AI Tech Lead

Thales Group; Reading; On-site; GBP 120,000 - 180,000; Full time

Job summary

Thales Group in Reading is seeking an experienced AI Technical Lead to steer the design, delivery and governance of enterprise AI initiatives. You will collaborate with Agile teams, define architectures for Generative AI, RAG, and ML platforms, and ensure solutions are scalable, secure and compliant.

The role requires mentoring engineers, leading POCs, and embedding responsible AI practices while coordinating with security, legal and compliance functions.

Qualifications

• Degree in Computer Science, Software Engineering, Data Science or related discipline.
• Relevant cloud certifications (Microsoft Azure preferred).
• AI, Machine Learning or Data certifications advantageous.

Responsibilities

• Lead the technical implementation of the organisation's AI strategy.
• 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.
• Design scalable AI and machine learning solutions.
• 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.
• 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.
• 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.
• 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.

Skills

Software engineering

AI solutions

Azure OpenAI

Python

APIs & microservices

Cloud-native architecture

DevOps & CI/CD

Kubernetes

MLOps

Education

CS/Software Engineering degree

Microsoft Azure certifications

AI/ML/Data certifications advantageous

Tools

LangChain

Semantic Kernel

Kubernetes

CI/CD pipelines

Job description

Location(s): Crawley or Reading or Cheadle or Bristol or Glasgow or any other Thales site in the UK

Key Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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, DevOps and CI/CD practices.

AI & Data

• Hands-on experience with: Retrieval-Augmented Generation (RAG) AI orchestration frameworks such as LangChain, Semantic Kernel or similar.
• Understanding of model evaluation methodologies.
• Knowledge of responsible AI principles.

Leadership

• Demonstrable experience leading technical teams.
• Ability to coach and mentor engineers.
• Experience influencing stakeholders at multiple organisational levels.
• Microsoft AI certifications.
• Experience implementing Microsoft 365 Copilot.
• Knowledge of Power Platform and AI Builder.
• Experience in regulated industries.
• Experience with Data Science and Machine Learning Operations (MLOps).
• Familiarity with Kubernetes and containerisation technologies.
• Experience with agentic AI and autonomous workflow solutions.

Qualifications

Degree in Computer Science, Software Engineering, Data Science or related discipline, or equivalent experience.

Relevant cloud certifications (Microsoft Azure preferred).

AI, Machine Learning or Data certifications advantageous.

Security Clearance Requirement

Due to the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires Security Clearance (SC). It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance. To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years' residence in the UK over the last 5 years may be accepted, with additional overseas checks.

About Thales

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.