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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.
Role Overview
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.
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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.
Technical Skills
Required Skills & Experience
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.
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Platforms & Tooling
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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
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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
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