DevOps Senior Engineer

Key Responsibilities

• Design, build and operate AWS infrastructure and shared AI Platform services, balancing security, reliability, performance and cost. Develop serverless and event-driven solutions using AWS Lambda, API Gateway, EventBridge, SQS and Step Functions. Develop reusable Terraform modules and automate cloud infrastructure provisioning across development, test and production environments. Build and optimise CI/CD pipelines using GitHub and GitHub Actions, incorporating automated testing, security scanning, approvals and rollback capabilities. Automate the packaging, deployment and monitoring of AI applications, models and agents, supporting MLOps and LLMOps workflows. Deploy, configure and troubleshoot containerised applications using Docker and Kubernetes, ensuring secure and reliable integration with enterprise platforms. Implement cloud security controls including least-privilege access, identity federation, secrets management, encryption and secure network connectivity. Establish monitoring, logging, tracing and alerting capabilities using tools such as CloudWatch, Grafana, Prometheus and Loki. Lead incident investigation, root cause analysis and operational improvements to enhance platform availability, performance and resilience. Provide technical leadership through mentoring, code reviews, documentation and collaboration with engineering, infrastructure, networking and Cyber teams. Qualifications and Experience Bachelor's degree in Computer Science, Engineering, Information Technology or equivalent industry experience. Significant hands-on experience in DevOps, platform engineering or cloud engineering, including delivering and operating production services in enterprise environments. Strong AWS experience, including Lambda, IAM, VPC networking, S3, CloudWatch and serverless or event-driven architectures. Demonstrated proficiency in Infrastructure as Code using Terraform, including reusable modules, automated provisioning and controlled infrastructure changes. Strong experience developing and managing CI/CD pipelines using GitHub and GitHub Actions, including automated testing, security controls and release management. Practical experience deploying and troubleshooting Docker and Kubernetes workloads, with strong Linux administration and networking knowledge. Strong Python and shell scripting skills, with experience developing automation, APIs and integration components. Understanding of AI/ML application lifecycles and MLOps/LLMOps practices, including deployment, monitoring and integration with AI model services. Experience implementing enterprise security and identity controls, including SSO, role-based access, secrets management and Microsoft Entra ID integration. Proven ability to lead technical delivery, troubleshoot complex production issues, mentor engineers and influence engineering standards across multidisciplinary teams.