At a Glance
- Tasks: Lead the design and deployment of impactful AI solutions that transform industries.
- Company: Join Laing O'Rourke, a global leader in engineering and construction.
- Benefits: Competitive salary, career growth, and a supportive work environment.
- Other info: Be part of a dynamic team focused on meaningful projects and collaboration.
- Why this job: Make a real difference by driving innovation and sustainability through AI.
- Qualifications: Experience in AI engineering and strong communication skills required.
The predicted salary is between 80000 - 100000 £ per year.
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
Success in the role will be demonstrated through:
- 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.
AI Engineering Manager employer: Laing O'Rourke
Laing O'Rourke is an exceptional employer, offering a dynamic work environment where innovation and sustainability are at the forefront of our mission. As an AI Engineering Manager, you will be part of a forward-thinking team that values your contributions and fosters professional growth through meaningful projects that impact communities and the environment. With a commitment to engineering excellence and a culture of collaboration, we empower our employees to thrive in their careers while making a tangible difference in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineering Manager
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at Laing O'Rourke. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your AI projects. This is your chance to demonstrate your hands-on experience and problem-solving abilities. Make sure it’s easy to navigate and highlights your best work!
✨Tip Number 3
Prepare for interviews by practising common questions related to AI engineering. Think about how you can relate your past experiences to the role at Laing O'Rourke. Be ready to discuss how you’ve tackled challenges and delivered impactful solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Laing O'Rourke team. So, get that application in and let’s make some waves together!
We think you need these skills to ace AI Engineering Manager
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how motivated you are to contribute to something larger than yourself, so share your experiences and what excites you about the field!
Tailor Your Application:Make sure to customise your application to highlight your relevant skills and experiences that align with the role. We’re looking for someone who can translate business challenges into practical AI solutions, so be specific about how you've done this in the past.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your key achievements stand out. This will help us quickly see how you can add value to our team.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Laing O'Rourke!
How to prepare for a job interview at Laing O'Rourke
✨Know Your AI Stuff
Make sure you brush up on your AI and machine learning knowledge. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This role is all about delivering production-grade solutions, so show them you know your stuff!
✨Understand the Business Impact
It's crucial to connect your technical skills with business outcomes. Prepare examples of how your AI solutions have driven measurable value in previous roles. They want to see that you can translate complex problems into practical, outcome-driven solutions.
✨Showcase Your Leadership Skills
As an AI Engineering Manager, you'll be leading a team. Be ready to talk about your leadership style, how you foster a culture of quality and accountability, and any experiences where you've built high-performing teams. They’ll want to know how you can inspire and guide others.
✨Engage with Stakeholders
Strong communication and stakeholder engagement are key for this role. Think of times when you've successfully collaborated with different teams or stakeholders. Be prepared to discuss how you ensure everyone is aligned and working towards common goals.
