Lead Architect

Role Overview

Required Qualifications

• 10 - 14 years of experience in working on ML projects that includes product building mindset, strong hands on skills, technical leadership, leading development teams
• Model development, training, deployment at scale, monitoring performance for production use cases
• Strong knowledge on Python, Data Engineering, FastAPI, NLP
• Knowledge on Langchain, Llamaindex, Langtrace, Langfuse, LLM evaluation, MLFlow, BentoML
• Should have worked on proprietary and open-source LLMs
• Experience on LLM fine tuning including PEFT/CPT
• Experience in creating Agentic AI workflows using frameworks like CrewAI, Langraph, AutoGen, Symantec Kernel
• Experience in performance optimization, RAG, guardrails, AI governance, prompt engineering, evaluation, and observability
• Experience in GenAI application deployment on cloud and on-premises at scale for production using DevOps practices
• 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
  

Must Have Skills

• Product thinking that includes ideation, prototyping, and scale internal accelerators for LLMOps
• Architect and build scalable LLMOps platforms for enterprise-grade GenAI systems
• Design and manage end-to-end LLM pipelines from data ingestion and embedding to evaluation and inference
• Drive LLM-specific infrastructure: memory management, token control, prompt chaining, and context optimization
• Lead scalable deployment frameworks for LLMs using Kubernetes and GPU-aware scaling
• Build agentic AI operations capabilities including agent evaluation, observability, orchestration and reflection loops
• Guardrails & Observability: Implement output filtering, context-aware routing, evaluation harnesses, metrics logging, and incident response
• Platform Automation for LLMOps: Drive end-to-end automation with Docker, Kubernetes, GitOps, DevOps, Terraform, etc.
  

Product Thinking

GenAI Engineering