> Markdown version of [/jobs/ext/325993-ai-solution-architect](https://www.wearedevelopers.com/jobs/ext/325993-ai-solution-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Solution Architect

- **Company:** Ai
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Architectural Patterns, Microsoft Azure, Cloud Computing, Encodings, Data Architecture, Cursor (Graphical User Interface Elements), DevOps, Github, Knowledge Management, Cloud Services, Azure Machine Learning, Software Engineering, Enterprise Software Applications, Azure Data Factory, GitHub Copilot, Snowflake, Multi-Agent Systems, Prompt Engineering, AWS Lambda, Event Driven Architecture, Microsoft Fabric, Containerization, AI Platforms, Data Management, Machine Learning Operations, Api Gateway, Terraform, Data Pipelines, Databricks, Microservices
- **Published:** June 2, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/38142217/

## About the Role

AI solution architecture- you have demonstrated experience designing and delivering AI-powered solutions at enterprise scale. You can take responsibility for end-to-end AI solution design from requirements through to production, across use cases such as generative AI applications, RAG systems, agentic workflows, or AI-assisted automation. You understand the architectural patterns, trade-offs, and constraints involved in building production AI systems and can make informed decisions about when and how to apply AI to business problems.
Technical depth across cloud platforms- you have strong hands-on experience with cloud services and platforms, particularly across Microsoft Azure and AWS ecosystems. You can design integration patterns for AI workloads, applying modern software engineering practices including APIs, microservices, event-driven architectures, and DevOps. You have sufficient depth to make credible technology choices and guide delivery teams through implementation, with a practical understanding of how AI capabilities integrate with existing enterprise systems and infrastructure.
Security, governance, and responsible AI- you understand the security, data protection, and compliance considerations specific to AI implementations. You can design solutions that embed responsible AI principles from the start, including appropriate governance frameworks, model monitoring, audit trails, and accountability structures. You're able to navigate regulatory requirements and work with security and risk teams to ensure AI solutions meet the standards expected by enterprise clients.
Stakeholder engagement and communication- you have experience working directly with clients and senior stakeholders to understand problems, shape AI solution approaches, and build consensus. You can translate complex AI concepts for non-technical audiences, facilitate design discussions with multi-disciplinary teams, and present recommendations to architectural review boards. You contribute to pre-sales activities including technical input to proposals and client presentations.

Highly Desirable

Large organisation delivery experience- you have delivered AI solutions for government departments, major financial institutions, or large private sector organisations, understanding the complexities of enterprise environments including governance requirements, security constraints, and working effectively within multi-supplier delivery contexts.
Data architecture and pipeline design- experience designing data pipelines, model deployment strategies, and working with data platforms such as Microsoft Fabric, Databricks, or Snowflake to support production AI workloads.
Architecture community and thought leadership- active participation in AI and architecture communities, staying current with rapidly evolving AI technologies and contributing to professional development through knowledge sharing, presentations, or published work.

Technologies and Platforms

Cloud AI services: Azure OpenAI Service, Azure AI Services, Azure Machine Learning, AWS Bedrock, AWS SageMaker, AWS Lambda, API Gateway
Data platforms: Microsoft Fabric, Databricks, Snowflake, Azure Data Factory
AI development and tooling: Copilot Studio, Power Platform, Cursor, GitHub Copilot, prompt engineering frameworks, RAG and evaluation frameworks
Infrastructure and DevOps: Azure DevOps, GitHub Actions, Terraform, containerisation
AI patterns: RAG architectures, agentic workflows, multi-agent orchestration, tool use patterns, human-in-the-loop design

## Description

As an AI Solution Architect, you'll work with government, financial services, and private sector clients to design and deliver AI solutions that solve real business problems. You'll bring together AI capabilities, sound solution design, and practical engineering experience to create production-grade systems that deliver measurable value- not proofs of concept that gather dust. Your work sits at the intersection of software engineering and AI, focusing on building scalable, secure systems that consume and orchestrate AI services rather than training foundation models from scratch.
One week you might be designing a RAG architecture for a government department's knowledge management platform; the next you could be working with a financial services client to integrate agentic workflows into their existing operations, guiding a delivery team through implementing responsible AI patterns on a live service. You'll establish architecture patterns and standards that accelerate AI adoption across our client base, embedding governance frameworks and security controls into solution designs from the outset. Whether you're evaluating the right AI platform for a client's use case, designing data pipelines to support model deployment, or presenting your solution approach to an architectural review board, you'll bring both hands-on AI engineering experience and sound architectural judgement to every engagement.
Your background in solution architecture and building digital services means you understand how enterprise systems work in practice- and you've applied that foundation to designing and delivering AI-powered solutions at scale. You know how to move from experimentation to production - designing integration patterns for AI services, building reliable pipelines, and ensuring solutions meet the non-functional requirements that enterprise clients demand around performance, security, and compliance. You'll bring systems thinking that connects AI architectural decisions to broader service and business contexts, combined with a strong understanding of responsible AI principles including bias mitigation, transparency, and appropriate human oversight. You collaborate effectively with diverse teams including data scientists, software engineers, product managers, and senior business stakeholders, translating complex AI concepts into language that supports informed decision-making at all levels.
As part of our central architecture team, you'll work alongside experienced Technology Principals and Solution Architects who share your drive to solve complex challenges. You will have a strong support network to collaborate with, learn from different perspectives, and tackle problems together. AI is moving fast, and we recognise that staying current matters - you'll contribute to and shape our AI architectural approaches, share knowledge through internal sessions and technical documentation, and help build reference architectures that the wider organization can draw on. Your expertise helps our clients adopt AI with confidence, building solutions that are not only technically sound but deliver meaningful outcomes for the people who use them.


## Related Videos

- [Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact](https://www.wearedevelopers.com/videos/1541-azure-ai-foundry-for-developers-open-tools-scalable-agents-real-impact)
- [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next)
- [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform)
- [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team)
- [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture)
- [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean)

## Related Articles

- [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)
- [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)