CSI GLOBAL LTD
AI Architect
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Role: AI Architect
Location: London, UK - Hybrid
Type: Contract - Inside IR35
Role Overview
We are seeking an experienced AI Architect to define, design, and lead the implementation of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will be responsible for architecting scalable, secure, and responsible AI platforms, driving innovation through Agentic AI, LLMs, RAG frameworks, MLOps, and cloud-native technologies.
The role requires close collaboration with business stakeholders, data scientists, engineering teams, and enterprise architects to translate business objectives into AI-driven solutions that deliver measurable value.
Key Responsibilities
AI Strategy & Architecture
- Define enterprise AI architecture roadmaps aligned with business objectives
- Design scalable AI, ML, and Generative AI platforms across cloud environments
- Evaluate and recommend AI technologies, frameworks, models, and deployment patterns
- Lead architecture reviews and establish AI engineering best practices
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Generative AI & Agentic AI
- Design and implement solutions using LLMs such as OpenAI, Claude, Gemini, and open-source models
- Architect Retrieval-Augmented Generation (RAG), GraphRAG, Hybrid Search, and Knowledge Retrieval platforms
- Design multi-agent systems and orchestration workflows using LangChain, LangGraph, CrewAI, or similar frameworks
- Define prompt engineering, model evaluation, and AI observability standards
Data & AI Engineering
- Design data pipelines supporting AI model training, fine-tuning, and inference
- Establish vector database architecture and semantic search solutions
- Drive knowledge graph and ontology-based AI implementations
- Ensure integration with enterprise systems, APIs, and data platforms
MLOps & AI Operations
- Define AI model lifecycle management frameworks
- Establish CI/CD pipelines for AI deployment
- Implement monitoring, retraining, drift detection, and performance management strategies
- Drive automation and operational excellence across AI environments
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Governance, Security, & Compliance
- Establish Responsible AI, Explainable AI (XAI), and AI governance frameworks
- Ensure compliance with organizational and regulatory requirements
- Define AI security controls, access management, data privacy, and model governance standards
- Conduct architecture risk assessments and mitigation planning
Stakeholder Management
- Partner with business leaders to identify high-value AI opportunities
- Lead client-facing architecture discussions and solution presentations
- Provide technical mentorship to AI engineers, data scientists, and architects
- Drive PoCs, innovation initiatives, and AI transformation programs
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