Architect, deploy, and operate scalable, secure production environments (AWS preferred).
Lead reliability improvements across multiple engineering streams.
Design and evolve Kubernetes-based infrastructure, including migration and optimisation initiatives.
Build and enforce strong Infrastructure-as-Code standards.
Define and operationalise SLIs, SLOs, and error budgets.
Strengthen observability across applications, infrastructure, data pipelines, and ML systems.
Work closely with product and data teams to integrate model analytics and product telemetry into reliability insights.
Work across and optimise the entire CI/CD pipeline, from build to deploy to rollback.
Improve release safety, deployment frequency, and predictability of SLAs.
Lead incident response for complex cross-system failures and drive postmortems.
Reduce operational toil through automation and platform engineering improvements.
Design processes and tooling to absorb, standardise, and troubleshoot customer environments.
Support and productionise ML workloads (MLOps practices including model deployment, monitoring, retraining workflows).
Ensure infrastructure aligns with enterprise-grade security and regulatory requirements.
Mentor engineers and raise the overall reliability bar across teams.

Extensive hands-on experience in SRE or Production Engineering roles.
Demonstrated experience building or scaling SRE practices in high-growth or complex environments.
Deep expertise in AWS or Azure-based cloud infrastructure.
Strong experience with Kubernetes (including migration, scaling, and production hardening).
Advanced Infrastructure-as-Code experience (Terraform or equivalent).
End-to-end CI/CD pipeline design and optimisation experience.
Strong experience with observability tooling across distributed systems.
Experience troubleshooting complex multi-tenant or customer-hosted environments.
Experience supporting production data platforms and ML systems.
MLOps experience, including model deployment and monitoring.
Strong understanding of distributed systems, scalability, and fault tolerance.
Systems thinker who understands interactions across infrastructure, product, data, and ML.
Excellent communication skills and ability to work cross-functionally.

Staff Site Reliability Engineer

Key skills