UK
  • Oversee the implementation of the cortAIx Factory AI and MLOPS strategy
  • Practice lead across the Data & AI job family in Thales UK
  • Design & Governance
  • Serve as the principal authority on AI design, providing expert guidance on best practices and industry standards.
  • Ensure the design of AI models, algorithms, and data architectures meets business, technical, and regulatory requirements.
  • Establish and enforce governance frameworks for AI algorithms and implementation to production.
  • Promote best practices in AI ethics, robustness, transparency, and governance.
  • Market Engagement
  • Monitor industry trends, market landscapes, and benchmarks to maintain a technical edge.
  • Identify and engage third-party collaborators to enhance the capabilities of the AI Factory team as needed
  • AI delivery
  • Work with Head of cortAIx Factory Engineering Delivery and Head of cortAIx Factory Product to enact the cortAIx mission
  • Work with the Engineering management team in the UK to derive and deliver capability improvement plans for AI
  • Line management responsibility for Data Science and AI resources in the Data and Digital Centre (DCC)
  • Work across DCC to support the planning and execution of our data and digital transformation



Required Skills


  • Experience of working in the UK Defence AI sector
  • A degree in computer science, artificial intelligence, or a related field. And / or appropriate hands-on experience of practical AI engineering
  • Extensive knowledge of Data Science and AI solutions, along with experience in data product management
  • Demonstrable knowledge and experience of MLOps practices.
  • Familiarity with data analytics, technology, and governance.
  • Excellent stakeholder and project management skills, with experience in client-facing roles.
  • Strategic mindset with the ability to balance innovation with business needs.
  • Experience in user interface design and user experience considerations.
  • Understanding of the software development lifecycle, including requirements analysis, quality assurance, design, scheduling, implementation, issue tracking, version control, and deployment.



Security Requirements

In line with Thales' Baseline Security requirements, candidates will be asked to provide evidence of identity, eligibility to work in the UK and employment and/or education history for up to three years. Some vacancies may require full Security Clearance which can require further evidence to be provided. For further details of the evidence required to apply for Baseline and Security Clearance please refer to the Defence Business Services National Security Vetting (DBS NSV) Agency.

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.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

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.