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About the Role

We are seeking an experienced AI Architect to lead the design and delivery of secure, scalable, and responsible AI solutions for enterprise and public-sector programs. This role involves hands-on technical expertise and architectural leadership to shape AI solutions from discovery through production.

Responsibilities

• Design and own end-to-end AI client-specific solution architectures, including Generative AI, Agents, and traditional ML.
• Define and maintain enterprise AI architecture patterns, reference architectures, and reusable building blocks within the Microsoft ecosystem.
• Lead AI governance, security, and Responsible AI by design, ensuring solutions meet regulatory, ethical, and organizational standards.
• Provide architectural oversight across delivery teams, ensuring quality and scalability.
• Support pre-sales and discovery, shaping solution approaches, technical estimates, and delivery roadmaps.
• Advise stakeholders on AI feasibility, trade-offs, risks, and long-term sustainability.
• Build hands-on prototypes, reference implementations, and reusable accelerators to set credible technical direction and unblock delivery teams.

Requirements

• Significant overall experience delivering AI and Data solutions in complex enterprise environments, with a minimum of 5 years hands-on AI delivery experience.
• Proven experience delivering production-grade AI solutions end-to-end, from discovery through to live operations and ongoing model management.
• Hands-on expertise across Microsoft cloud and AI ecosystem, including Microsoft Foundry and data platform.
• Strong experience with integrating low-code Power Platform solutions into enterprise-scale solutions, including hands-on experience with Copilot Studio.
• Solid understanding of Microsoft security, identity, and compliance (Entra ID, RBAC, network isolation, data protection).
• Strong experience designing LLM-based solutions, including Retrieval-Augmented Generation (RAG), prompt engineering strategies, and agent-based architectures, leveraging frameworks such as Semantic Kernel, LangChain, and Microsoft Agent Framework.
• Deep practical experience with classical Machine Learning, including supervised and unsupervised learning, feature engineering, model selection, training pipelines, evaluation frameworks, and production lifecycle management.
• Proven ability to assess client use cases and make well-reasoned architectural decisions between classical ML and Generative AI approaches.
• Strong experience in cloud-native architecture, including API-based and event-driven designs, enterprise integration patterns, and architectures focused on scalability, resilience, and reliability.
• Experience with DevOps, MLOps, and LLMOps practices, including CI/CD pipelines, automated testing, environment strategies, and operating LLM-based solutions in production.
• Strong understanding of Generative AI governance, operational controls, and cost evaluation.
• Strong experience embedding Responsible AI and governance into Generative AI solutions, covering safety, risk management, transparency, explainability, human-in-the-loop design, and regulatory alignment.
• Desirable experience in integrating enterprise data platforms with AI solutions, including familiarity with Lakehouse architectures and data engineering principles.
• Proven experience in a consulting role, with the ability to translate complex technical concepts into clear business outcomes.
• Good experience of managing and mentoring junior AI engineers or consultants.
• Must hold at least two relevant Microsoft certifications (AI-901, AI-103, DP-800 AZ-305, AI-300), or be actively working towards them.
• Candidates must hold, or be eligible for, UK Security Clearance.

Skills

• Generative AI
• Agents
• Traditional ML
• Microsoft ecosystem
• Responsible AI
• Microsoft cloud
• Microsoft AI ecosystem
• Microsoft Foundry
• Microsoft data platform
• Low-code Power Platform
• Copilot Studio
• Microsoft security
• Microsoft identity
• Microsoft compliance
• Entra ID
• RBAC
• Network isolation
• Data protection
• LLM-based solutions
• Retrieval-Augmented Generation (RAG)
• Prompt engineering
• Agent-based architectures
• Semantic Kernel
• LangChain
• Microsoft Agent Framework
• Classical Machine Learning
• Supervised learning
• Unsupervised learning
• Feature engineering
• Model selection
• Training pipelines
• Evaluation frameworks
• Production lifecycle management
• Cloud-native architecture
• API-based designs
• Event-driven designs
• Enterprise integration patterns
• Scalability
• Resilience
• Reliability
• DevOps
• MLOps
• LLMOps
• CI/CD pipelines
• Automated testing
• Environment strategies
• Model lifecycle management
• Prompt lifecycle management
• Observability
• Cost management
• Generative AI governance
• Operational controls
• Cost evaluation
• Safety
• Risk management
• Transparency
• Explainability
• Human-in-the-loop design
• Regulatory alignment
• Enterprise data platforms
• Lakehouse architectures
• Data engineering principles
• Consulting
• Mentoring

Location

• Home workers
• Office visits required

Work Type

• Home workers

Experience Level

• Minimum of 5 years hands-on AI delivery experience
• Significant overall experience delivering AI and Data solutions in complex enterprise environments

Education Level

• At least two relevant Microsoft certifications (AI-901, AI-103, DP-800 AZ-305, AI-300), or actively working towards them.

Benefits

• Competitive compensation packages (incl. bonuses)
• Pension and benefits plans
• Comprehensive career development programme
• Mentoring
• Training plans

About the Company

• Hitachi Solutions Europe is a global Digital, Data and Technology consultancy, Microsoft Gold partner and Cloud Services partner, specializing in end-to-end transformation.
• We specialize in Dynamics 365 Business Applications, Power Platform, including Azure, Application Modernisation and Data & Analytics.
• Our highly skilled team help drive improvements, creating efficiency and growth within organisations.
• We are committed to Microsoft technologies, with a mission to revolutionize modern businesses.
• We place value on collaboration, open communication, and transparency.
• We emphasize the importance of team spirit, cohesion, and appreciation.
• Our learning culture and flat hierarchy are our recipes for success.