AI Architect

Required Skills & Experience

• 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, equivalent in depth to GenAI expertise.
• Proven ability to assess client use cases and make well-reasoned architectural decisions between classical ML and Generative AI approaches; and articulate clearly why.
• 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, with a strong focus on model and prompt lifecycle management, observability and evaluation, reliability and cost management.
• Strong understanding of Generative AI governance, operational controls and cost evaluation, including monitoring usage, performance and designing solutions that are supportable, auditable and sustainable at scale.
• 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, effectively engaging non‑technical stakeholders and senior leaders.
• 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.

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