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.
- Robust exp