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AI Architect
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Job Description
AI Architect
Location: London (Hybrid)
Contract Duration: 6 Months
Daily Rate: £680 per day
Clearance: Active SC Clearance Required
Role Overview
We are seeking a AI Architect to lead the design, governance, and delivery of enterprise-grade AI solutions built on frontier foundation models.
This is a high-impact, hybrid technical-leadership contract position. You will architect solutions that push what frontier models including LLMs, multi-modal systems, and agentic architectures can responsibly achieve within complex, highly regulated environments. You will lead a team of architects and engineers while serving as a trusted technical advisor to client CxOs.
Key Responsibilities
- Architecture and Solution Design: Architect enterprise AI solutions using frontier models (Claude, GPT, Gemini family) across agentic automation, RAG, copilots, and multi-modal applications.
- Pre-Sales and Discovery: Lead technical solutioning during pre-sales and discovery, translating client business challenges into scalable AI architectures and delivery roadmaps.
- Platform Governance: Design and govern AI platform architectures covering model orchestration, prompt/context management, retrieval pipelines, vector stores, and tool integration (including emerging protocols like MCP).
- Responsible AI Frameworks: Define and enforce AI governance, risk, and safety frameworks (covering bias, data privacy, and model risk) aligned with regulatory requirements.
- Team Leadership and Delivery: Mentoring and leading a team of AI engineers and architects, driving end-to-end delivery quality, technical governance boards, and production readiness.
- Ecosystem Partnerships: Own technical relationships across major cloud AI ecosystems (Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, OpenAI).
- Reusable Assets: Drive the creation of reusable accelerators, frameworks, and IP across client engagements.
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Required Skills And Experience
- Clearance: Active UK SC Clearance is essential.
- Experience: 10+ years in software, data engineering, or solution architecture, with at least 3-5 years focused specifically on applied AI/ML or Generative AI.
- Hands-on GenAI Depth: Proven experience architecting solutions with frontier models including prompt engineering, fine-tuning, RAG, and agentic/multi-agent system design.
- LLMOps / MLOps Grounding: Expertise in evaluation frameworks, observability, cost and latency optimization, guardrails, and safe deployment at scale.
- Cloud and Model Ecosystems: Direct experience with major model providers (Anthropic, OpenAI, Google) and hyperscaler AI stacks (AWS Bedrock, Azure AI/OpenAI, Google Vertex AI).
- AI Governance: Deep knowledge of Responsible AI, risk management, and regulatory frameworks (e.g., EU AI Act, NIST AI RMF).
- Consulting Leadership: Proven experience in client-facing consulting, pre-sales technical leadership, and managing CxO-level stakeholders.
- Engineering Fundamentals: Strong software engineering background (API design, microservices, cloud-native architecture, data pipelines).
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Preferred / Desirable Skills
- Experience with agent orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI) and emerging tool protocols (e.g., Model Context Protocol / MCP).
- Relevant certifications (e.g., Azure AI Engineer, AWS ML Specialty, Google Professional ML Engineer).
£650.00 - £680.00 / day
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