Agentic AI Architect

Tata Consultancy Services; Hyderabad, Delhi, Mumbai; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Tata Consultancy Services is seeking an Agentic AI Architect with 10+ years of AI/Gen AI experience to lead design and implementation of advanced Gen AI solutions in enterprise environments.

You will architect scalable, secure systems, collaborate with cross-functional teams, and drive production deployments across cloud platforms using LangChain, LLMs, and modern MLOps practices.

The role requires hands-on coding in Python or R and a strong SDLC and DevOps mindset.

Qualifications

• 10+ years of AI/Gen AI architecture experience.
• Proven experience in architecting Gen AI systems in production environments.
• Strong coding in Python or R with ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with cloud-based AI services (AWS, Azure, GCP).
• Solid SDLC/DevOps understanding.

Responsibilities

• Design scalable Gen AI architectures for enterprise use cases.
• Lead deployment of AI solutions in production environments.
• Evaluate Gen AI platforms and Agentic AI approaches (RAG, MCP, Vector DBs).
• Collaborate with cross-functional teams to solve complex business challenges using AI.

Skills

AI/Gen AI

LLMs

Python/R

Cloud platforms

SDLC/DevOps

LangChain

Microservices

API integration

Model deployment

Secure solutions

Tools

LangChain

MLFlow

LangGraph

Vector databases

Job description

Agentic Ai Architect

Experience Range

10 to 18 years

Job Description

• 10+ years of experience
• 5+ years in AI/Gen AI
• Proven experience in architecting and deploying AI/Gen AI systems in production environments
• Ability to design scalable, robust, and secure solutions with a focus on Gen AI
• Comprehensive knowledge about Gen AI platforms and architecting integrated solutions
• Large Language Models (LLMs), and other advanced AI technologies
• Understanding of microservices, APIs and integration with existing systems
• Expertise in designing Gen AI solutions for enterprise use cases
• Proficiency in Python or R, along with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn)
• Experience with cloud-based AI services (e.g., AWS, Azure, GCP) for building scalable AI solutions
• Solid understanding of software development lifecycle (SDLC) and DevOps practices
• Experience of LangChain, Phoenix, MLFlow, LangGraph, Google Agent Development Kit
• Experience of designing AI solutions using Agentic AI approach, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Vector Databases, etc.
• Comprehensive knowledge to assess and evaluate Agentic AI and Generative AI applications
• Excellent problem-solving skills and the ability to tackle complex business challenges using AI technologies