Description

Design, develop, and manage enterprise-grade AI and cloud infrastructure solutions on Google Cloud Platform (GCP), with a strong focus on Gemini Enterprise AI capabilities and Vertex AI services.

Support MLOps lifecycle activities including model deployment, versioning, monitoring, retraining workflows, and CI/CD for AI applications.

Create reusable templates, automation frameworks, and deployment standards for enterprise AI adoption on GCP.

Solid understanding of GCP networking concepts (VPC, Shared VPC, Cloud DNS, Load Balancing, Cloud Interconnect/VPN).

knowledge on GCP services (AI application, Pub/Sub, GCP IAM) is preferred.

Design and implement scalable infrastructure using Infrastructure as Code (IaC) on GCP. 

Develop and maintain CI/CD pipelines using tools such as Cloud Build, Jenkins, Gitlab or GitHub Actions. 

Solid understanding of Docker and Kubernetes is mandatory.

Manage and monitor cloud resources, performance, and cost optimization. 

Implement best practices in system reliability, observability, and security. 

Automate operational processes using scripting (e.g., Python, Bash,). 

Collaborate with cross-functional teams to understand system requirements and deliver infrastructure solutions. 

Ensure compliance with cloud security and governance policies.

Exposure to AWS or Azure, Sailpoint & ServiceNow is a plus.

Excellent problem solving and communication skills.

Experience with containerization and orchestration using Docker and Kubernetes (GKE preferred). 

Strong scripting skills (Python, Bash). 

Experience with monitoring and logging tools like Splunk, Prometheus, Grafana. 

Knowledge of GCP IAM, networking, VPCs, and security best practices

Key Skills

Education

Bachelor’s degree