AI Engineering Manager

Introduction

The IT function has renewed its strategy in response to Laing O'Rourke's ambition to help transform an industry, making it more sustainable, more productive, and fit for the future.

Our opportunity is to apply technology in ways that genuinely matter, shaping how complex projects are delivered, how decisions are made, and how innovation improves outcomes for people, communities, and the environment.

The mission is clear - to create a modern, resilient technology environment, where data underpins every decision, AI enhances every process, and digital capability accelerates progress at scale.

We are building a different kind of IT function to help achieve this, one that is trusted, forward-looking, and deeply connected to the success of the business.

You will work on meaningful technical challenges, contribute to important initiatives, and grow your capability in a supportive environment. You will be trusted with responsibility, encouraged to contribute ideas, and able to see the impact of your work.

We are looking for people who are curious, thoughtful and motivated by contributing to something larger than themselves.

Role Purpose

The AI Engineering Manager is responsible for the design, development, and scaling of production-grade AI and machine learning solutions across Laing O'Rourke.

Reporting to the Principal Lead - Data & AI Solutions and Insight, this role leads a multidisciplinary team to deliver AI capabilities that automate processes, enhance decision-making, and unlock measurable business value.

You Will Ensure AI Solutions Are Engineered, Deployed, And Scaled Effectively, Working As Part Of The Wider Data & AI Operating Model

• Enterprise Data & AI Enablement - defines where and how data and AI are applied across the business
• Data & AI Solutions and Insight - builds and delivers the solutions that realise that value
• Data Platforms and Governance - provides trusted, secure, and scalable data foundations

You will be accountable for moving AI from experimentation to reliable, enterprise-scale capability, ensuring solutions are robust, secure, and embedded into operational systems.

Key Accountabilities

AI Solution Engineering and Delivery

• Lead the design, development, and deployment of AI and machine learning solutions into production
• Ensure solutions are scalable, reliable, and aligned to enterprise architecture and data platforms
• Drive the transition from experimentation to production and sustained operation

Use Case Delivery and Business Value

• Partner with the Data & AI Enablement team and business stakeholders to deliver high-value AI use cases
• Translate business challenges into practical, outcome-driven AI solutions
• Ensure clear linkage between AI delivery and measurable business outcomes

Engineering Excellence and Standards

• Establish best practices for model development, testing, deployment, and monitoring
• Implement strong MLOps and engineering discipline across AI delivery
• Promote reuse of models, components, and delivery patterns

Integration with Data Platforms

• Work closely with the Data Platforms and Governance team to ensure AI solutions are built on trusted, well-managed data
• Ensure efficient data access, integration, and performance for AI workloads

Governance and Responsible AI

• Ensure AI solutions comply with enterprise governance, security, and data standards
• Embed responsible AI practices including transparency, explainability, and ethical use
• Monitor model performance, drift, and business impact

Scaling and Operationalisation

• Ensure AI solutions are embedded into business processes and operational systems
• Drive reuse and scalability across use cases and domains
• Reduce reliance on bespoke solutions through standardisation and platform use

Leadership Contribution

• Build and lead a high-performing AI engineering team
• Develop capability in machine learning, engineering, and delivery discipline
• Foster a culture of quality, accountability, and continuous improvement
• Act as a visible and credible technical leader within the IT team

Key Measures of Success

• Successful delivery of production-grade AI solutions with measurable business impact
• Increased adoption of AI-driven automation and decision-support capabilities
• Scalable, reliable AI systems operating across multiple business domains
• Reduced time from use case definition to production deployment
• Strong collaboration with Data Enablement and Platform teams
• High-performing, engaged AI engineering team

Qualifications And Experience

Essential skills and experience

• Proven experience leading AI engineering or machine learning teams in complex environments
• Strong hands-on understanding of ML, AI engineering, and model deployment practices
• Experience delivering AI solutions into production at scale
• Strong understanding of data platforms, cloud technologies, and integration patterns
• Ability to translate business problems into AI-enabled solutions
• Strong stakeholder engagement and communication skills

Desirable Experience

• Experience with MLOps platforms and automation
• Experience operating in organisations undergoing data or digital transformation
• Familiarity with construction, manufacturing, or other asset-intensive industries

About Us

Laing O'Rourke are an international engineering and construction company delivering state-of-the-art infrastructure and buildings projects for clients in the UK, Middle East and Australia.

Certainty, reliability, quality – this is what our clients want. And at Laing O'Rourke, we have more than 150 years of experience delivering it. Laing O'Rourke's story is one of energy, passion, ambition, people and teamwork. We harness the power of our experience, stretching back over a century and a half to deliver certainty for our clients.