Lead AI Engineer - #2078103

Lead AI/ML Engineer – Agentic AI & Enterprise GenAI (Contract)

Location - Sheffield or Bristol, United Kingdom (Hybrid – 2 Days Onsite)

Long-Term Project

New Enterprise AI Transformation Programme

About the Role

We are looking for an experienced Lead AI/ML Engineer to join a newly formed AI engineering team delivering large-scale enterprise AI and Generative AI solutions for a strategic transformation programme.

This role is ideal for a hands-on engineering lead with strong experience building production-grade AI platforms, Agentic AI systems, enterprise RAG solutions, and cloud-native ML infrastructure.

The successful candidate will play a key role in shaping the architecture, engineering standards, and delivery approach for next-generation AI capabilities across the organisation.

Key Responsibilities

• Design and develop enterprise-scale Agentic AI and Multi-Agent systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or similar.
• Build scalable Retrieval-Augmented Generation (RAG) pipelines integrating structured and unstructured enterprise data sources.
• Develop production-ready LLM applications using Azure OpenAI, Azure AI Foundry, Vertex AI, or equivalent platforms.
• Lead implementation of robust MLOps and LLMOps practices including CI/CD, model deployment, monitoring, governance, and observability.
• Architect cloud-native AI solutions using containerized microservices, Kubernetes, Docker, and event-driven architectures.
• Implement AI safety controls, evaluation frameworks, hallucination detection, and governance standards.
• Build reusable AI/ML components and scalable deployment pipelines across Dev, Test, and Production environments.
• Collaborate closely with architects, platform engineers, data teams, and business stakeholders.
• Provide technical leadership and mentoring across the AI engineering team.

Required Skills & Experience

• Strong experience in AI/ML Engineering, Machine Learning Platform Engineering, or Generative AI Engineering roles.
• Proven experience delivering enterprise-grade Generative AI solutions in production environments.
• Deep hands-on expertise in:
• Agentic AI
• Multi-Agent orchestration
• RAG architectures
• LLMOps / MLOps
• Vector databases and embeddings
• AI evaluation frameworks
• Strong experience with:
• Python
• LangGraph
• LangChain
• Semantic Kernel
• Hugging Face
• MLflow / Kubeflow
• Cloud expertise in one or more:
• Azure AI Foundry
• Azure OpenAI
• Azure Machine Learning
• Vertex AI / GCP
• Experience with:
• Docker
• Kubernetes
• CI/CD pipelines
• Microservices architecture
• Event-driven systems
• Experience working within enterprise or regulated environments.
• Excellent stakeholder communication and leadership skills.

Desirable Skills

• Experience with NeMo Guardrails or AI safety frameworks.
• Exposure to Energy, Utilities, Telecom, or Financial Services sectors.
• Azure or Google Cloud certifications.
• Experience implementing AI observability and monitoring solutions.

Working Arrangement

• Hybrid working model
• 2 days onsite in either Sheffield or Bristol
• Long-term programme engagement
• Opportunity to help build a new AI engineering capability from the ground up