AI Solutions Architect

AI Architect - SC cleared - London/Hybrid - Government projectKey ResponsibilitiesArchitect enterprise-grade AI solutions using frontier foundation models (eg Claude, GPT, Gemini family) across use cases including agentic automation, retrieval-augmented generation (RAG), copilots, and multi-modal applicationsLead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architecture and delivery roadmapsDesign and govern the AI platform architecture: model orchestration, prompt and context management, retrieval pipelines, vector stores, agent frameworks, and tool/context integration (including emerging protocols such as MCP)Define and enforce responsible AI, governance, and assurance frameworks - covering bias, safety, data privacy, and model risk - aligned to client and regulatory requirementsLead and mentor a team of AI engineers and architects, building technical capability and clear career pathways within the practiceOwn technical relationships with hyperscaler and frontier model partners (Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, OpenAI) to stay ahead of platform capabilityDrive reusable accelerators, frameworks, and IP that can be repeated and scaled across client engagementsAct as a trusted advisor to client CxOs and senior stakeholders on AI strategy, architecture, and roadmapOwn end-to-end delivery quality: architecture reviews, technical governance boards, production readiness, and post-go-live scalingContribute to thought leadership - whitepapers, conference contributions, and internal capability-buildingRequired Skills & Experience10+ years in software engineering, data engineering, or solution architecture, including at least 3-5 years focused specifically on applied AI/ML or generative AIProven, hands-on architecture experience with frontier large language models and multi-modal models - including prompt engineering, fine-tuning, RAG, and agentic/multi-agent system designStrong grounding in LLMOps/MLOps: evaluation frameworks, observability, cost and latency optimisation, guardrails, and safe deployment at enterprise scaleDirect experience with major frontier model providers (Anthropic Claude, OpenAI, Google Gemini, or equivalent) and cloud AI ecosystems (Azure AI/OpenAI Service, AWS Bedrock, Google Vertex AI)Solid understanding of AI governance, responsible AI, and emerging regulatory frameworks (eg EU AI Act, NIST AI RMF, or regional equivalents)Demonstrated technical leadership - leading architecture teams, chairing design/technical governance authorities, mentoring senior engineersClient-facing consulting experience: solutioning, pre-sales support, and stakeholder management at senior client levelStrong software engineering fundamentals: API design, cloud-native architecture, microservices, and data pipeline/data engineering experienceBachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience; an advanced degree is a plusPreferred/Desirable SkillsExperience with agent orchestration frameworks (eg LangGraph, AutoGen, CrewAI) and emerging tool-integration protocols (eg Model Context Protocol)Public sector or other regulated-industry delivery experience (financial services, healthcare, government)Relevant certifications (eg Azure AI Engineer Associate, AWS Certified Machine Learning, Google Professional ML Engineer)Experience building or scaling an AI Centre of Excellence or comparable practice capability within a consulting organisationPublished thought leadership, patents, or conference speaking in AI/ML