Site Reliability Engineer

Role Summary - Site Reliability Engineer
Experience/Skills: 2+ years of experience as an SRE with strong Kubernetes and GCP expertise
Location: Bangalore (Work from office)
What are we looking for?
We are looking for a curious Site Reliability Engineer to keep our Kubernetes and GCP platform reliable, secure and cost-efficient. You are a natural tinkerer who likes understanding how systems work at a deep level, isn't afraid to experiment, and can explain technical trade-offs to engineers and non-technical stakeholders alike. You will also be our main point of contact with Google Cloud and other infrastructure providers.
Responsibilities:
Design, run and scale containerized services on Kubernetes (GKE) on GCP
Define and track SLIs and SLOs for critical services, and work with development teams to meet them
Automate deployment, scaling and infrastructure management using GitOps (ArgoCD) and Helm
Own observability: monitoring, logging and alerting
Plan capacity, optimize performance and keep GCP costs in check
Maintain disaster recovery and business continuity plans, and test them through chaos engineering and game days
Own infrastructure security for Kubernetes clusters and GCP services: IAM least privilege, network policies, secrets management, vulnerability scanning and audit logging
Document processes, runbooks, and best practices for maintaining system reliability
Participate in the on-call rotation, lead incident response, and run blameless postmortems
Use AI agents (Claude Code or similar) to write and review Terraform, Helm charts, runbooks and automation scripts
Build AI-assisted ops tooling: alert triage, log and incident summaries, and first-pass root-cause analysis on observability data
Set guardrails for AI in production: no agent gets write access to prod without review, credentials stay scoped, and every AI-driven change is auditable
Act as the primary point of contact with Google Cloud and other providers, and keep our use of their services current
Requirements:
Strong hands-on experience with Kubernetes, Docker and Helm
Solid knowledge of GCP services and best practices
Experience with GitOps (ArgoCD) and CI/CD pipelines
Strong understanding of cloud and infrastructure security: IAM, network segmentation, secrets management (e.g. Secret Manager, Vault), container image scanning, and compliance needs for financial data
Hands-on experience using AI coding tools for infrastructure work, with the judgment to spot when generated configs are wrong or insecure
Understanding of the security risks of AI tooling: prompt injection, secrets leaking into prompts, and over-privileged agents
Experience with observability tools such as Prometheus and Grafana
Deep understanding of networking: VPCs, VPNs, gateways and load balancing
Familiarity with cloud-native databases
Clear communicator, comfortable working with cloud vendors and explaining technical topics to non-technical stakeholders
Curious, fast learner with a tinkerer's mindset; personal projects or open-source contributions are a plus
CKA or Google Cloud Professional DevOps Engineer certification is a plus

Work arrangement
No