Enterprise AI Architect

Enterprise AI Solution Architect - West Midlands, hybrid working weekly on-site, Up to £90k, 6 Month initial FTC - Scope for extension and permanent

Step into a pivotal role shaping an enterprise-scale AI future for a major organisation in the West Midlands. This fixed-term opportunity will see you architecting impactful AI solutions that transform internal business processes, reporting, frontline operations and customer experience, while setting the foundations for long-term innovation. You will work at the intersection of technology, strategy and commercial impact, translating ambitious ideas into secure, scalable AI capabilities.

About the Role:

You will be the Enterprise Scale AI Solution Architect responsible for designing and validating proof-of-concept solutions that underpin the organisation’s AI roadmap. Working across business units, you will define target architectures, orchestrate AI components, and create reusable patterns that accelerate delivery of high-value use cases. Your work will directly influence how AI is embedded into the data, knowledge and process layers of the enterprise, ensuring solutions are robust, compliant and commercially viable., * Architect end-to-end AI solutions across data, knowledge and process layers, covering internal business processes, reporting, frontline operations and customer experience.

• Design and deliver proof-of-concept AI solutions that validate target architectures, use cases and reusable patterns at enterprise scale.
• Define and document AI solution blueprints, including integration patterns for APIs, microservices, orchestration and cloud-native components.
• Lead the technical design of MLOps and model deployment pipelines, ensuring reliable, secure and compliant operation of LLMs, agentic AI and generative AI services.
• Select and integrate appropriate AI frameworks and tools (e.g. LangChain, Semantic Kernel, Llama, vector-based search, MCP/Model Context Protocol) into the enterprise architecture.
• Design and implement RAG (Retrieval-Augmented Generation) architectures, including data ingestion, vector stores, and knowledge layer orchestration.
• Ensure AI solutions meet security, governance and compliance requirements, including data protection, access controls and auditability.
• Collaborate with stakeholders across IT, data, security and business functions to refine use cases, align solutions with commercial objectives, and transition PoCs towards production readiness.

• Proven experience as an AI Solutions Architect or Enterprise Architect delivering AI/ML solutions at enterprise scale.
• Strong expertise in enterprise integration patterns, including APIs, microservices, event-driven architectures and cloud-native services.
• Experience with MLOps, model deployment and operationalising AI/ML models in production environments.
• Deep understanding of LLMs, generative AI, agentic AI and their application to real-world business use cases.
• Practical experience designing and implementing vector-based search and retrieval systems within AI solutions.
• Strong knowledge of security, compliance and governance in AI systems, including data privacy and responsible AI considerations.
• Ability to define target architectures, solution designs and reusable patterns that support scalability, maintainability and commercial impact.
• Proven track record of working with cross-functional teams to translate business requirements into technical AI solutions.

Desirable Skills:

• Experience with LangChain, Semantic Kernel, Llama and related frameworks for building LLM-based applications.
• Familiarity with Model Context Protocol (MCP) and emerging standards for AI orchestration and context management.
• Experience designing and implementing RAG architectures in enterprise environments.
• Background in cloud platforms (e.g. AWS, Azure, GCP) and their AI/ML services.
• Exposure to knowledge management, knowledge graphs or advanced search systems integrated with AI solutions.
• Experience in designing AI solutions for customer experience, contact centres, or frontline operations.
• Previous involvement in building AI roadmaps or strategic AI initiatives within large organisations., * Degree in Computer Science, Software Engineering, Data Science, Information Systems or a related technical discipline is ideal.