At a Glance
- Tasks: Lead the design and development of innovative AI solutions that drive business success.
- Company: Join M&G, a pioneering financial services firm with over 175 years of innovation.
- Benefits: Enjoy flexible working, competitive salary, generous leave, and comprehensive health coverage.
- Other info: Be part of a diverse team committed to innovation and continuous improvement.
- Why this job: Make a real impact in AI while shaping the future of financial technology.
- Qualifications: Strong experience in AI, machine learning, and software engineering required.
The predicted salary is between 74295 - 90805 £ 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.
As a Senior AI Engineer within the M&G Life Technology team, you will play a leading role in the design, development, deployment, and optimisation of enterprise AI solutions that deliver measurable business outcomes. Working closely with Product Owners, Architects, Data Engineers, Security teams, and Business stakeholders, you will help shape the future of AI adoption across M&G by building scalable, secure, and responsible AI capabilities.
We are seeking experienced AI Engineering professionals to join the team on a 12-month fixed term basis to support us through a period of exciting business and technological growth. Successful candidates will combine strong software engineering expertise with deep knowledge of artificial intelligence, machine learning, and generative AI technologies. The role requires a product-led mindset, ensuring that solutions are technically robust, aligned to business value, and designed for operation within a regulated financial services environment.
As a member of the Technology team, you will contribute to experimentation, innovation, engineering excellence, and the development of enterprise AI capabilities that improve customer outcomes, operational efficiency, decision-making, and developer productivity.
Key Responsibilities
- AI Solution Delivery
- Partner with the AI Product Owner during discovery activities to assess feasibility, shape solution options, and contribute to product roadmaps and prioritisation.
- Translate business challenges into scalable technical solutions through MVPs, proofs of concept, and production-ready implementations.
- Contribute to product vision, user stories, acceptance criteria, and technical architecture decisions.
- Support experimentation and rapid innovation while maintaining engineering quality and governance standards.
- AI Engineering & Generative AI
- Design, develop, deploy, and optimise AI-powered applications, APIs, copilots, agents, and intelligent automation solutions.
- Develop Retrieval-Augmented Generation (RAG) architectures, prompt engineering frameworks, vector search solutions, and enterprise knowledge retrieval capabilities.
- Integrate Large Language Models (LLMs) into enterprise applications, business processes, and engineering workflows.
- Build and maintain agentic AI solutions using orchestration frameworks such as LangChain, Semantic Kernel, and equivalent technologies.
- Evaluate emerging AI technologies and recommend appropriate adoption strategies.
- Implement evaluation frameworks and guardrails to measure model quality, safety, reliability, and business effectiveness.
- Software Engineering & Platform Delivery
- Apply modern software engineering principles including automated testing, source control, CI/CD, infrastructure-as-code, observability, resilience, and security-by-design.
- Build scalable cloud-native applications, APIs, microservices, and data pipelines using modern engineering frameworks and patterns.
- Collaborate with platform engineering teams to enable AI capabilities across enterprise platforms and developer ecosystems.
- Develop reusable frameworks, libraries, patterns, and standards to accelerate AI adoption across engineering teams.
- Contribute to AI-assisted software development practices and developer productivity initiatives.
- MLOps, Monitoring & Production Operations
- Implement MLOps practices supporting model lifecycle management, deployment automation, testing, monitoring, and continuous improvement.
- Build and maintain observability, telemetry, and analytics capabilities for AI solutions.
- Monitor model performance, usage patterns, and business outcomes using defined KPIs and OKRs.
- Implement model evaluation, drift detection, performance monitoring, and AI safety controls.
- Investigate and resolve production issues to ensure reliability, resilience, and operational effectiveness.
- Data Governance, Security & Responsible AI
- Collaborate with Data Engineering teams to prepare, manage, and govern high-quality datasets for AI solutions.
- Ensure all AI solutions comply with enterprise security, governance, privacy, risk, regulatory, and responsible AI requirements.
- Support explainability, auditability, lineage, and transparency requirements for AI systems.
- Develop and implement AI guardrails and governance controls throughout the full AI lifecycle.
- Work with data governance and cataloguing platforms such as Microsoft Purview, Databricks Unity Catalog, or equivalent technologies.
- Business Value & Adoption
- Build AI solutions that deliver measurable business outcomes and support KPI and OKR definition and tracking.
- Develop dashboards, measurement frameworks, and reporting mechanisms to quantify business value and adoption.
- Support training, user enablement, go-live activities, and change adoption initiatives.
- Gather user feedback and continuously improve AI products through iterative enhancement.
- Collaboration, Leadership & Capability Development
- Partner with Product Owners, Architects, Business Analysts, Data Engineers, Risk teams, and operational stakeholders to solve complex business challenges.
- Provide technical leadership and mentoring to engineers adopting AI capabilities.
- Contribute to AI communities of practice, engineering standards, and capability development initiatives.
- Promote innovation, experimentation, and continuous improvement across engineering teams.
- Share knowledge, best practices, and lessons learned to foster organisational AI capability growth.
Required Skills & Experience
- Technical Skills
- AI & Machine Learning
- Strong hands-on experience in Machine Learning, Generative AI, Large Language Models (LLMs), Agentic AI, and Decision Intelligence systems.
- Experience designing and implementing:
- Retrieval-Augmented Generation (RAG)
- Prompt engineering frameworks
- AI agents and copilots
- Vector databases and embeddings
- Enterprise search and knowledge retrieval systems
- Strong understanding of model evaluation, model selection, guardrail design, responsible AI, and AI governance.
