This is a hands-on leadership role combining technical depth with team management. You will work closely with R&D and Product to continuously improve our infrastructure, deployment processes, and production operations.
Responsibilities
Lead, mentor, and grow a team of DevOps/Infrastructure engineers, including 1:1s, career development, and performance feedback.
Own the CI/CD pipeline strategy, driving faster, safer, and more reliable deployments across services.
Design, implement, and maintain cloud infrastructure using Infrastructure as Code (e.g., Terraform, CloudFormation, Pulumi).
Lead the adoption and evolution of Kubernetes-based platforms and cloud-native microservices architectures.
Drive observability and reliability practices: monitoring, alerting, logging, incident response, and on-call rotations.
Define and enforce SLAs/SLOs, and lead root-cause analysis and postmortems for production incidents.
Partner with engineering teams to improve developer experience, build tooling, and reduce deployment friction.
Own cloud cost, capacity planning, and infrastructure scaling decisions.
Set technical roadmap and priorities for the DevOps function, in partnership with Engineering leadership.
5+ years of DevOps/SRE/Infrastructure engineering experience, including 1-2+ years leading or mentoring other engineers.
Proven track record operating production environments on Azure and AWS (multi-cloud experience strongly preferred).
Deep expertise in infrastructure as code (Terraform, CloudFormation), Kubernetes, and CI/CD tooling.
Solid understanding of cloud security principles and compliance standards (ISO 27001, SOC 2, GDPR).
Background supporting 24/7 customer-facing production environments at scale.
Experience implementing FinOps frameworks and optimizing cloud spend.
Experience working with cloud cost optimization practices.
Excellent management, communication, and cross-functional collaboration skills.
Fluent in English (spoken and written).
Advantages
Certifications in Azure, AWS, Kubernetes (CKA/CKAD), and FinOps Practitioner.
Experience with knowledge management or AI/ML-powered SaaS products.
