AI Tech Lead

Location: Templecombe

Location:

Crawley, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services.

We are seeking an experienced and innovative AI Technical Lead to drive the design, development and deployment of AI-powered solutions across the organisation. The successful candidate will lead technical delivery of AI initiatives, establish best practices, provide technical leadership to engineering teams, and ensure AI solutions are secure, scalable, ethical and aligned to business objectives.

This role combines hands-on technical expertise with leadership, stakeholder engagement and strategic thinking to accelerate business value through artificial intelligence.

Location(s):

Crawley or Reading or Cheadle or Bristol or Glasgow or any other Thales site in the UK

Key Responsibilities:

AI Strategy & Leadership Lead the technical implementation of the organisation's AI strategy.

Evaluate emerging AI technologies and identify opportunities for adoption.

Define AI engineering standards, patterns and best practices.

Act as the technical authority for AI-related projects and programmes.

Mentor and develop engineers, architects and technical specialists.

Solution Design & Architecture Design scalable AI and machine learning solutions.

Define architecture for Generative AI, Machine Learning and Intelligent Automation platforms.

Establish patterns for integrating AI services into enterprise applications.

Ensure solutions align with enterprise architecture, security and compliance requirements.

Lead technical design reviews and architecture governance activities.

Engineering & Delivery Build and oversee development of AI-powered applications and services.

Lead proof-of-concepts, pilots and production implementations.

Collaborate with Agile delivery teams to embed AI capabilities into products and services.

Establish CI/CD pipelines and MLOps practices.

Drive technical quality, performance and operational resilience.

Generative AI & Large Language Models Design and implement solutions using Large Language Models (LLMs).Develop Retrieval-Augmented Generation (RAG) architectures.

Implement prompt engineering and AI orchestration frameworks.

Evaluate AI model performance, accuracy and cost optimisation.

Ensure effective use of Microsoft Copilot, Azure OpenAI and other enterprise AI services where appropriate.

Governance, Risk & Compliance Ensure responsible AI principles are embedded in all solutions.

Implement monitoring, auditability and model governance controls.

Assess risks relating to bias, security, privacy and ethical use of AI.Work with legal, security and compliance teams to maintain regulatory adherence.

Support AI governance boards and decision-making forums.

Stakeholder Management Engage with senior business stakeholders to understand challenges and opportunities.

Translate business requirements into technical solutions.

Present AI roadmaps, technical options and recommendations to leadership audiences.

Build strong relationships across technology, data and operational teams.

Required Skills & Experience Technical Expertise Strong software engineering background.

Experience delivering AI, machine learning or Generative AI solutions.

Knowledge of Azure AI Services, Azure OpenAI, AWS AI or Google Vertex AI.

Experience with Python and modern development frameworks.

Strong understanding of APIs, microservices and cloud-native architecture.

Experience with data platforms, databases and data engineering concepts.

Knowledge of MLOps, Dev Ops and CI/CD practices.

AI & Data Hands-on experience with:

Large Language Models (LLMs)
Prompt engineering

Retrieval-Augmented Generation (RAG)
Vector databasesAI orchestration frameworks such as Lang Chain, Semantic Kernel or similar

Understanding of model evaluation methodologies.

Knowledge of responsible AI principles.

Leadership Demonstrable experience…