Key Responsibilities:

- Design, implement, and manage end-to-end application DevOps pipelines

- Build and maintain CI/CD pipelines using Azure DevOps for automated deployments and releases

- Manage Development, Staging, and Production environments with rollback and release strategies

- Deploy, monitor, and scale applications on Google Cloud Platform (GCP)

- Containerize applications using Docker and orchestrate workloads using Kubernetes (GKE preferred)

- Implement Infrastructure as Code (IaC) using Terraform

- Manage IAM roles, permissions, and cloud security best practices in GCP

- Configure and manage API gateways, rate limiting, logging, and monitoring solutions

- Deploy and manage AI agents and AI-powered applications in production environments

- Support AI/ML pipelines including LLM configuration, model deployment, and inference workflows

- Configure and manage Google AI Studio environments

- Monitor infrastructure and application performance to ensure high availability and reliability

- Troubleshoot deployment, infrastructure, and production issues proactively

- Collaborate with development and AI/ML teams for seamless delivery and integration

- Support distributed systems and cloud-native architecture initiatives

Required Skills & Qualifications:





- 3+ years of hands-on experience in Google Cloud Platform (GCP) DevOps environments

- Strong experience managing live production deployments and cloud infrastructure in GCP

- Expertise in Azure DevOps and CI/CD pipeline implementation

- Solid knowledge of Docker and Kubernetes (GKE preferred)

- Hands-on experience with Terraform and Infrastructure as Code practices

- Experience managing cloud networking, IAM, security policies, and access controls

- Knowledge of monitoring, logging, and observability tools

- Experience configuring API gateways, rate limiting, and cloud-native services

- Hands-on exposure to AI agents, AI/ML pipelines, and model deployment workflows

- Experience working with Google AI Studio and LLM configurations

- Strong troubleshooting, analytical, and problem-solving skills

- Understanding of distributed systems and high-availability architecture

- Good communication and collaboration abilities

Preferred Skills:

- Experience with AI/ML production environments and inference pipelines

- Familiarity with cloud-native DevOps practices and automation

- Exposure to scalable microservices architecture

- Experience handling large-scale production workloads

- Immediate joiners preferred

📌 Google Cloud DevOps Engineer (GCP DevOps Engineer) (Chennai)
🏢 Important Business
📍 Chennai