Principal - Architecture

LTM; Maharashtra; On-site; INR 3,600,000 - 6,000,000; Full time

Job summary

LTM is seeking a Senior GenAI Architect in Maharashtra to design and lead enterprise-scale Generative AI solutions aligned with business and technology strategies. You will architect end-to-end AI platforms leveraging LLMs, RAG, agentic AI and retrieval-augmented knowledge graphs, and lead cloud deployments on Azure, AWS, or GCP.

You will define standards, governance, and MLOps/LMMOps pipelines, mentor teams, and collaborate with stakeholders to drive GenAI adoption across the enterprise while

Skills

Python

Generative AI

Agentic AI

LLMs

RAG

LangChain

LangGraph

Semantic Kernel

AutoGen

Vector Databases

Azure OpenAI

AI Foundry

MLOps

LLMOps

Docker

Kubernetes

REST APIs

CICD

Cloud Architecture

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

Vector Databases

Azure OpenAI

AI Foundry

MLOps

LLMOps

Docker

Kubernetes

Job description

Role Description

• Design and lead enterprisescale Generative AI solutions aligned with business and technology strategies
• Design and lead enterprisescale Generative AI solutions aligned with business and technology strategies
• Architect endtoend AI platforms leveraging Large Language Models LLMs Agentic AI and RetrievalAugmented Generation RAG
• Develop scalable AI applications and services using Python and modern AI frameworks
• Define architecture standards best practices and governance for GenAI implementations
• Lead the design of multiagent systems using LangChain LangGraph Semantic Kernel and AutoGen
• Architect vector database solutions and enterprise knowledge retrieval platforms
• Drive solution design workshops with business stakeholders product owners and technology teams
• Evaluate and select appropriate foundation models including GPT Llama Claude Gemini and Mistral
• Design scalable prompt engineering and model orchestration frameworks for enterprise applications
• Build secure and compliant AI solutions following Responsible AI principles and governance guidelines
• Create reusable AI accelerators frameworks and architecture blueprints
• Define API microservices and integration architectures using Python FastAPI and cloudnative technologies
• Lead cloudbased AI deployments on Azure AWS or GCP platforms
• Architect MLOps and LLMOps pipelines for model lifecycle management and continuous delivery
• Establish monitoring observability evaluation and performance optimization frameworks for GenAI solutions
• Guide teams in implementing advanced RAG Graph RAG Hybrid RAG and knowledge graph architectures
• Collaborate with data engineering teams to design scalable data pipelines for AI workloads
• Drive architecture reviews technical governance and solution assurance activities
• Conduct PoCs and innovation initiatives to assess emerging AI technologies and frameworks
• Mentor architects technical leads and engineers on GenAI architecture and Python development best practices
• Define enterprise security privacy compliance and risk mitigation strategies for AI platforms
• Support presales activities technical proposals solution estimation and customer presentations
• Provide thought leadership in AI transformation initiatives and enterprise modernization programs
• Stay current with advancements in GenAI multimodal AI AI agents and foundation models

Required Skills

• Python
• Generative AI
• Agentic AI
• LLMs
• RAG
• LangChain
• LangGraph
• Semantic Kernel
• AutoGen
• Vector Databases
• Azure OpenAI
• AI Foundry
• MLOps
• LLMOps
• Docker
• Kubernetes
• REST APIs
• CICD
• and Cloud Architecture