Digital & Technical Consultancy

Our client is one of the most recognised names in digital and technical consultancy, working at the cutting edge of technology transformation across government and public sector. They are not just advising - they are building, deploying, and transforming. Their Engineering, AI & Data practice is where some of the most ambitious and impactful AI programmes in the UK are taking shape. The Security & Justice team is at the heart of that - a tight-knit group of engineers, data scientists, and architects working on projects that genuinely matter to society. These are not sandbox experiments. They are production systems operating in some of the most complex and sensitive environments you will find. To thrive here, you will need extensive hands-on experience architecting and deploying enterprise-grade AI and ML solutions end-to-end, expert Python skills, and deep knowledge of LLMs, RAG pipelines, and MLOps. Cloud-agnostic experience across AWS, Azure, and GCP is a must, and you will need to be as comfortable talking to senior stakeholders as you are reviewing a CI/CD pipeline. SC or DV clearance is required for this role. Sound like you?, · Design scalable, secure, production-ready AI architectures integrating LLMs and ML models into enterprise workflows.

· Oversee the full technical lifecycle from model architecture selection through to robust CI/CD and MLOps pipelines.

· Deploy and optimise models using AWS Bedrock, Azure AI Foundry, or self-hosted GPU/CPU infrastructure with tools like vLLM and Ollama.

· Design and implement evaluation, monitoring, and observability frameworks to track AI system performance in real time.

· Translate high-level client requirements into detailed technical roadmaps and actionable engineering tasks.

· Proactively identify and manage technical risk, including security vulnerabilities and deployment bottlenecks.

· Lead and mentor cross-functional teams of data scientists and engineers across project delivery.

· Communicate complex AI concepts clearly to non-technical senior stakeholders, building confidence in AI-driven solutions.

· Extensive experience designing, developing, and deploying enterprise-grade AI and ML solutions end-to-end.

· Expert-level Python skills with proficiency in PyTorch, TensorFlow, LangChain, LangGraph, or similar GenAI frameworks.

· Deep knowledge of LLMs, prompt engineering, RAG pipelines, vector databases, and generative AI architectures.

· Hands-on experience with AI evaluation frameworks, security best practices, and ethical guardrails for production systems.

· Broad cloud experience across AWS, Azure, and GCP with Generative AI services - cloud-agnostic experience preferred.

· Strong grasp of MLOps and LLMOps principles including CI/CD for ML, model monitoring, and governance frameworks.

· Proven ability to lead technical teams and manage stakeholder relationships at a senior level.

· Ability to assess client challenges pragmatically and determine when AI is the right solution versus a simpler approach.

The client would also like to see some of the below, but this is not essential:

· PhD or equivalent in Computer Science, Machine Learning, or Artificial Intelligence.

· Background in traditional ML and AI alongside Generative AI experience.

· Experience working in complex regulated sectors such as healthcare, government, or justice.

· Proficiency with large-scale data processing technologies such as SQL, Spark, or Hadoop.

· Open source contributions or personal projects demonstrating excellence in AI engineering.