GEN AI

Tata Consultancy Services Limited; Hyderabad; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Tata Consultancy Services Limited is seeking a Full Stack Software Development Engineer to design and build GenAI-powered solutions for conversational AI, knowledge retrieval, and insights delivery. The role spans cloud and on-prem environments, with emphasis on scalable microservices, REST APIs, and secure productionization.

You will craft end-to-end GenAI pipelines, manage LLM agents, integrate across platforms, and implement AI safety guardrails while enabling robust observability and

Qualifications

• Strong proficiency in Java/J2EE and Spring Boot for building scalable enterprise-grade applications.
• Proficiency in Python for AI/ML workflows and GenAI tasks.
• Experience delivering distributed systems and microservices architectures.

Responsibilities

• Design and develop LLM-powered apps for conversational AI, knowledge retrieval and insights delivery.
• Build end-to-end GenAI pipelines including prompt engineering and RAG.
• Develop and manage LLM agents (tool usage, function calling) and integrations across environments.
• Implement evaluation frameworks for accuracy, latency, safety, and governance.
• Ensure AI safety, guardrails and prompt injection prevention.
• Develop multimodal conversational experiences and scalable backend services.
• Maintain observability for latency, token usage, and cost.

Skills

Java/J2EE

Spring Boot

REST APIs

Python

Distributed systems

Tools

LangChain

LangGraph

Semantic Kernel

Vector DBs

Job description

This is a Full Stack Software Development Engineer role within a team building customer- and workforce-facing

conversational AI solutions, responsible for building next-generation conversational AI, intelligent search, and

knowledge systems that power customer and associate experiences across multiple channels. This role requires

hands-on expertise in designing, developing, and productionizing scalable, secure, and enterprise-grade GenAI

solutions across cloud and on-premise environments.

Key Responsibilities

• Design and develop LLM-powered applications for conversational AI, knowledge retrieval, and insights delivery
• Build and orchestrate end-to-end GenAI pipelines, including prompt engineering, RAG, and agent-based workflows
• Develop and manage LLM agents (tool usage, API integration, function calling)
• Integrate LLMs across cloud and on-prem/open-source environments
• Implement evaluation frameworks covering accuracy, hallucination, latency, safety, and validation (LLM-as-judge, human-in-loop)
• Apply AI safety and guardrails, including prompt injection prevention and response validation
• Optimize models using prompt tuning, embeddings, and fine-tuning techniques
• Develop multimodal conversational experiences (text and voice)
• Build scalable backend services using microservices and REST APIs
• Enable observability (latency, token usage, cost, drift, quality monitoring)
• Contribute to POCs, experimentation, and adoption of emerging GenAI technologies

Required Skills

Core Engineering

• Strong proficiency in Java / J2EE, Spring Boot, RESTful APIs
• Strong proficiency in Python for AI/ML and GenAI workflows
• Experience in building distributed systems and microservices architectures

GenAI & LLM Expertise

• Hands-on experience with LLM frameworks (LangChain, LangGraph, Semantic Kernel) and RAG-based knowledge retrieval systems
• Strong understanding of prompt engineering, workflow orchestration, and agent-based systems (tool usage, function calling)
• Experience with vector databases, embeddings, and semantic search
• Experience working with LLMs across cloud platforms and on-prem/open-source models
• Strong understanding of hallucination mitigation, AI safety, guardrails, and prompt injection prevention
• Knowledge of PII handling and governance/compliance framework