AI Tech Lead
Job in
Crawley, West Sussex, RH11, England, UK
Listed on 2026-09-03
Listing for:
Jobtailor
Full Time
position Listed on 2026-09-03
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
- Lead the technical implementation of the organisation's AI strategy
- Evaluate emerging AI technologies and identify adoption opportunities
- Define AI engineering standards, patterns and best practices
- Act as technical authority for AI-related projects and programmes
- Mentor and develop engineers, architects and technical specialists
- Design scalable AI and machine learning solutions
- Define architectures 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 Large Language Model solutions and Retrieval-Augmented Generation architectures
- Implement prompt engineering and AI orchestration frameworks
- Evaluate AI model performance, accuracy and cost optimisation
- Use Microsoft Copilot, Azure OpenAI and other enterprise AI services where appropriate
- Embed responsible AI principles and implement monitoring, auditability and model governance controls
- Assess risks relating to bias, security, privacy and ethical AI use
- Work with legal, security and compliance teams to maintain regulatory adherence
- Support AI governance boards and decision-making forums
- Engage senior business stakeholders, translate requirements into technical solutions, present AI roadmaps and recommendations, and build relationships across technology, data and operational teams
- 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
- Hands‑on experience with Large Language Models (LLMs), prompt engineering, Retrieval‑Augmented Generation (RAG), vector databases, and AI orchestration frameworks such as Lang Chain or Semantic Kernel
- Understanding of model evaluation methodologies
- Knowledge of responsible AI principles
- Demonstrable experience leading technical teams
- Ability to coach and mentor engineers
- Strong technical decision‑making skills
- Experience influencing stakeholders at multiple organisational levels
- Relevant cloud certifications (Microsoft Azure preferred)
- Security Clearance (SC) required before commencing employment
- Generally, eligibility for full SC requires residence in the UK for the last 5 years; in some circumstances, 3 years' UK residence over the last 5 years may be accepted with additional overseas checks
- Degree in Computer Science, Software Engineering, Data Science or related discipline, or equivalent experience
Demonstrates expertise in leading AI strategy implementation, designing scalable AI and machine learning solutions, and establishing best practices for AI engineering. Proficient in mentoring technical teams and ensuring compliance with security and regulatory standards.
Highest-signal resume keywords- AI Strategy Implementation
- Generative AI Solutions
- Azure AI Services
- Large Language Models
- MLOps Practices
- Python
- AI Engineering Standards
- Machine Learning Solutions
- Data Engineering Concepts
- APIs
- Microservices
- Cloud‑Native Architecture
- Model Evaluation Methodologies
- Prompt Engineering
- Retrieval‑Augmented Generation
- Mentoring
- Technical Decision‑Making
- Stakeholder Influence
- Relevant Cloud Certifications
- Security Clearance (SC)
- Responsible AI Principles
- AI Governance
- Compliance Requirements
- Agile Delivery
- CI/CD Practices
- Microsoft Copilot
- Azure OpenAI
- AWS AI
- Google Vertex AI
- Lang Chain
- Semantic Kernel
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