About Us

At Xelix, we work with some of the world’s largest companies to automate and strengthen their financial controls. Our AI solutions redefine how Accounts Payable teams operate – moving from manual processes to automated, intelligent workflows.

Xelix is a fast-paced scale-up – things move fast and expectations are high. We raised our Series B with Insight Partners in June 2025 and are expanding aggressively. We have a team of over 150 talented people pulling together to achieve our goals. Everyone is trusted to take ownership, move fast, and have a meaningful impact. We prioritise personal and professional growth, keep things fun, and love to celebrate a milestone together.

In this role you’ll grow, be challenged and help shape the future of Xelix. If you’re excited about building something special with us, we’d love to hear from you.

About the Role

We are looking for a Senior DevOps Engineer to take ownership of the reliability, scalability, and security of our infrastructure. This role is for someone who has spent a decade or more building and operating production systems end-to-end — from cloud infrastructure and CI/CD pipelines through to databases, messaging, and the operational needs of machine learning workloads. You will be a technical anchor for the team, setting standards for infrastructure-as-code, security, and operational excellence, while remaining deeply hands-on with the platform day to day.

You’ll need to be based in or around London and able to work from our office several days a week, working closely with engineering, data, and security teams.

What You'll Be Doing

• Design, build, and operate our cloud infrastructure on AWS, with a strong focus on container orchestration (ECS and EKS) and reliable, scalable production services.
• Own our Infrastructure-as-Code estate in Terraform, driving consistent, version-controlled, repeatable provisioning across environments.
• Build and maintain CI/CD pipelines using GitHub Actions, enabling teams to ship safely and frequently.
• Operate and tune production RDS/Aurora databases, including performance, backups, migrations, partitioning, and scaling strategies.
• Support ML Ops needs: help productionise machine learning workloads and ensure the ML infrastructure is reliable, observable, and cost-effective.
• Write Python for automation, tooling, and infrastructure glue code across the platform.
• Champion DevSecOps practices — embedding security into the pipeline, managing secrets, enforcing least-privilege access, and working with engineering teams to remediate vulnerabilities early.
• Build and improve monitoring, alerting, and incident response so issues are caught and resolved before they become outages.
• Mentor other engineers, contribute to architecture decisions, and help shape the team’s technical standards and roadmap.
• Participate in on-call rotation and take ownership of incidents affecting production systems.