Senior AI Engineer (FTC)
3 days ago
Edinburgh
• 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, • 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, • 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, • 8% non-contributory pension plus up to 5% matching, • Life Assurance & Death in Service, • Support, feedback and development programmes to help you reach your full potential, • Flexible culture and ways of working, • Focus on health & wellbeing, • 30 days holiday as standard (excluding bank holidays), with the ability to purchase an additional 5 days, • Time off when you need it includes carer’s leave, faith leave, grandparent leave and career breaks, • New parents receive up to 26 weeks of full pay while on leave, • 4-week back-to-work transition for new parents: work 80% of your contractual hours, be paid for 100%, • New parents can take family leave in flexible blocks within the first year of birth/adaoption Experience designing and implementing:AI agents and copilotsStrong hands-on experience in Machine Learning, Generative AI, Large Language Models (LLMs), Agentic AI, and Decision Intelligence systemsEnterprise search and knowledge retrieval systemsStrong understanding of model evaluation, model selection, guardrail design, responsible AI, and AI governanceVector databases and embeddingsRetrieval-Augmented Generation (RAG)Prompt engineering frameworksExperience applying automated testing, CI/CD, infrastructure-as-code, and DevSecOps practicesUnderstanding of enterprise integration patterns and API-first architecturesKnowledge of containerisation and orchestration technologies such as Docker and KubernetesExperience building production-grade applications, APIs, and cloud-native servicesStrong software engineering experience using Python, Java, C#, or similar languagesExcellent communication and stakeholder management skillsPassion for innovation, continuous learning, and engineering excellenceExperience delivering solutions within regulated environments such as insurance, pensions, investments, banking, or asset managementProduct- and outcome-oriented mindset focused on delivering measurable valueUnderstanding of governance, operational resilience, security, auditability, risk management, and data privacy requirementsExperience building solutions that meet regulatory and responsible AI expectationsBehavioural CompetenciesStrong analytical and problem-solving capabilityAbility to explain complex technical concepts to both technical and non-technical audiencesCollaborative approach with experience working in agile, cross-functional teamsAI APIs, including OpenAI, Anthropic, Google GeminiAzure tooling, including Microsoft Foundry, Azure AI Services, Azure Machine LearningDatabricksLLM and ML Frameworks, such as LangChain, LangGraph, Semantic Kernel, PyTorch, TensorFlowGitHub Enterprise tooling, including GitHub CopilotM365 Copilot including Copilot StudioAzure DevOpsModel Hosting, including Hugging FaceExperience implementing enterprise-scale AI solutions in production environmentsExperience with AI observability tooling and model monitoring platformsKnowledge of service design and customer-centred product developmentExperience with Power Platform and AI-enabled automation solutionsFamiliarity with Microsoft Purview, Unity Catalog, or equivalent governance platformsKnowledge of AI ethics, regulatory requirements, and responsible AI practices #J-18808-Ljbffr