Associate Director - Lead AI Architect

£90,000 to 120,000 GBP

Bonus

Hybrid WORKING

Location: Central London, Greater London - United Kingdom Type: Permanent

Associate Director - Lead AI Architect

Locations: Edinburgh, Glasgow, London, Manchester or Newcastle

Salary: Up to £120,000 + Bonus

Employment Type: Permanent

Sponsorship: Unfortunately, visa sponsorship is not available for this position.

The Opportunity

We are looking for an experienced Lead AI Architect to join a leading Technology & Transformation consultancy, working on some of the UK's most complex and high-profile Security, Justice and Public Sector programmes.

This is an opportunity for someone who wants to move beyond AI experimentation and Proof of Concepts. You will play a leading role in architecting and delivering production-grade AI systems , helping clients take Generative AI and Machine Learning solutions from initial concept through to secure, scalable and operational services.

You will combine deep technical expertise with consulting, delivery and leadership experience. Working closely with senior client stakeholders and multidisciplinary engineering teams, you will translate complex business challenges into practical, robust and cost-effective AI solutions.

This is a hands-on technical leadership role, ideal for someone currently operating as a Lead AI Architect, Principal AI/ML Engineer, AI Engineering Lead, Principal Architect, AI Practice Lead or similar , and looking to take the next step into an Associate Director-level position.

The Role

• Design end-to-end, scalable and secure AI architectures for complex enterprise and public sector environments.
• Lead the development and deployment of production-grade Generative AI and Machine Learning solutions.
• Architect systems integrating LLMs and ML models into wider enterprise applications and workflows.
• Oversee the full technical lifecycle, from solution design and model selection through to deployment, monitoring and continuous improvement.
• Design and implement robust MLOps and LLMOps practices, including CI/CD, model monitoring, evaluation and governance.
• Deploy and optimise models using cloud-based AI services such as AWS Bedrock, Azure AI Foundry and other AWS, Azure or GCP services .
• Work with self-hosted inference and model-serving technologies where appropriate, including tools such as vLLM, SGLang and Ollama .
• Design evaluation, observability and monitoring frameworks to assess model performance, system health, reliability and business impact.
• Optimise AI solutions for performance, scalability, security and cost-efficiency.
• Identify where AI can deliver genuine value and, equally importantly, recognise when a simpler engineering solution is more appropriate.
• Translate high-level client requirements into technical architectures, delivery roadmaps and actionable engineering plans.
• Identify and mitigate technical risks, including security, deployment and operational challenges.
• Lead and mentor multidisciplinary teams of AI Engineers, Machine Learning Engineers, Data Scientists and Software Engineers.
• Engage with senior stakeholders and communicate complex technical concepts to both technical and non-technical audiences.

What We're Looking For

We are looking for someone with significant experience designing and delivering enterprise-scale AI, Machine Learning and Generative AI solutions in complex environments.

You will currently work, or have recently worked, for a consultancy or professional services organisation , with experience delivering technology solutions directly to external clients.

You should be able to demonstrate: Extensive experience designing, developing and deploying production-grade AI/ML and Generative AI solutions .

Experience operating at a senior technical leadership level, leading engineering teams and influencing senior stakeholders.

Strong hands-on experience with Python and modern AI/ML frameworks such as PyTorch and/or TensorFlow .

Deep understanding of LLMs, Generative AI, prompt engineering, RAG architectures and vector databases .

Experience with frameworks and tooling such as LangChain, LangGraph or similar open-source AI toolkits .

Experience fine-tuning, evaluating, deploying and monitoring large-scale AI systems.

Strong understanding of MLOps and/or LLMOps , including CI/CD, model deployment, monitoring, evaluation and governance.

Experience designing AI systems with a strong focus on security, responsible AI, ethical guardrails and compliance .

Broad cloud experience across AWS, Azure and/or GCP , ideally including native Generative AI services.

A strong software engineering mindset, with experience building scalable, reliable and maintainable production systems.

Excellent stakeholder management skills and the ability to bridge the gap between business requirements and technical delivery.

Experience working in complex and highly regulated sectors such as Government, Public Sector, Security, Justice, Defence, Healthcare or other similarly