GenAI Technical Lead

Tata Consultancy Services; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Tata Consultancy Services in Bengaluru, India seeks a GenAI Technical Lead to design and implement Generative AI workflows, architecting scalable solutions with LangChain, LangGraph, and Google ADK, and integrating LLMs into enterprise apps.

You will lead Python-based development for prompts, tool agents, and data pipelines, and deploy GenAI workloads across cloud services while mentoring a small AI engineering team.

Qualifications

• 7–10 years of hands-on GenAI experience in a lead role.
• Strong experience in Python-based development and API design.
• Proven ability to architect scalable cloud-native GenAI solutions.

Responsibilities

• Design, architect, and implement Generative AI workflows and agents using LangChain, LangGraph, or Google ADK.
• Integrate LLMs into enterprise systems and custom applications.
• Define and implement retrieval-augmented generation (RAG) pipelines using vector databases.
• Architect scalable and secure GenAI microservices leveraging cloud-native components.
• Lead Python-based development for prompt orchestration, tool agents, and data pipelines.
• Develop and deploy APIs or microservices integrating LLMs with enterprise data sources.
• Implement prompt optimization, context management, and model performance tuning.
• Architect, deploy, and monitor GenAI workloads on AWS, GCP, or other hyperscalers.
• Lead a small team of AI engineers and developers; conduct code reviews and mentor juniors.
• Collaborate with product owners, data engineers, and business stakeholders to translate requirements into technical solutions.

Skills

Python

LangChain

LangGraph

Google ADK

LLM integration

RAG & embeddings

Vector databases

PEFT/LoRA

REST APIs

Security & compliance

AI ethics

AI architecture

Tools

Docker

Kubernetes

Git

CI/CD

FastAPI

Flask

React

Streamlit

Gradio

API Gateway

DynamoDB

Vertex AI

SageMaker

Bedrock

Lambda

Job description

Greetings from Tata Consultancy Services (TCS)!!!

Job Title : GenAI Technical Lead

Experince : 7- 10 Years

Mode of Interview : Virtual

Key Responsibilities:

1. Solution Design

• Design, architect, and implement Generative AI workflows and agents using frameworks such as LangChain, LangGraph, or Google ADK.
• Integrate LLMs (e.g., Llama, Gemini, GPT, Claude) into enterprise systems and custom applications.
• Define and implement retrieval-augmented generation (RAG) pipelines using vector databases (e.g., ChromaDB, Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
• Architect scalable and secure GenAI microservices leveraging cloud-native components.

2. Development & Implementation

• Lead Python-based development efforts for building prompt orchestration, tool agents, and data pipelines.
• Develop and deploy APIs or microservices integrating LLMs with enterprise data sources.
• Implement prompt optimization, context management, and model performance tuning.
• Architect, deploy, and monitor GenAI workloads on one hyperscaler:
• GCP (Vertex AI, Document AI, AlloyDB, BigQuery, Cloud Run)
• AWS (Bedrock, SageMaker, Lambda, API Gateway)
• Manage cloud infrastructure for scaling AI models, ensuring cost efficiency and compliance.
• Lead a small team of AI engineers and developers.
• Conduct code reviews, enforce best practices, and mentor junior engineers.
• Collaborate closely with product owners, data engineers, and business stakeholders to translate business needs into technical requirements.
• Contribute to internal GenAI capability building and reusable assets for the organization.

Required Skills & Experience:

• Core Technical Skills
• Python (advanced proficiency; ability to build APIs, pipelines, and modular frameworks).
• Hands-on with at least one GenAI framework:
• LangChain, LangGraph, or Google ADK (AI Development Kit).
• Expertise with LLM integration (OpenAI API, Gemini API, Ollama, Hugging Face, etc.).
• Experience with RAG, embeddings, and vector databases.
• Familiarity with PEFT, LoRA, or prompt fine-tuning approaches.
• Cloud / Hyperscaler Expertise (at least one required)
• AWS – Bedrock, SageMaker, Lambda, API Gateway, DynamoDB
• Other Desirable Skills
• Knowledge of REST APIs, JSON, and FastAPI/Flask frameworks.
• Familiarity with data governance, PII handling, and AI ethics principles.
• Understanding of Docker/Kubernetes, CI/CD, and Git-based version control.
• Exposure to front-end integration with AI chat agents (React, Streamlit, Gradio, etc.) is a plus.