DevOps Engineer

Overview

Hands-on DevOps Engineer to operate and scale large self-managed Kubernetes environments on GCP and run the company's centralized observability stack, while building internal developer-productivity tools.

What you'll do

• Operate and scale large self-managed Kubernetes environments on GCP, including workloads and databases.
• Manage cloud infrastructure using Terraform, Helm, and other Infrastructure as Code tools.
• Run and scale the centralized observability stack for high-volume metrics, logs, dashboards, and alerting.
• Build and improve internal developer-productivity, deployment, alerting, and access-request tools.
• Work with developer, backend, frontend, security, and platform teams to reduce friction and improve release reliability.
• Troubleshoot production issues, automate repetitive work, and maintain platform-security best practices.
• Use LLMs and AI tooling efficiently for troubleshooting, automation, documentation, and improving engineering workflows.
• Write clear documentation and guide teams on DevOps best practices.

What you'll need

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Strong hands-on Kubernetes experience.
• Cloud experience with GCP, AWS, or Azure; GCP is strongly preferred.
• Experience with Helm and at least one IaC tool, such as Terraform or Crossplane.
• Strong experience with open-source observability tools; Grafana is required.
• Moderate proficiency in Python, Bash, or PowerShell.
• Experience with Docker and container-based application deployment.
• Understanding of cloud and platform security best practices.

Nice to have

• Experience with large managed or self-managed Kubernetes clusters.
• Prometheus, Loki, Victoria or ELK/OpenSearch experience.
• Experience operating self-managed infrastructure or open-source platforms.
• Experience improving developer productivity, internal tooling, or engineering environments.
• Experience using LLMs or AI coding assistants to solve real engineering problems.
• Experience supporting data engineering or data science teams.

Details

• Location: Bangalore.