Infrastructure Engineering Manager

Role overview

Cloud platform and reliability

• Own production infrastructure architecture, engineering, operations, and continuous improvement across GCP and OCI; lead production workload migration to GCP.
• Design secure, highly available, scalable, resilient platforms and set standards for compute, networking, storage, IAM, and cloud-native services.
• Own production Kubernetes and its ingress, service networking, service mesh, monitoring, and logging ecosystem.
• Build automation and self-service capabilities; establish SRE practices, SLIs, SLOs, operational metrics, and reliability improvements.
• Lead complex production troubleshooting, incident root-cause analysis, corrective action, toil reduction, and improved monitoring and early detection.

Infrastructure engineering and AI

• Drive an IaC-first model using Terraform, reusable modules, automated validation, and controlled production changes.
• Use source control, pull requests, peer review, testing, and automated deployment; use Bitbucket as the core infrastructure workflow.
• Use Claude Code and MCP servers to understand repositories, develop and review IaC, investigate issues, and automate workflows.
• Apply AI to monitoring, optimization, incident investigation, root-cause analysis, and Terraform development and review.
• Set human validation and approval requirements and ensure safe AI use around production systems, credentials, and sensitive operational data.

Services, security, and team leadership

• Oversee databases and data infrastructure, caching, messaging and middleware, Kubernetes services, networking, IAM, secrets, observability, backup, and recovery.
• Build security into infrastructure, owning IAM, network security, segmentation, secrets management, and hardening; partner with Security Engineering on risks.
• Maintain auditable infrastructure changes and guardrails and human oversight for production automation.
• Lead, mentor, and grow Infrastructure and SRE engineers; guide architecture, review solutions, and participate in complex troubleshooting.
• Partner with Product Engineering and Security, set standards, promote documentation and knowledge sharing, and coach AI-native engineering workflows.

Experience and core qualifications

• 10+ years across infrastructure, cloud, platform engineering, DevOps, or SRE; 3+ years leading relevant engineering teams.
• Proven design and operation of highly available production cloud environments; strong production Kubernetes and significant Terraform/IaC experience.
• Strong understanding of networking, IAM, security, observability, and production operations; experience leading major infrastructure migration or platform transformation.
• Substantial hands-on GCP production workload design, deployment, troubleshooting, and operation, with practical architecture and operational decision experience.
• Hands-on OCI experience and ability to operate across both OCI and GCP.

AI and engineering practices

• Daily hands-on Claude Code use, practical MCP server use, and proven AI use in software engineering, SRE, or infrastructure workflows beyond chat prompting.
• Experience applying AI across large code and infrastructure repositories, including generating, understanding, reviewing, and troubleshooting IaC and production incidents.
• Familiarity with agentic workflows such as sub-agents, reusable skills, and commands; strong judgment validating AI-generated code and keeping humans involved in critical decisions.
• Strong Git-based practices using Bitbucket; ability to demonstrate practical AI-native engineering workflows.

Technical knowledge

• Knowledge of Kubernetes, Helm, Kubernetes Operators, service mesh, cloud networking, DNS, IAM, and secrets management.
• Proficiency in Git, Bitbucket, and Linux administration; experience with observability, monitoring, logging, CI/CD, GitOps, incident management, and troubleshooting.
• Knowledge of high availability and disaster recovery practices.
• Experience with other AI coding tools such as GitHub Copilot, Cursor, or Gemini; GCP Professional Cloud Architect or Professional Cloud DevOps Engineer certification; and telecommunications, CPaaS, or messaging experience are listed as additional qualifications.

Character traits

Benefits

• Competitive salary and bonus, share scheme, 30 holiday days after the first anniversary, and a birthday day off.
• May work from anywhere in the world for up to 25 days per year.
• Paid leave for new parents.