At a Glance
- Tasks: Lead the design and development of AI-enabled applications and services.
- Company: Join a large consumer-focused organisation investing heavily in AI and Machine Learning.
- Benefits: Competitive salary, up to 15% bonus, flexible remote work, and career progression.
- Other info: Exciting opportunity for hands-on leadership in a growing AI environment.
- Why this job: Shape the future of AI solutions while mentoring a talented team.
- Qualifications: Strong software engineering background with experience in AI and GCP.
£85k - £90k + Up to 15% Bonus + Benefits - Permanent
Remote UK - Flexible remote working model - Occasional travel to the South-East / South London region
Must be Eligible to work in the UK - Cannot Provide Sponsorship
We're currently supporting a large consumer-focused organisation undergoing significant investment across AI, Machine Learning & Cloud Engineering capability. As part of this growth, we're looking to identify an experienced Lead AI Engineer to help shape, build and deliver scalable AI-enabled solutions across the organisation.
This role would suit someone with a strong Software Engineering background who has evolved into AI / Machine Learning Engineering and is comfortable operating across both hands-on technical delivery & technical leadership. Alongside remaining hands-on, you'll help mentor AI Engineers, establish engineering best practice and support the delivery of enterprise-scale AI solutions.
Key Responsibilities
- Design and develop AI-enabled Applications & Services
- Build scalable AI & Machine Learning solutions within a GCP environment
- Lead the technical direction of AI Engineering initiatives
- Provide technical leadership, mentoring and coaching to AI Engineers across the wider team
- Help establish engineering standards, best practice and code quality across AI Engineering
- Collaborate closely with Digital Products, AI, Data & business stakeholders
- Support the development of AI Agents and intelligent automation capabilities
- Drive Engineering best practice across cloud-native AI delivery
- Help transition AI Proof of Concepts into secure, scalable production solutions
- Contribute towards architecture, experimentation and proof-of-concept initiatives
Required Experience
- Strong Software Engineering background (Python preferred)
- Commercial AI / Machine Learning Engineering experience
- Hands-on Google Cloud Platform (GCP) experience
- Experience deploying ML / AI solutions into production environments
- Understanding of modern AI frameworks & LLM ecosystems
- Exposure to AI Agents, Agentic AI workflows and/or Google ADK highly desirable
- Strong stakeholder engagement & communication capability
- Previous technical leadership, mentoring or experience leading Engineering teams would be highly beneficial
Desirable Technologies
- GCP / Vertex AI
- Gemini
- Python
- AI Agents / ADK
- Machine Learning Frameworks
- APIs & Microservices
- Docker / Kubernetes
- CI/CD Pipelines
- LLM Orchestration Frameworks
Additional Information
- Bonus potential up to c.15%
- Opportunity to join a growing AI capability within a large-scale Enterprise environment
- Opportunity to combine hands-on AI Engineering with technical leadership and mentoring
- Excellent long-term progression potential as the AI function expands
Lead AI Engineer - GCP / Machine Learning / AI Agents employer: Mackenzie Jones IT
Mackenzie Jones IT is an excellent employer, offering a dynamic work environment in Slough that fosters collaboration and innovation. With a hybrid work model, employees enjoy the flexibility of remote work while benefiting from a supportive culture that prioritises professional growth and development. The competitive salary package, including a 10% bonus, along with comprehensive benefits, makes this an attractive opportunity for those looking to advance their careers in SAP and EDI.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer - GCP / Machine Learning / AI Agents
✨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 Mackenzie Jones IT 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 Mackenzie Jones IT.
✨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 Mackenzie Jones IT.
✨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 Mackenzie Jones IT 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 Lead AI Engineer - GCP / Machine Learning / AI Agents
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 Mackenzie Jones IT.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Mackenzie Jones IT 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 Mackenzie Jones IT
✨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 Mackenzie Jones IT 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.
