Initialize IT

AI Architect - SC cleared - London/Hybrid - £682 - 6-12 months - Government project Key Responsibilities Architect 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 applications Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architecture and delivery roadmaps Design 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 requirements Lead and mentor a team of AI engineers and architects, building technical capability and clear career pathways within the practice Own technical relationships with hyperscaler and frontier model partners (Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, OpenAI) to stay ahead of platform capability Drive reusable accelerators, frameworks, and IP that can be repeated and scaled across client engagements Act as a trusted advisor to client CxOs and senior stakeholders on AI strategy, architecture, and roadmap Own end-to-end delivery quality: architecture reviews, technical governance boards, production readiness, and post-go-live scaling Contribute to thought leadership - whitepapers, conference contributions, and internal capability-building Required Skills & Experience 10+ years in software engineering, data engineering, or solution architecture, including at least 3-5 years focused specifically on applied AI/ML or generative AI Proven, hands-on architecture experience with frontier large language models and multi-modal models - including prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design Strong grounding in LLMOps/MLOps: evaluation frameworks, observability, cost and latency optimisation, guardrails, and safe deployment at enterprise scale Direct 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 engineers Client-facing consulting experience: solutioning, pre-sales support, and stakeholder management at senior client level Strong software engineering fundamentals: API design, cloud-native architecture, microservices, and data pipeline/data engineering experience Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience; an advanced degree is a plus Preferred/Desirable Skills Experience 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 organisation Published thought leadership, patents, or conference speaking in AI/ML