At a Glance
- Tasks: Lead and innovate AI engineering while developing cutting-edge AI products.
- Company: Dynamic enterprise focused on AI solutions and innovation.
- Benefits: Competitive salary, growth opportunities, and a collaborative culture.
- Other info: Fast-paced environment with a focus on emerging technologies.
- Why this job: Shape the future of AI and make a real impact in enterprise innovation.
- Qualifications: Proven AI leadership experience and strong software engineering skills.
The predicted salary is between 63000 - 77000 £ per year.
Are you passionate about building production-grade AI solutions while shaping the future of enterprise innovation?
We're looking for an experienced
Head of AI Engineering & Innovation to lead and grow a high-performing AI function.
This is a unique opportunity to define AI strategy, drive technical innovation, and remain hands-on in developing cutting-edge AI products and solutions used by both internal teams and enterprise clients.
You’ll play a key role in influencing AI adoption, leading technical delivery, supporting business growth, and establishing best practices across AI engineering.
- What you’ll be doing
- Define and execute the organisation's AI engineering and innovation strategy.
- Lead and mentor a growing AI engineering team.
- Design, build and deliver AI-powered applications, platforms and internal tools.
- Stay hands-on with software development, architecture and technical problem-solving.
- Work closely with clients and internal stakeholders to design scalable AI solutions.
- Support pre-sales activity through technical proposals, workshops and solution presentations.
- Champion emerging AI technologies and promote innovation across the business.
- Develop reusable frameworks, accelerators and best practices that improve delivery and scalability.
- What we’re looking for
- Proven experience leading AI engineering, AI product or innovation teams.
- Strong software engineering background with experience delivering production-ready applications.
- Expert Python development skills, ideally including
Fast API .
- Strong experience with
- AWS , including services such as
Bedrock, Lambda, ECS/EKS, API Gateway and S3 .
- Hands-on experience with
Lang Chain, Lang Graph, Retrieval-Augmented Generation (RAG), vector databases and multi-agent systems .
- Experience building APIs, AI platforms and intelligent products.
- Knowledge of AI evaluation, observability and monitoring tools such as
Lang Smith, Promptfoo, Arize or MLflow .
- Understanding of AI testing, governance, safety and security best practices.
- Experience with
Docker, Kubernetes, CI/CD pipelines and modern Dev Ops practices .
- Excellent communication skills with experience engaging technical and non-technical stakeholders.
- Previous experience delivering solutions within regulated industries such as financial services, telecommunications or insurance is advantageous.
- Nice to have
- AWS Agent Core.
- MLOps and AI deployment tooling.
- Knowledge graphs and graph databases.
- Low-code, automation or integration platforms.
- Experience creating reusable developer platforms or innovation frameworks.
You’ll be successful if you...
- Enjoy balancing strategic leadership with hands-on engineering.
- Can translate complex AI concepts into practical business solutions.
- Thrive in fast-paced environments where innovation is encouraged.
- Have a commercial mindset and enjoy working closely with clients.
- Are passionate about building scalable, real-world AI solutions that deliver measurable value.
- What’s on offer
- Opportunity to shape and lead an AI engineering capability.
- Work on enterprise-scale AI products and innovation initiatives.
- Influence technical strategy and emerging technologies.
- Collaborative, forward-thinking engineering culture.
If you're excited by the opportunity to build impactful AI solutions while leading a growing engineering function, we'd love to hear from you.
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Head of Artificial Intelligence employer: Morgan McKinley
Morgan McKinley offers an exceptional work environment for a Terraform & AWS DevOps Engineer, providing the opportunity to collaborate with a leading UK insurance and financial services company. Employees benefit from a culture of innovation and support, with ample opportunities for professional growth and development in a dynamic, multi-vendor setting. The company's commitment to employee well-being and career advancement makes it an attractive choice for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Artificial Intelligence
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Morgan McKinley or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Morgan McKinley.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Morgan McKinley.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Morgan McKinley that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Head of Artificial Intelligence
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Morgan McKinley.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Morgan McKinley and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Morgan McKinley
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Morgan McKinley uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
