Cloud Infrastructure & DevOps Engineer

We’re seeking an experienced Cloud Infrastructure & DevOps Engineer to architect, automate, and manage our cloud-native platform backend.
You’ll be responsible for setting up and maintaining scalable infrastructure using Kubernetes, Docker, and serverless services (AWS Lambda, etc.), enabling seamless data processing, AI workflows, and application deployment.

This role is ideal for someone who loves designing robust, automated, high-availability cloud systems and can bridge development with infrastructure.

Key Responsibilities

• Design and manage scalable cloud infrastructure using AWS, Azure, or GCP.
• Deploy and maintain Kubernetes clusters (EKS/AKS/GKE) for containerized applications and ML workflows.
• Implement serverless functions (AWS Lambda, Azure Functions, or Google Cloud Functions) for automated triggers and background processing.
• Build and manage CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins) for deploying code and infrastructure.
• Containerize applications using Docker and manage deployments via Helm or Terraform.
• Automate infrastructure provisioning using IaC tools like Terraform, Pulumi, or AWS CloudFormation.
• Set up observability and logging (CloudWatch, Prometheus, Grafana, ELK Stack).
• Monitor and optimize cloud resources for cost, performance, and scalability.
• Collaborate with developers and data teams to support backend and AI workflows.
• Ensure security best practices (IAM roles, VPCs, encryption, least privilege access).

Required Skills

• Strong experience with AWS (EKS, EC2, S3, Lambda, IAM, CloudWatch) or equivalent cloud services (Azure/GCP).
• Hands-on with Kubernetes (Helm charts, scaling, deployments, namespaces, GPU nodes, monitoring).
• Proficiency in Docker and container management.
• Experience with CI/CD pipelines and Infrastructure as Code (Terraform or CloudFormation).
• Familiarity with serverless architectures (AWS Lambda / Azure Functions).
• Scripting in Python, Bash, or Node.js for automation.
• Understanding of networking, load balancing, security groups, and VPCs.

Nice to Have

• Experience with data or AI/ML pipelines (e.g., SageMaker, MLflow, Kubeflow, Airflow).
• Exposure to distributed systems or high-performance data workflows.
• Familiarity with monitoring and cost optimization in large-scale cloud environments.
• Interest in working with geospatial data (not required but a plus).

Who You Are

• You love building scalable, automated systems that “just work.”
• You think in infrastructure-as-code and believe manual setup is a bug.
• You enjoy optimizing systems for performance, cost, and reliability.
• You’re comfortable taking ownership of end-to-end cloud architecture.

Job Type: Full-time

Pay: ₹300,000.00 - ₹500,000.00 per year

Work Location: In person