About this role

Design, deploy, and scale GenAI and Agentic AI applications
Build scalable systems from the ground up
Drive LLM-specific infrastructure including memory management and context optimization
Lead scalable deployment frameworks using Kubernetes and GPU-aware scaling
Build agentic AI operations capabilities
Drive end-to-end automation with Docker, Kubernetes, GitOps, DevOps, Terraform
Create evaluation pipelines including prompt orchestration and feedback loops
Implement output filtering, context-aware routing, and incident response

10
14 years of experience in working on ML projects
Strong hands on skills and technical leadership
Model development, training, deployment at scale
Strong knowledge on Python, Data Engineering, FastAPI, NLP
Knowledge on Langchain, Llamaindex, Langtrace, Langfuse, LLM evaluation, MLFlow, BentoML
Experience on LLM fine tuning including PEFT/CPT
Experience in creating Agentic AI workflows
Experience in performance optimization, RAG, guardrails, AI governance, prompt engineering
Experience in GenAI application deployment on cloud and on-premises at scale
Experience in DevOps and MLOps
Good working knowledge on Kubernetes and Terraform
Experience in minimum one cloud: AWS / GCP / Azure to deploy AI services
Team player with excellent communication and presentation skills.

Lead Architect

Key skills