Agentic AI Engineer

Tata Consultancy Services; Hyderabad, Chennai District, Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Tata Consultancy Services seeks an experienced Agentic AI Architect to lead the design and implementation of enterprise-scale AI solutions powered by Generative AI, LLMs, Agentic AI, and RAG architectures.

The role focuses on autonomous reasoning, workflow orchestration, and business process automation while ensuring security, governance, and responsible AI practices across platforms such as Azure OpenAI, AWS Bedrock, and Google Vertex AI.

Qualifications

• 8+ years of overall IT experience.
• 3+ years in Generative AI or AI Architecture roles.
• Strong expertise in Agentic AI, Multi-Agent Systems, Generative AI, LLM Architectures.
• Hands-on experience with LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, OpenAI APIs.
• Proficiency in Python, REST APIs, Microservices and Event-Driven Architecture.
• Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, SageMaker, Vertex AI.

Responsibilities

• Design end-to-end Agentic AI architectures for enterprise business use cases.
• Develop scalable, secure AI architecture frameworks and patterns.
• Define enterprise AI reference architectures, standards, and governance models.
• Lead AI modernization and digital transformation initiatives.
• Design autonomous AI agents capable of planning, memory management, reasoning, and task execution.
• Build multi-agent orchestration frameworks using modern Agentic AI platforms.
• Implement agent collaboration, tool calling, workflow automation, and decision-making capabilities.
• Design HITL mechanisms for governance and validation.
• Evaluate, deploy, and optimize LLMs including GPT, Claude, Gemini, Llama, Mistral, and open-source models.
• Design prompt engineering, prompt chaining, and agent workflow frameworks.
• Architect RAG solutions; implement semantic search, vector retrieval, embeddings, and knowledge systems.
• Establish LLM evaluation and optimization strategies.

Skills

Agentic AI

Multi-Agent Systems

Generative AI

LLM Architectures

Machine Learning

Deep Learning

Python

REST APIs

Microservices

Event-Driven Architecture

Kubernetes

Docker

CI/CD

Infrastructure as Code

LangChain

LangGraph

Semantic Kernel

OpenAI APIs

Azure AI Foundry

Tools

LangChain

LangGraph

Semantic Kernel

CrewAI

AutoGen

OpenAI APIs

Azure AI Foundry

Azure OpenAI

AWS Bedrock

SageMaker

Vertex AI

Job description

We are seeking an experienced Agentic AI Architect to lead the design and implementation of enterprise-scale AI solutions powered by Generative AI, LLMs, Agentic AI, Multi-Agent Systems, and RAG architectures. The ideal candidate will architect intelligent AI ecosystems capable of autonomous reasoning, planning, decision-making, workflow orchestration, and business process automation while ensuring security, governance, scalability, and responsible AI practices.

Key Responsibilities

AI Solution Architecture

• Design end-to-end Agentic AI architectures for enterprise business use cases.
• Develop scalable, secure, and reusable AI architecture frameworks and patterns.
• Define enterprise AI reference architectures, standards, and governance models.
• Lead AI modernization and digital transformation initiatives.

Agentic AI & Multi-Agent Systems

• Design autonomous AI agents capable of planning, memory management, reasoning, and task execution.
• Build multi-agent orchestration frameworks using modern Agentic AI platforms.
• Implement agent collaboration, tool calling, workflow automation, and decision-making capabilities.
• Design Human-in-the-Loop (HITL) mechanisms for governance and validation.

Generative AI & LLM Engineering

• Evaluate, deploy, and optimize LLMs including GPT, Claude, Gemini, Llama, Mistral, and open-source models.
• Design advanced prompt engineering, prompt chaining, and agent workflow frameworks.
• Architect Retrieval-Augmented Generation (RAG) solutions.
• Implement semantic search, vector retrieval, embeddings, and knowledge systems.
• Establish LLM evaluation and optimization strategies.

Cloud & AI Platform Engineering

• Architect AI solutions using:
• Azure OpenAI
• Azure AI Foundry
• AWS Bedrock
• Amazon SageMaker
• Google Vertex AI
• Integrate AI agents with enterprise applications, APIs, data platforms, and business workflows.
• Design event-driven and microservices-based AI architectures.

Data & Knowledge Management

• Design enterprise knowledge repositories and AI knowledge management frameworks.
• Implement vector databases including Pinecone, Weaviate, Chroma, Milvus, and Azure AI Search.
• Define ingestion, chunking, indexing, embedding, and retrieval strategies.
• Ensure data governance, lifecycle management, and knowledge quality standards.

AI Governance & Security

• Define Responsible AI governance frameworks.
• Implement AI guardrails, security controls, and compliance mechanisms.
• Address risks related to hallucinations, prompt injection attacks, data privacy, and regulatory compliance.
• Establish enterprise AI governance and model risk management practices.

LLMOps / AgentOps / MLOps

• Design and implement AI deployment pipelines and automation frameworks.
• Establish observability, monitoring, and AI performance evaluation frameworks.
• Define AI KPIs, operational metrics, and continuous improvement processes.
• Support production-scale AI operations and governance.

Required Skills

• 8+ years of overall IT experience.
• Minimum 3+ years of experience in Generative AI or AI Architecture roles.
• Strong expertise in:
• Agentic AI
• Multi-Agent Systems
• Generative AI
• LLM Architectures
• Machine Learning
• Deep Learning
• RAG Architectures
• Hands-on experience with:
• LangChain
• LangGraph
• Semantic Kernel
• CrewAI
• AutoGen
• OpenAI APIs
• Azure AI Foundry
• Strong proficiency in:
• Python
• REST APIs
• Microservices
• Event-Driven Architecture
• Experience working with:
• Azure OpenAI
• Azure AI Services
• AWS Bedrock
• Amazon SageMaker
• Google Vertex AI
• Experience with:
• Kubernetes
• Docker
• CI/CD
• Infrastructure as Code

Preferred Skills

• Knowledge Graphs and semantic reasoning systems.
• Enterprise Architecture and Digital Transformation experience.
• AI Security and Responsible AI frameworks.
• Data Governance and Regulatory Compliance.
• LLMOps, AgentOps, and MLOps implementation experience.
• Financial Services, Insurance, Healthcare, or Enterprise Platform experience.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• AWS Certified Machine Learning Specialty
• Google Professional Machine Learning Engineer
• Databricks Generative AI Certification
• TOGAF Certification
• Certified Kubernetes Administrator (CKA)

Desired Candidate Profile

• Strategic thinker with strong AI architecture expertise.
• Experience leading enterprise AI transformation initiatives.
• Ability to engage with CXOs and senior business stakeholders.
• Strong leadership, mentoring, and team-building capabilities.
• Excellent analytical, communication, and problem-solving skills.
• Proven track record delivering enterprise-scale Generative AI and Agentic AI solutions.