Associate Director, Lead AI Architect, Security & Justice, Engineering, AI & Data, Technology & Transformation

Overview

In this role you will lead the design and deployment of production-grade AI systems for government and public sector priorities, bridging innovation and practical impact. You’ll shape end-to-end architectures that integrate GenAI and traditional ML, and ensure scalable, secure, cost-efficient solutions. You will guide cross-functional teams, manage risk, and drive AI transformations from strategy to real-world delivery. This is a hands-on leadership role focused on delivering mission-critical AI with measurable societal impact. You will work within Deloitte’s Technology & Transformation practice, aligned to client needs and engineering excellence.

Pay / Benefits

• hybrid working policy
• flexible location (London base with hybrid options)
• focus on wellbeing
• opportunity for growth and development
• impactful client work
• culture of inclusion and collaboration

Responsibilities

• Architect end-to-end AI systems that are scalable, secure, and production-ready, integrating LLMs and ML models into enterprise workflows
• Oversee the full technical lifecycle from model selection to robust CI/CD and MLOps pipelines
• Deploy and optimise models across cloud and on-prem environments using tools like AWS Bedrock, Azure AI Foundry, or local GPU/CPU hardware
• Develop evaluation frameworks to measure model performance against business objectives pre- and post-deployment
• Drive system performance focusing on cost-efficiency, reliability, and quality of AI outputs for security and justice clients
• Design observability frameworks to monitor AI health and performance in real time
• Translate client requirements into technical roadmaps and actionable engineering tasks
• Identify and mitigate technical risk, including security vulnerabilities and deployment bottlenecks
• Shift AI from prototypes to production-ready services meeting high security and reliability standards
• Provide cross-functional team leadership and mentor data scientists and engineers

Key requirements

• Extensive experience designing, developing, and deploying enterprise-grade AI/ML solutions with team leadership and stakeholder management
• Expert Python proficiency with modern AI/ML frameworks (PyTorch, TensorFlow) and Generative AI libraries (LangChain, LangGraph or related open-source toolkits)
• Deep knowledge of LLMs, prompt engineering, RAG pipelines, vector databases, fine-tuning, and production-scale deployment
• Hands-on experience with evaluation, security practices, and ethical guardrails for safe deployment
• Experience across major cloud platforms (AWS, Azure, GCP) and cloud-agnostic capabilities; strong MLOps/LLMOps knowledge
• Proficiency in large-scale data processing/storage (SQL, Spark, Hadoop) is a plus
• Excellent stakeholder management and communication skills; ability to translate complex AI concepts for diverse audiences
• Ability to determine when AI adds value versus simpler engineering approaches

• Stakeholder management
• Clear communication
• Leadership and mentoring
• Python
• PyTorch
• TensorFlow

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