Job Description
As an AI Solution Architect, you’ll work with our 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, or 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 that’s 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. This gives you 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 organisation 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.
Qualifications
Essential Requirements AI solution architecture — you have demonstrated experience designing and delivering AI-powered solutions at enterprise scale. You can evidence taking 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 The following reflects the types of technologies and platforms relevant to this role. We don’t expect expertise across all of these, but familiarity with a meaningful subset is important. 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
Additional Information
At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their well-being, professional growth, and financial stability. One of our standout advantages is the ability to work with a hybrid schedule along with business travel, allowing our employees to strike a balance between work and life. We also offer a range of tech-related benefits, including an innovative Tech Scheme to help keep our team members up-to-date with the latest technology. We prioritise the health and safety of our employees, providing private medical and life insurance coverage, as well as free eye tests and contributions towards glasses. Our team members can also stay ahead of the curve with incentivized certifications and accreditations, including AWS, Microsoft, Oracle, and Red Hat. Our employee-designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth. #LI-SS1
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