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# Principal AI Solution Architect, Technology Consulting- London, Leeds, Manchester or Newcastle

- **Company:** CRELIMUK Credera Limited
- **Location:** Leeds, UK
- **Experience:** Expert
- **Salary:** £95,000.0 - £113,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Cloud Engineering, Information Technology Consulting, Continuous Integration, Information Leak Prevention, Data Systems, Information Lifecycle Management, Key Management, Machine Learning, Platform as a Service (PAAS), Cloud Services, Azure Machine Learning, Search Technologies, Systems Integration, Enterprise Data Management, Large Language Models, Snowflake, Multi-Agent Systems, Software Security, Generative AI, Microsoft Fabric, Core Data, Machine Learning Operations, Virtual Agents, Azure Synapse Analytics, Amazon Redshift, Databricks, Microservices
- **Published:** September 21, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5834863638

## About the Role

Proven experience (8+ years) in AI, machine learning or data solution design, including significant hands-on experience delivering modern generative AI solutions.
Deep, applied experience leading generative AI and agentic proof of concepts and industrialising them into production - including tool use, orchestration, autonomous and multi-agent workflows.
Demonstrable experience designing end-to-end AI architectures that incorporate modern AI or agentic capability at enterprise scale.
Overall responsibility and accountability for programme delivery, managing cost, quality and business outcomes with minimal oversight, and effectively leading large teams across multiple workstreams.
Experience leading solution implementations and AI programmes for medium to large teams.
Experience providing architectural assurance, reviewing the work of other architects and acting as a Design Authority across complex programmes.
Experience in the architecture of advanced analytics platforms or modern data solutions (e.g. cloud-native data and lakehouse platforms) is desirable, providing a strong foundation for grounding enterprise AI solutions in trustworthy data.
Strong understanding of core data management concepts over the full data lifecycle, and how to ground AI solutions in trustworthy enterprise data.
Strong understanding of cloud-centric approaches to solution design and architecture.
Strong understanding of CI/CD, LLMOps and modern approaches to IT and infrastructure delivery.
In-depth knowledge of AI security, responsible AI and compliance standards.
Public sector experience preferred (government, healthcare, or regulated industries).

Technical Expertise
Deep, hands-on experience delivering enterprise AI solutions on Azure or AWS, with named, relevant capability, for example:Azure: Azure OpenAI Service, Azure AI Foundry, Azure AI Search (vector / RAG), Azure Machine Learning, Azure AI Agent Service, Semantic Kernel, Prompt Flow and Content Safety.
AWS: Amazon Bedrock (including Knowledge Bases and Agents), Amazon SageMaker, Amazon Q, Amazon OpenSearch (vector), and Guardrails for Amazon Bedrock.

Expertise in agentic frameworks and orchestration patterns (e.g. Semantic Kernel, AutoGen, LangGraph, LangChain, CrewAI or equivalents) and emerging standards such as the Model Context Protocol (MCP).
Expertise in RAG and retrieval patterns using vector stores and embedding models, and in evaluation and guardrail frameworks for LLM and agentic systems.
Certified architect in a cloud-based platform (AWS or Azure); AI or machine learning specialism desired.
Familiarity with modern data and lakehouse ecosystems (e.g. Microsoft Fabric, Databricks, Snowflake, Synapse, Redshift) as a foundation for grounding AI.

Soft Skills
Strong leadership and programme management skills, with the confidence and directive to challenge the status quo and align delivery to expected outcomes.
Excellent communication and collaboration abilities, able to partner with and influence C-suite stakeholders.
Recognised as a leader in AI whose knowledge and experience are actively sought by clients and the wider market.
Ability to translate business objectives into pragmatic, scalable technical solutions and communicate the value and limitations of AI with credibility.
Ability to provide constructive technical challenge and assurance, influencing architectural decisions while maintaining strong relationships with delivery teams and stakeholders.

## Description

AI Solution & End-to-End Architecture
Lead the design and development of robust, end-to-end AI solution architectures that incorporate modern generative and agentic capabilities and support clients' strategic goals.
Define and implement AI solution architectures for cloud-native PaaS and SaaS environments, integrating AI with enterprise data, APIs and microservices.
Oversee the integration of Machine Learning, Generative AI and agentic systems into enterprise environments, ensuring seamless functionality, performance and responsible operation.
Provide technical assurance across programmes, reviewing and challenging solution designs to ensure they meet architectural, security, scalability and delivery standards.
Act as a Design Authority where appropriate, providing architectural oversight and accountability across complex programmes and ensuring consistency and quality across multiple workstreams.

AI Proof of Concepts & Agentic Enablement
Lead high-profile generative AI and agentic proof of concepts (PoCs) at client sites, personally shaping and steering delivery to demonstrate the value and potential of AI-driven solutions with credibility and pace.
Drive the implementation and industrialisation of LLM-based and agentic solutions to enhance business processes, decision-making and customer experience, applying patterns such as RAG, orchestration and multi-agent workflows, and tool/function calling.
Establish best practices for LLMOps, MLOps and AIOps, including evaluation, observability, model routing, cost and latency optimisation, and secure deployment.
Lead the development of reusable AI accelerators, patterns and reference architectures, and champion market-leading practice across the capability.

Responsible AI, Security & Governance
Establish evaluation, guardrail and responsible AI practices to manage risks such as hallucination, bias, data leakage and prompt injection at enterprise scale.
Ensure AI solutions meet relevant standards and regulations for security, privacy and responsible AI, particularly in public sector and regulated environments.

Consulting & Collaboration
Advise clients on AI adoption, modernisation and operating-model strategies for the sustainable, responsible scaling of AI and agentic capability.
Collaborate with cross-functional teams to align AI strategy with business objectives, and partner with senior client stakeholders and the C-suite to define AI roadmaps.
Work closely with business, engineering and policy teams to align solutions with organisational goals.
Act as a leader in Credera's AI capability, driving thought leadership and innovation, and sharing expertise with clients and audiences beyond immediate project delivery.
Mentor and guide teams of engineers, data scientists and architects across multiple workstreams, fostering a culture of innovation and excellence.
Act as a Design Authority across programme delivery where required, providing assurance and constructive challenge on the designs produced by other architects and delivery teams.


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