At a Glance
- Tasks: Design and build AI platforms, automate operations, and enhance user experience.
- Company: M&G, a leading financial services company with a rich history of innovation.
- Benefits: Competitive pension scheme, 38 days annual leave, private healthcare, and flexible working options.
- Other info: Inclusive culture with opportunities for growth and support for diverse backgrounds.
- Why this job: Join a dynamic team to shape the future of AI in finance and make a real impact.
- Qualifications: Experience in cloud platforms, software engineering, and a passion for AI and automation.
The predicted salary is between 63000 - 77000 £ per year.
At M&G, our purpose is to give everyone real confidence to put their money to work. With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions.
Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions. Through telling it like it is, owning it now and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent. We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role.
The AI and Data Platforms team designs, builds and runs the platforms that enable our organisation to adopt AI and data capabilities. We own the full platform lifecycle, from architecture and engineering through to operations and continuous improvement. As an AI Platform Engineer, you’ll extend our platform capabilities, embed AI and automation into platform operations, and help teams across the business adopt AI solutions safely and effectively.
This is a hands-on engineering role that combines feature delivery with responsibility for resilience, observability, governance and measurable outcomes. You’ll work closely with Product Owners, Architects, Engineers, Security teams and business stakeholders to deliver secure, scalable and reliable platform capabilities.
Main Responsibilities
- Platform delivery
- Design, build and deliver new platform capabilities across a multi-cloud environment.
- Contribute to solution design, technical decisions and implementation.
- Build production-ready services, APIs, automation and platform components.
- Apply modern engineering practices, including automated testing, CI/CD, infrastructure as code, security by design and observability.
- Take platform capabilities from initial design through to production use and ongoing improvement.
- AI-driven platform operations
- Apply AI and agentic capabilities to improve platform operations and engineering workflows.
- Build automation and agents that support environment provisioning, onboarding, access management, fault diagnosis and remediation.
- Automate the operational lifecycle of environments, workspaces, resources, agents and permissions.
- Develop self-service capabilities that reduce manual effort while maintaining appropriate controls.
- Evaluate emerging AI capabilities and recommend practical approaches to adoption.
- Resilience, reliability and service quality
- Design solutions that remain reliable and predictable when failures occur.
- Build for known failure modes using appropriate retry, isolation, recovery and service degradation patterns.
- Test recovery processes and use the results to strengthen platform resilience.
- Implement monitoring, alerting, telemetry and operational dashboards.
- Define and track service measures that reflect user needs and platform performance.
- Investigate and resolve operational issues, continuously improving platform reliability and user experience.
- Measurement and value
- Build reporting, telemetry and analytics that provide clear visibility of platform usage, cost, performance and outcomes.
- Support the definition and tracking of KPIs, OKRs and service measures.
- Develop reporting that demonstrates adoption and business value to technical stakeholders and senior audiences.
- Use operational and user data to guide platform decisions and continuous improvement.
- Enablement and adoption
- Work with engineering, data and business teams to design, integrate and support AI use cases.
- Help teams move AI use cases into secure and reliable production environments.
- Develop reusable patterns, standards, documentation and self-service capabilities.
- Support user onboarding, enablement and go-live activities.
- Share knowledge and promote consistent engineering practices across teams.
- Gather feedback and use it to improve the platform and user experience.
- Governance, security and responsible AI
- Make sure platform capabilities align with enterprise security, governance, privacy and risk requirements.
- Support the explainability, auditability and transparency of AI-enabled capabilities.
- Apply appropriate controls and guardrails throughout the AI lifecycle.
- Work with data governance, cataloguing, lineage and access-management capabilities where required.
- Contribute to a strong control environment and support the responsible adoption of AI.
Key Knowledge, Skills and Experience
- Essential
- Demonstrable experience building and operating cloud-based platforms and services.
- Strong understanding of cloud fundamentals, including networking, identity and access management, security and operational controls.
- Strong software engineering or scripting capability, with experience working in production codebases.
- Experience using infrastructure as code, CI/CD and automated delivery practices.
