Senior DevOps Engineer

Responsibilities:

• Design, develop, and maintain backend services using Golang, ensuring high code quality, performance, and maintainability.
• Participate in system design and architectural discussions, including service boundaries, data flow, scalability, and reliability trade-offs.
• Build, deploy, and operate applications on Google Kubernetes Engine (GKE):
  • Package and deploy applications using Helm charts
  • Configure resources, autoscaling, health checks, and rollout/rollback strategies
  • Troubleshoot production issues related to performance, stability, networking, and resource usage
• Manage cloud infrastructure (GCP) using Terraform (Infrastructure as Code):
  • Create, maintain, and review Terraform modules
  • Ensure consistent and reliable environments across development, staging, and production
• Improve system reliability, observability, and security:
  • Implement and use logging, metrics, tracing, and alerting
  • Participate in incident response, root cause analysis, and post-incident improvements
• Collaborate closely with product, DevOps, and engineering teams to deliver secure, production-ready solutions.

Requirements & Qualifications:

• 6+ years of experience in backend or platform engineering in production environments.
• Solid understanding of distributed systems concepts such as scalability, reliability, retries, timeouts, and consistency.
• Strong hands-on experience with GKE / Kubernetes, including:
  • Core Kubernetes resources (Deployments, Services, Ingress, ConfigMaps, Secrets)
  • Deploying and managing applications using Helm charts
  • Debugging and operating production workloads
• Strong understanding of GCP core services, including IAM, VPC, Subnets, Cloud NAT, VPN, Load Balancing, Cloud DNS, Cloud Logging, Cloud Run and Monitoring.
• Practical experience with Terraform for infrastructure provisioning and management.
• Experience with CI/CD pipelines and cloud-native application operations.
• Strong proficiency in Golang, including:
  • Concurrency (goroutines, channels), context handling, and error management
  • Building and maintaining APIs (REST and/or gRPC)
  • Writing clean, testable, and maintainable code
• Strong problem-solving skills and the ability to work with complex systems.
• Good communication skills and a strong sense of ownership.

Optional (Nice to Have):

• Basic knowledge of AI systems and GenAI fundamentals, including AI agents, RAG architectures, and LLM-based services.
• Familiarity with AI infrastructure concepts:
  • Model inference services
  • GPU-based workloads
  • Scaling, latency, and cost trade-offs
• Experience with service mesh (e.g., Istio)
• Familiarity with observability tools (Prometheus, Grafana, Cloud Monitoring)
• Good understanding of cloud and application security, including:
  • IAM and access control (GCP IAM, Kubernetes RBAC)
  • Secrets management and secure configuration
  • Secure service-to-service communication (mTLS)
  • Container and Kubernetes security best practices