Lead AI Engineer

Lead AI Engineer Overview

This role is for an experienced Lead AI Engineer who will help design, build, and operationalise advanced artificial intelligence, machine learning, and generative AI solutions at enterprise scale. The position is centred on turning AI concepts and prototypes into production-ready business capabilities, with a strong focus on reliability, responsible deployment, and measurable business value. The successful candidate will help shape the practices, controls, and technical foundations needed to move AI from experimentation into live use across client environments.

What you will do

• Lead the design and delivery of complete AI and machine learning systems, covering the full lifecycle from data preparation and model development through to deployment, feature stores, model management, and monitoring.
• Build and apply modern generative AI and agentic AI approaches using tools and frameworks such as ADK, LangGraph, Microsoft Agent Framework, LlamaIndex, and similar technologies.
• Translate business AI opportunities into practical data and AI architecture choices, selecting suitable cloud services across major hyperscale platforms.
• Guide multi-disciplinary teams in delivering complex technical solutions and coordinating work across different specialisms.
• Architect and implement generative AI solutions, including retrieval-augmented generation pipelines, agent-based workflows, and orchestration of large language models on Azure, GCP, or AWS.
• Embed safety, evaluation, and assurance controls throughout the AI lifecycle so that solutions are ethical, explainable, and responsible.
• Work with product managers, data scientists, and business stakeholders to ensure AI solutions create real business impact.
• Create client-ready demonstrations and proof-of-value materials, support proposals, and provide technical deep-dives to help shape and win work.
• Develop reusable assets and frameworks that speed up delivery across multiple accounts and strengthen internal capability.
• Contribute to internal communities, thought leadership, blog content, and accelerator development in emerging areas such as agentic AI, LLM operations, and evaluation frameworks.

What you will bring

• Experience in a major consulting firm, or in an industry role with a consulting mindset, including the ability to succeed in a matrixed organisation and gain commitment from peers when selling and delivering solutions.
• Experience working with both technical and non-technical client sponsors to shape requirements collaboratively and turn them into working solutions.
• A strong track record of designing and implementing MLOps strategies and frameworks, along with delivering AI and machine learning solutions at scale from concept through to production.
• Deep knowledge of generative AI and agentic AI, including retrieval-augmented generation, embeddings, evaluation harnesses, and orchestration frameworks.
• Experience designing cloud-native data and AI architectures using Azure, GCP, AWS, and/or Databricks.
• The ability to demonstrate how scaling AI can create business value and measurable impact.

Technical experience and skills

The team works with a broad range of technologies, and you do not need to know every tool listed. What matters most is a strong foundation, a good mix of relevant skills, and the curiosity and adaptability to learn new tools as project needs evolve. The team values self-driven people who learn quickly and enjoy working in a fast-moving environment.

• Experience deploying and scaling AI solutions on at least one major cloud platform, such as Azure, GCP, or AWS, using services like Azure Foundry, AI Studio, OpenAI, AKS, Vertex AI, Cloud Run, Bedrock, or SageMaker.
• Experience building and automating AI and machine learning pipelines with tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow, or Google ADK.
• Practical experience with generative and agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar tools.
• Ability to design and implement retrieval-augmented generation pipelines, agent workflows, MCP, and integrations with LLM APIs such as OpenAI, Anthropic, Hugging Face, or equivalent services.
• Proficiency with CI/CD and containerisation tools, including GitHub Actions, Azure DevOps, Docker, and Kubernetes.

Nice-to-have knowledge

• Familiarity with methods for evaluating AI system performance, including prompt testing, A/B testing, and quality assessment frameworks.
• Understanding of modern data patterns such as lakehouse architectures, vector databases, and relational or NoSQL data stores.
• Familiarity with API gateways, event streaming, and general integration patterns.

Working environment and culture

The organisation describes itself as a team of ambitious technology professionals who enjoy bringing the latest innovations into real client production environments. Work spans both public and private sector clients, and the emphasis is on delivering technology that has visible, practical impact. The company highlights a culture of experimentation, curiosity, and innovation, with in-house projects that showcase what can be achieved using the newest models and agentic frameworks.

There is a strong commitment to diversity and inclusion, with active efforts to create an environment where people can bring their whole selves to work. The company also aims to support work-life balance and says flexible working is part of everyday working life for UK employees. Employee wellbeing is treated as a priority, supported by trained Mental Health Champions and wellbeing apps such as Thrive and Peppy. The business also places importance on social impact, including reducing its carbon footprint and improving access to the digital world.

The company notes that it has been recognised as a Glassdoor Best Place to Work in the UK for two consecutive years and has been named one of the world’s most ethical companies by the Ethisphere Institute for ten years in a row.

Working pattern and location

The role has an office base location, but the company says the successful candidate must be fully flexible about assignment location because the work may involve periods away from home at short notice. Hybrid working is embedded in the organisation, and all UK employees can request flexible working arrangements.

Pay and other details

• The contract is permanent.
• The role is for an experienced professional.
• The posting lists London, Newcastle upon Tyne, Birmingham, and Bristol as location options in the UK.
• The role is part of the Data & AI professional community.
• The reference code is 404560.
• The posting date shown on the page is 25 August 2026.

Eligibility

Applicants must have lived in the UK for the last five years in order to be eligible to apply for this position.

To apply, candidates should use the application process provided on the page, including the standard apply option and the LinkedIn application route where available.

Degree Requirement: Not Specified

Visa Sponsorship May be