- Experience developing and supporting cloud-native applications, APIs, services or platforms.
- Experience using logs, metrics, traces and telemetry to improve platform performance and reliability.
- Experience designing solutions with resilience, scalability, observability and operability in mind.
- Evidence of improving the dependability of production systems through practical engineering changes.
- A track record of delivering technology capabilities into production and supporting their ongoing operation.
- Ability to communicate complex technical concepts clearly to technical and non-technical audiences.
- A collaborative approach to working with engineering, data, security and business stakeholders.
- An interest in AI, automation and agentic systems, combined with sound judgement about where they add value.
- Desirable
- Experience building AI-powered applications, agents, copilots or intelligent automation.
- Experience with Retrieval-Augmented Generation, prompt engineering, vector search or enterprise knowledge retrieval.
- Experience with major public cloud platforms and associated AI services.
- Experience with data platform technologies and governance concepts, including metadata, lineage, cataloguing and access control.
- Experience delivering solutions in a regulated or controlled environment.
- Experience with MLOps, AI evaluation, monitoring and the operational support of AI solutions.
- Knowledge of containerisation, orchestration and API-first architecture.
- Familiarity with responsible AI, model governance and AI safety controls.
What Success Looks Like
- Delivering secure, scalable platform capabilities used by multiple business teams.
- Moving AI use cases into production with appropriate reliability, observability and governance.
- Replacing routine manual activity with controlled automation and self-service capabilities.
- Improving monitoring and alerting so the team can identify and address issues before users report them.
- Providing clear reporting on platform usage, cost, performance, adoption and outcomes.
- Increasing organisational capability through reusable assets, documentation and knowledge sharing.
- Continuously improving the reliability, efficiency and user experience of our AI and data platforms.
We’re dedicated to supporting your wellbeing and helping you thrive, both at work and beyond. Our benefits are designed to help you balance your professional and personal life, and financially plan for the future.
Our UK benefits include:
- A valuable pension scheme of up to 18% (13% made up of employer contributions and 5% employee contributions).
- Access to our Share Save and Share Incentive Plan, alongside financial wellbeing and support services to help give you real confidence to put your money to work.
- Enjoy 38 days annual leave (including bank holidays), with the opportunity to purchase up to five extra days. Our Time Off When You Need It policy gives you the flexibility - to balance work and personal commitments.
- Our market-leading Inspiring Families policy includes comprehensive support and paid parental leave covering maternity, adoption, surrogacy, and paternity leave - because supporting families is an important part of our inclusive culture.
- Health & Protection cover includes Private Healthcare, Critical Illness cover and Life Assurance for you, with additional family options - for peace of mind.
At M&G we strive to have a diverse workforce and an inclusive culture, underpinned by our policies and employee-led networks that offer networking, support and development opportunities for the diverse communities our colleagues represent. We welcome applications from people of all backgrounds – across gender, ethnicity, age, disability, sexual orientation and more – including neurodivergent individuals, career returners and those with military service experience.
M&G is proud to be Level 3: Disability Confident Leader under the UK Government Disability Confident employer scheme, and we welcome applications from candidates with disabilities and long-term health conditions. If you would like to participate in the initiative, you will have the opportunity to indicate this on your application.
We are committed to providing an inclusive recruitment process. All candidates have the opportunity to request reasonable adjustments when applying. If you need any additional support at any stage, please contact us at: careers@mandg.com
AI Platform Engineer employer: M&GPrudential
M&G is an exceptional employer that prioritises employee well-being and professional growth, offering a flexible work environment and a comprehensive benefits package including a generous pension scheme, extensive annual leave, and robust family support policies. With a commitment to diversity and inclusion, M&G fosters a collaborative culture where employees are encouraged to develop their skills and contribute to meaningful financial solutions for clients worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land AI Platform Engineer
✨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 M&GPrudential 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 M&GPrudential.
✨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 M&GPrudential.
✨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 M&GPrudential 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 AI Platform Engineer
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 M&GPrudential.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at M&GPrudential 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 M&GPrudential
✨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 M&GPrudential 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.