Your work will span external cloud operations, internal dev teams CI/CD and deployment automation, AI/LLM tooling, and cloud FinOps.
In this role, you will:
Lead the design, implementation, maintenance, and improvement of our cloud infrastructure and deployments especially on Google Cloud Platform (GCP) and/or Microsoft Azure (with GCP a strong preference; experience on both is a big plus)
Own and evolve CI/CD pipelines, deployment automation, and developer tooling to streamline releases, reduce friction, and increase team velocity
Collaborate with different engineering teams to identify manual/deployment bottlenecks, build and deliver automation solutions, and improve their DevOps practices.
Execute engineering org-wide initiatives, including AI/LLM gateway tooling, internal dev tooling (e.g., Claude Code assistants), and other horizontal improvements.
Drive Cloud FinOps: monitor, analyse, and optimise cloud spend; evaluate and implement self-hosting (versus SaaS) alternatives; proactively reduce cost while maintaining reliability and scale.
Support operational practices including monitoring, alerting, incident response, backups, disaster recovery, security best practices, and infrastructure scalability.
Be the go-to DevOps partner across teams – youll rotate focus as needed among squads, enabling them to self-serve faster.
5+ years of progressive, hands-on experience in a DevOps, SRE, or Cloud Platform Engineering role (We're looking for deep expertise, not just time).
Mandatory Deep Expertise in either GCP or Azure, with a strong preference for Google Cloud Platform (GCP). Experience with both is highly desirable.
Proven experience and in-depth understanding of containerisation and orchestration specifically with Kubernetes.
Solid experience with Infrastructure as Code, particularly Terraform.
Advanced scripting proficiency (Bash and/or Python).
Experience with CI/CD tooling (GitHub, GitHub Actions, or similar).
Familiarity with internal developer tooling and developer experience improvements.
Strong analytical, troubleshooting, and operational mindset youre good at reducing manual toil, automating things, optimising cost, and monitoring production systems.
Excellent collaboration skills: able to work across engineering teams, be a trusted partner, and help raise DevOps maturity.
Preferred qualifications:
Proven track record leading FinOps/Cost Optimization initiatives that delivered tangible, measurable savings
Experience with AI/LLM tooling or developer experience/adoption of AI assistants (e.g. Claude Code, MCPs, LLM Gateways)
Knowledge of Jira, DevOps best practices, observability stacks (monitoring/alerting/logging)
Prior success operating as a sole Platform/DevOps Engineer embedded across multiple engineering teams
