Description

Lead the design, implementation, and operation of scalable infrastructure platforms supporting AI/LLM-based solutions for enterprise clients.

This role is on-site.

Responsibilities

• Own end-to-end infrastructure architecture below the application layer, including compute, container orchestration, CI/CD, observability, and security.
• Architect and manage production-grade Kubernetes environments (AKS/EKS), including cluster operations, RBAC, and GPU infrastructure provisioning (NVIDIA A100/H100).
• Design and operationalize RAG pipelines, covering ingestion, chunking, embedding workflows, and vector database management.
• Drive Infrastructure-as-Code adoption using Terraform and GitOps practices (ArgoCD/Flux) and build CI/CD pipelines with GitHub Actions and Azure DevOps.
• Establish observability standards using Datadog, OpenTelemetry, and ELK/OpenSearch, while leading incident response and InfoSec review processes.

Required Skills

• 5–8 years of experience in Platform Engineering, SRE, or Infrastructure Engineering.
• 3+ years of proven experience delivering and leading infrastructure for AI/LLM-based production systems.
• Strong hands-on expertise in Kubernetes, Docker, and Helm.
• 3+ years of experience with Terraform and GitOps tools (ArgoCD/Flux).
• 3+ years of experience with Azure services, including Key Vault, Monitor, and DevOps Pipelines.
• 3+ years of experience leading client-facing technical engagements and managing multiple concurrent projects.
• Hands-on experience with incident management in SLA-driven environments.
• Strong understanding of vector databases, RAG pipelines, and LLM inference systems.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Preferred Skills

• Experience with AWS alongside Azure, or familiarity with Azure API Management and AKS.
• Experience with Pulumi (Python/TypeScript) or knowledge of NIM deployment and lifecycle management.

Key Skills

Education

Bachelor’s degree