- Software Engineering
- Strong software engineering experience using Python, Java, C#, or similar languages.
- Experience building production-grade applications, APIs, and cloud-native services.
- Experience applying automated testing, CI/CD, infrastructure-as-code, and DevSecOps practices.
- Knowledge of containerisation and orchestration technologies such as Docker and Kubernetes.
- Understanding of enterprise integration patterns and API-first architectures.
- Platforms & Tooling
- Experience with one or more of:
- AI APIs, including OpenAI, Anthropic, Google Gemini
- Azure tooling, including Microsoft Foundry, Azure AI Services, Azure Machine Learning
- Databricks
- LLM and ML Frameworks, such as LangChain, LangGraph, Semantic Kernel, PyTorch, TensorFlow
- M365 Copilot including Copilot Studio
- GitHub Enterprise tooling, including GitHub Copilot
- Model Hosting, including Hugging Face
- Azure DevOps
- Experience with cloud platforms, preferably Microsoft Azure.
- Financial Services & Regulatory Experience
- Experience delivering solutions within regulated environments such as insurance, pensions, investments, banking, or asset management.
- Understanding of governance, operational resilience, security, auditability, risk management, and data privacy requirements.
- Experience building solutions that meet regulatory and responsible AI expectations.
- Behavioural Competencies
- Strong analytical and problem-solving capability.
- Excellent communication and stakeholder management skills.
- Ability to explain complex technical concepts to both technical and non-technical audiences.
- Product- and outcome-oriented mindset focused on delivering measurable value.
- Collaborative approach with experience working in agile, cross-functional teams.
- Passion for innovation, continuous learning, and engineering excellence.
Desirable Experience
- Experience implementing enterprise-scale AI solutions in production environments.
- Experience with AI observability tooling and model monitoring platforms.
- Knowledge of service design and customer-centred product development.
- Experience with Power Platform and AI-enabled automation solutions.
- Familiarity with Microsoft Purview, Unity Catalog, or equivalent governance platforms.
- Knowledge of AI ethics, regulatory requirements, and responsible AI practices.
What Success Looks Like
- Delivery of secure, scalable, and measurable AI solutions that achieve business outcomes.
- Successful deployment of AI capabilities into production with high levels of reliability, observability, and governance.
- Increased organisational productivity through responsible AI adoption.
- Demonstrable business value measured through defined KPIs and OKRs.
- Strong compliance with governance, privacy, security, and regulatory standards.
- Growth of enterprise AI capability through mentoring, reusable assets, and technical leadership.
What we offer:
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.
To explore more about life at M&G and our full benefits offering, visit Life at M&G.
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 & Machine Learning
Senior AI Engineer - FTC in Edinburgh employer: Prudential Distribution
M&G is an exceptional employer that prioritises employee wellbeing and professional growth, offering a comprehensive benefits package including an 18% pension scheme, generous annual leave, and extensive family support policies. Our inclusive culture fosters collaboration and innovation, ensuring that every team member feels valued and empowered to contribute to our mission of providing confidence in financial solutions. Located in the heart of the UK, we embrace flexible working arrangements, making it easier for you to balance your personal and professional life while thriving in your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer - FTC in Edinburgh
✨Get Involved in Open-Source Projects
Diving into open-source projects is a brilliant way to showcase your skills and connect with other developers in the community. Not only will you beef up your GitHub profile but you might also catch the eye of someone at Prudential Distribution who values hands-on experience over just theory.
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We think you need these skills to ace Senior AI Engineer - FTC in Edinburgh
Some tips for your application 🫡
Show Off Your Tech Skills:Make sure your CV highlights your tech stack and any programming languages you’re proficient in. Include specifics about any frameworks or technologies you’ve worked with; they can make you stand out in the sea of applicants. It’s all about showing that you have the chops we need at Prudential Distribution!
Portfolio 2.0:Since you’re applying for a temporary gig, it’s super important to showcase a portfolio that highlights your best projects. Include links to GitHub or any personal projects that demonstrate what you can do in a real-world environment. This gives us a taste of your style and your problem-solving approach!
Keep It Brief and Relevant:With a temporary position, we want to see your ability to hit the ground running. Be concise in your CV and cover letter; stick to experiences that directly relate to the role. Highlight any previous temporary roles or freelance gigs that show your adaptability and quick learning!
Tailor Your Cover Letter:Don’t just send a generic cover letter. Personalise it for Senior AI Engineer - FTC at Prudential Distribution! Mention why this temporary role excites you and how you see yourself contributing in the short run. Show us what you've got and why you're the one for this quick turn-around!
How to prepare for a job interview at Prudential Distribution
✨Nail the Technical Skills
For a software engineering role, you'll likely face technical questions or coding tasks during your interview. Brush up on the relevant programming languages and frameworks that Prudential Distribution uses, and don’t forget to practice some coding challenges on platforms like LeetCode or HackerRank. Showing your coding prowess can really make you stand out!
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✨Demonstrate Your Adaptability
Since this is a temporary role, you'll want to emphasise your ability to hit the ground running. Highlight experiences where you quickly adapted to new technologies or teams. Let’s make it clear to the interviewers at Prudential Distribution that you can learn on the job and deliver results in a short timeframe!
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Make sure to have a portfolio or GitHub ready showcasing your projects. Having tangible evidence of what you've done—be it personal projects, contributions to open-source, or previous work—can convey how capable you are. Tailor this for what might interest Prudential Distribution, so it's relevant and sparks conversation during your interview.