Lead AI Engineer

Our client is a leading automotive organisation at the forefront of AI-driven innovation, investing heavily in Generative AI, Machine Learning, Connected Vehicle technologies, and intelligent manufacturing solutions. As part of a major digital transformation programme, they are looking for a Lead AI Engineer to take ownership of AI delivery across multiple business domains whilst remaining hands-on in solution design and development.

This position offers the opportunity to lead the development of cutting-edge AI products that will shape the future of mobility, customer experience, and operational excellence.

The Role

As a Lead AI Engineer, you will combine technical leadership with hands-on engineering responsibilities. You will lead the design, development, and deployment of scalable AI applications, mentor a growing team of AI Engineers and Data Scientists, and work closely with senior stakeholders to define the organisation's AI roadmap.

You'll be expected to spend a significant amount of your time architecting solutions, writing production code, evaluating emerging AI technologies, and ensuring best practices are followed across the AI landscape.

Key Responsibilities

• Lead the design and implementation of AI and Machine Learning solutions across the business.
• Architect scalable cloud-native AI platforms and MLOps frameworks.
• Develop and deploy production-ready Machine Learning and Generative AI applications.
• Build and optimise Large Language Model (LLM) solutions, AI agents, and Retrieval-Augmented Generation (RAG) platforms.
• Mentor and support AI Engineers, Data Scientists, and MLOps Engineers.
• Collaborate with Product, Engineering, Data, and Business teams to deliver innovative AI solutions.
• Create technical roadmaps and define AI engineering standards and best practices.
• Oversee model deployment, monitoring, governance, and performance optimisation.
• Drive the adoption of emerging AI technologies and evaluate new tools and frameworks.
• Ensure solutions are secure, scalable, and compliant with responsible AI principles.

Required Experience

• 6 years of experience building and deploying Machine Learning or AI solutions.
• Previous experience leading technical projects or mentoring engineering teams.
• Strong expertise in Python and modern software engineering practices.
• Experience with Machine Learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn.
• Strong knowledge of cloud platforms, ideally Azure.
• Experience designing MLOps workflows and CI/CD pipelines for AI applications.
• Hands-on experience with Generative AI, LLMs, and Agentic AI solutions.
• Experience building APIs, microservices, and enterprise-grade applications.
• Excellent stakeholder management and communication skills.

Preferred Experience

• Automotive, mobility, manufacturing, or IoT industry experience.
• Experience with connected vehicle data and real-time streaming architectures.
• Knowledge of Azure OpenAI, Databricks, LangChain, Semantic Kernel, or similar frameworks.
• Experience leading AI transformations within large enterprise environments.
• Exposure to computer vision, predictive maintenance, or intelligent automation solutions.

Technology Stack

• Python
• Azure AI & Azure OpenAI
• PyTorch / TensorFlow
• Databricks
• Docker & Kubernetes
• GitHub Actions / Azure DevOps
• LangChain / Semantic Kernel
• SQL & NoSQL Databases
• Kafka & Event Streaming Technologies

What's On Offer

• Base Salary: €95,000 – €110,000
• Company Car & Fuel Card
• Annual Performance Bonus
• Pension Scheme
• Private Healthcare & Group Insurance
• Meal Vouchers & Net Allowance
• 35 Days Holiday
• Flexible Hybrid Working
• Dedicated Training & Conference Budget
• Clear Progression Towards AI Engineering Manager or AI Architect

Why Join?

This is an opportunity to lead the next generation of AI initiatives within a globally recognised automotive organisation. You'll have direct influence over AI strategy while remaining deeply involved in technical delivery, working on projects spanning GenAI, intelligent manufacturing, connected vehicles, predictive maintenance, and autonomous decision-making systems.