Description

Build and operate secure, scalable multi-cloud platforms (GCP and Azure) to support GenAI, LLM, and RAG workloads.

This role is hybrid.

Responsibilities

• Design and provision cloud infrastructure using Terraform, including landing zones, networking, and org policies across GCP and Azure.
• Enable MLOps and LLMOps pipelines for model deployment, monitoring, and lifecycle management using Arize AI and GenAI platforms.
• Implement platform engineering best practices, including Kubernetes abstractions (GKE/OpenShift), internal developer portals, and self-service environments.
• Establish observability, SLOs, and SRE practices to ensure reliability and performance of GenAI and platform services.
• Ensure platform security and governance using HashiCorp Vault, IAM, and policy-as-code.

Required Skills

• 5+ years of experience in cloud platform engineering.
• Strong hands-on expertise with GCP and Azure, with a preference for multi-cloud environments.
• Proficiency in Terraform for Infrastructure as Code (IaC).
• Experience with cloud networking and hybrid connectivity (VPN, VPC/VNet peering, private endpoints).
• Knowledge of Kubernetes platforms, specifically GKE and OpenShift (OCP).
• Familiarity with Platform Engineering and Internal Developer Platforms.
• Understanding of Observability, monitoring, logging, and tracing.
• Application of SRE concepts, including SLOs and SLIs.
• Proficiency in Python for automation.

Preferred Skills

• Experience with GenAI platforms, LLMs, and RAG (Retrieval Augmented Generation).
• Knowledge of MLOps/LLMOps pipelines.

Key Skills

Education

Any Gradute