AI Platform Engineer: Multi-Cloud & AI Automation

M&G; Stirling; Hybrid; GBP 75,000 - 110,000; Full time

Benefits offered by this job

Pension up to 18% (employer 13% + 5%)

Share Save and Share Incentive Plan

38 days annual leave (+ option to buy

Inspiring Families policy

Private Healthcare & Life Assurance

Job summary

M&G is hiring an AI Platform Engineer to extend our multi-cloud platform, embedding AI and automation across engineering workflows. You will work with product owners, architects, security, and business stakeholders to deliver secure and scalable platform capabilities that support responsible AI adoption.

This hands-on role focuses on reliability, observability, governance and measurable outcomes, with flexible hybrid working and strong emphasis on collaboration and continuous improvement.

Qualifications

• Demonstrated experience building and operating cloud-based platforms and services.
• Strong understanding of cloud fundamentals, including networking, IAM, 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.

Skills

Cloud platforms

CI/CD

Observability

Security by design

AI adoption

Platform resilience

Team collaboration

Clear communication

Automation

Tools

Kubernetes

Infrastructure as code

Cloud-native apps

APIs

Job description

M&G is hiring an AI Platform Engineer to extend our multi-cloud platform, embedding AI and automation across engineering workflows. You will work with product owners, architects, security, and business stakeholders to deliver secure and scalable platform capabilities that support responsible AI adoption.

This hands-on role focuses on reliability, observability, governance and measurable outcomes, with flexible hybrid working and strong emphasis on collaboration and continuous improvement.