At a Glance
- Tasks: Lead a high-performing AI engineering team and deliver innovative AI solutions.
- Company: Dynamic data & AI practice with a focus on growth and innovation.
- Benefits: Competitive salary, bonus, hybrid working, and comprehensive benefits.
- Other info: Client-facing role with opportunities to influence AI roadmaps and solutions.
- Why this job: Shape the future of AI while leading a talented team in a collaborative environment.
- Qualifications: Strong AI/ML production experience and solid engineering skills in Python.
The predicted salary is between 80000 - 100000 £ per year.
£130,000 - £160,000 + 10-15% Bonus + Benefits
Hybrid Working, can be based out of Edinburgh, Manchester, London.
We’re working with a growing data & AI practice looking for someone to lead the next phase of their AI engineering capability. This role sits at the intersection of consulting and hands-on engineering — ideal for someone who can move between senior stakeholder conversations and deep technical delivery without losing credibility in either.
What you’d be doing:
- Leading and developing a high-performing AI engineering team
- Setting engineering standards and ensuring quality across multiple client engagements
- Translating complex AI concepts into clear, practical direction for business and technical audiences
- Architecting and delivering production-grade AI solutions (ML + newer generative/agent-based approaches)
- Acting as a trusted advisor in shaping AI roadmaps, solution design, and delivery approaches
What matters for this role:
- Strong experience taking AI/ML solutions into production environments
- Solid engineering foundations (Python and modern data/ML ecosystems)
- Familiarity with cloud-based AI platforms and scalable data systems
- Experience with deployment practices (automation, monitoring, reliability, etc.)
- Ability to operate in ambiguity and guide decision-making with structure and clarity
This is a client-facing leadership role suited to someone who enjoys building teams, shaping solutions, and staying close to emerging AI capabilities. If you're curious, feel free to reach out for a confidential conversation.
AI Engineering Lead in Slough employer: MBN Solutions
As an AI Engineering Lead at our innovative data and AI practice, you will thrive in a dynamic work culture that values collaboration and creativity. With hybrid working options available in vibrant cities like Edinburgh, Manchester, and London, we offer competitive salaries, performance bonuses, and a commitment to employee growth through continuous learning opportunities. Join us to lead a high-performing team and make a meaningful impact in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineering Lead in Slough
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like MBN Solutions!
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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 MBN Solutions.
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We think you need these skills to ace AI Engineering Lead 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 MBN 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 MBN 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 MBN 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 MBN 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.
