Description

You will design, scale, and maintain highly available infrastructure for LLM training, fine-tuning, and inference workloads.

This role is on-site.

Responsibilities

• Architect and implement agentic AI systems for automated alert triage, root cause analysis, and self-healing.
• Optimize GPU utilization, cluster health, and orchestration across Kubernetes-based environments.
• Define and monitor AI-specific SLOs/SLIs such as latency, throughput, and cost efficiency.
• Ensure reliability of vector databases and RAG pipelines for AI data processing.
• Integrate AI-driven incident management with ChatOps and enforce security guardrails for GenAI systems.

Required Skills

• 8–10 years of experience in Site Reliability Engineering, DevOps, or AI/ML infrastructure roles.
• Strong expertise in Kubernetes and cloud platforms (AWS, GCP, or Azure).
• Proficiency in infrastructure automation using Terraform and CI/CD pipelines.
• Proven experience with GenAI/LLM systems and orchestration frameworks like LangChain or AutoGen.
• Experience building reliable, scalable AI platforms and vector databases.
• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.

Key Skills

Education

Any Graduate