Enterprise AI Architect

Amtis Professional; Birmingham; Hybrid; GBP 54,000 - 90,000; Full time

Job summary

Amtis Professional seeks an Enterprise AI Solution Architect to shape an enterprise AI roadmap in the West Midlands. You will architect end-to-end AI solutions, validate PoCs, and define blueprints across data, knowledge and process layers, aligning with security and governance requirements.

Collaborating with IT, data, and business units, you will drive scalable, compliant AI deployments and reusable design patterns for commercial impact.

Qualifications

• Proven experience as an AI Solutions Architect delivering AI/ML at enterprise scale.
• Strong enterprise integration experience with APIs, microservices, and cloud-native patterns.
• Experience with MLOps and deploying AI/ML models in production.
• Deep knowledge of LLMs, generative AI, and agentic AI in business contexts.
• Experience designing vector-based search and retrieval systems.
• Knowledge of security, governance, data privacy, and responsible AI.

Responsibilities

• Architect end-to-end AI solutions across data, knowledge and process layers.
• Design PoCs to validate target architectures and reusable patterns at scale.
• Define AI solution blueprints and integration patterns for APIs and microservices.
• Lead MLOps and model deployment pipelines for secure, compliant operation.
• Integrate AI frameworks like LangChain, Semantic Kernel, Llama into architectures.
• Design and implement RAG architectures with data ingestion and vector stores.
• Ensure security, governance and auditability across AI solutions.
• Collaborate with IT, data, security and business to transition PoCs to production.

Skills

AI architecture

Enterprise integration

MLOps

LLMs

Security & governance

Education

Degree in CS/SE/Data Science

Tools

LangChain

Semantic Kernel

Llama

Vector search

MCP

Job description

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.

Key Responsibilities:

• 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.

Key Requirements:

• 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.

Qualifications:

Degree in Computer Science, Software Engineering, Data Science, Information Systems or a related technical discipline is ideal.