Lead DevOps Engineer - AI Infrastructure

About the role

LSEG is building scalable AI products and platforms that need reliable cloud infrastructure, efficient delivery pipelines and strong operational engineering. As a Lead DevOps Engineer you will own the technical direction of cloud infrastructure, delivery platforms and operational capabilities, staying hands-on from architecture and design through deployment, observability, incident response and continuous improvement. This is an individual contributor role with no direct reports, offering functional leadership and guidance to engineers.

Key responsibilities

• Own the technical roadmap for cloud infrastructure, DevOps, deployment and operations
• Architect, build and operate secure, observable, resilient and scalable platforms on Azure, AWS or both
• Improve CI/CD pipelines, infrastructure as code, automated testing, release controls, environment management and deployment strategies
• Work with software engineering and data science teams to productionise AI solutions at scale
• Set engineering standards and reusable patterns for infrastructure, security, observability, resilience and documentation
• Lead architectural decisions and take ownership of operational risks and incidents
• Use approved generative AI tools for infrastructure development, automation, testing, pipeline improvement, documentation and incident analysis
• Guide engineers through design reviews, code reviews, pairing and coaching

Required profile

• Significant hands-on experience in DevOps, platform engineering, cloud infrastructure or software engineering
• Strong expertise in Azure, AWS or both, in complex production environments
• Advanced experience with CI/CD, infrastructure as code, release automation and automated testing
• Experience with containerised workloads and orchestration
• Knowledge of observability, incident management, cloud security, IAM, secrets management, network security, vulnerability management and supply-chain risk
• Demonstrable experience using generative AI tools in engineering workflows, including protecting sensitive information
• Ability to work autonomously and provide technical leadership without formal management authority

Required skills

• Azure, AWS
• Terraform, Bicep, CloudFormation, Ansible or similar
• Docker and Kubernetes
• Python, Bash, PowerShell, Go or a similar language
• Bonus: AI/machine learning platforms, MLOps, GitOps, policy as code, internal developer platforms, FinOps