Senior Infrastructure - Platform Engineer

Hiring for Senior Infrastructure Engineer / Platform Engineer AI Platforms & GPU Infrastructure

Location: Bangalore

Job Summary:

We are looking for a hands-on Infrastructure Engineer / Platform Engineer with 8+ years of experience building and operating cloud-native platforms for Agentic AI workloads. The ideal candidate should have deep expertise in Kubernetes, Terraform, CI/CD, Infrastructure as Code, Multi-Cloud environments, and proven experience deploying Generative AI, Agentic AI, and LLM workloads on GPU infrastructure. Experience supporting production-scale AI platforms, model serving, and MLOps is essential.

Key Responsibilities:

• Design, build, and operate scalable Kubernetes platforms for AI/ML and GenAI workloads.
• Automate cloud infrastructure provisioning using Terraform and Infrastructure as Code.
• Build and maintain CI/CD pipelines and GitOps deployment frameworks.
• Deploy and manage GPU-enabled infrastructure supporting model training and inference.
• Support Large Language Models (LLMs), RAG pipelines, and Agentic AI applications in production.
• Build scalable AI serving platforms using Kubernetes-based model serving frameworks.
• Implement monitoring, observability, security, and platform reliability best practices.
• Partner with AI/ML engineers and data scientists to accelerate AI adoption.
• Drive platform automation and self-service capabilities across cloud environments.

Required Skills:

• 8+ years of experience in Platform Engineering
• Strong hands-on experience with Kubernetes in large-scale production environments.
• Expertise in Terraform and Infrastructure as Code (IaC).
• Strong experience with CI/CD, GitOps, and automation.
• Experience across AWS, Azure, and/or GCP environments.
• Strong Linux administration and troubleshooting skills.
• Proficiency in Python and/or Go.

Mandatory Experience:

• Hands-on experience deploying AI/ML, Generative AI, or Agentic AI solutions in production.
• Experience deploying and scaling LLM workloads.
• Strong experience with GPU infrastructure including NVIDIA GPUs, CUDA, GPU Operators, and model optimization.
• Experience with AI model serving platforms such as Triton Inference Server, KServe, Ray Serve, or similar.
• Experience building RAG pipelines and AI platforms.
• Experience with vector databases and AI orchestration frameworks.

Interested candidates can share their profiles on [Confidential Information].