AI Solutions Architect

We're looking for a Solution Architect to join a forward-thinking AI Solutions programme within a major global automotive OEM.

The role sits at the heart of a large-scale AI transformation effort — responsible for proposing and designing technical, AI-based solutions across a broad Product Development and Technology (PDT) organisation. The mission is clear: improve efficiency, speed, inventiveness, and quality by applying production-grade AI at scale, adapted to the people who use it every day.

• Location: TBC
• Contract type: Permanent or freelance
• Benefits: Competitive package; high-visibility role within a major AI transformation programme

Responsibilities

• Analyse existing problem descriptions and product requirements, gathering additional context where needed in collaboration with the Product Manager
• Design high-level technical architectures that bring together AI components, front end, back end, infrastructure, data pipelines, and neural network models into cohesive solutions
• Define service boundaries, APIs, and scalable system architectures suited to enterprise-scale environments
• Translate product needs into clear data requirements and architecture decisions
• Produce technical documentation including architecture diagrams, tradeoff analyses, and decision records
• Work in close collaboration with Product Managers, Project Managers, and technical implementation teams
• Ensure solutions are production-grade, observable, secure, and trustworthy at scale

Qualifications

• 5+ years designing and delivering production software systems
• 2+ years developing or working with ML, AI, or data-driven solutions
• Working knowledge of AI/ML system design including data pipelines, deployment patterns, and operational monitoring
• Strong data architecture fundamentals across batch and streaming, modelling, and governance
• Experience with cloud infrastructure, deployment patterns, and secure system design
• Excellent technical documentation skillsExperience architecting production LLM applications — RAG, vector search, tool calling, agents — is a strong plus
• Hands-on MLOps or ML platform experience is advantageous
• Background in enterprise-scale or regulated environments is beneficial
• Strong cost modelling skills for AI workloads is a plus
• Degree in an engineering or science field preferred
• Ability to work across global, cross-functional teams and build alignment