At a Glance
- Tasks: Lead and mentor a high-performing AI Engineering team while driving technical excellence.
- Company: Global consultancy investing heavily in AI with ambitious growth plans.
- Benefits: Competitive salary, remote work flexibility, and opportunities for professional development.
- Other info: Join an experienced leadership team and work on cutting-edge AI programmes.
- Why this job: Shape the future of AI Engineering and influence strategy in a dynamic environment.
- Qualifications: Proven experience in leading AI teams and delivering enterprise-scale AI solutions.
Job Title: Head of AI Engineering
Location: Remote/Central London (1/2 Days a month onsite)
Salary: £130,000 - £145,000
Summary:
We're looking for an experienced Head of AI Engineering to lead and scale a growing AI Engineering capability within a global consultancy's Data & AI Practice.
This is a key leadership role, combining technical leadership with people, strategy, and delivery. You'll build and develop a high-performing team, define engineering standards, and ensure the successful delivery of enterprise AI solutions, while working closely with senior leadership to shape the firm's AI strategy.
Key Responsibilities:
- Lead, grow, and mentor the AI Engineering team.
- Drive technical excellence across AI and GenAI engagements.
- Define engineering standards across AI Engineering, MLOps, LLMOps, DevSecOps, and cloud-native delivery.
- Provide technical leadership and governance across complex AI programmes.
- Support bids, proposals, solution design, and technical estimations.
- Represent the AI practice with clients and contribute to thought leadership and innovation.
What You'll Bring:
- Experience leading AI engineering teams within a consultancy or professional services environment.
- Strong expertise in LLMs, Agentic AI, AI Agents, RAG, Machine Learning, and cloud-based AI platforms.
- A track record of delivering enterprise-scale AI solutions into production.
- Strong stakeholder management and the ability to translate technical concepts into business value.
Why Join?
- Join a consultancy making significant investment in AI, with ambitious growth plans and strong executive backing.
- Play a key role in shaping the AI Engineering function, influencing strategy, technology, and team growth.
- Work on cutting-edge AI programmes alongside an experienced leadership team, helping enterprise clients deliver real business value through AI.
Head of AI Engineering in Slough employer: Lumora Solutions
At Lumora Solutions, we pride ourselves on being a leading global consultancy in Data & AI, offering our employees the chance to work on cutting-edge projects that shape the future of technology. Our remote work culture promotes flexibility and work-life balance, while our commitment to employee growth ensures that you will have access to continuous learning opportunities and career advancement. Join us to be part of a high-performing team where your expertise in data architecture will be valued and rewarded.
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We think this is how you could land Head of AI Engineering in Slough
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lumora Solutions.
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We think you need these skills to ace Head of AI Engineering in Slough
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Lumora Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lumora Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Lumora Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Lumora Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
