Generative AI Lead

Birlasoft; Hyderabad; On-site; INR 400,000 - 600,000; Full time

Job summary

Birlasoft is seeking a GenAI Sr Lead to architect and deliver GenAI applications across multiple locations including Noida, HYD and Bengaluru. You will lead design, development, and integration of large-scale data workflows.

You will work with Python, tools, cloud platforms, LLM fine-tuning, LLMOps, and collaboration with data scientists to produce impactful solutions. The role emphasizes responsible AI and cross-functional teamwork, with mentorship expectations.

Qualifications

• 6+ years of experience required.
• Experience building GenAI applications from scratch.
• Proficiency with Python and large-scale data architectures.
• Experience with cloud platforms and MLOps.

Responsibilities

• Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.
• Develop Python code for GenAI solutions.
• Design architectures for large-scale data handling and transformation.
• Implement OCR/document intelligence solutions using cloud tools.
• Integrate APIs using REST/SOAP and other protocols.
• Collaborate with data scientists, engineers, and product managers.

Skills

Python

Large-scale data

Multimodal LLMs

Fine-tuning (PEFT/LoRA)

Frontend integration

Data modernization

OCR/Document intelligence

API integration

Cloud platforms

LLMOps

Responsible AI

RAG architectures

Data curation automation

Technical documentation

Collaboration

Mentorship

Tools

React

Streamlit

AG Grid

Azure

AWS

GCP

REST

SOAP

Job description

Job Description:

Area(s) of responsibility

Job Title: GEN AI Sr Lead

Location - Noida/HYD/Bengaluru/Pune/Chennai/Mumbai

Experience Required - 6+ years Only

Application Development

Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.

• Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.
• Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
• Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
• Fine-tune SLM(Small Language Model) for domain specific data and use cases.
• Front-End Integration: Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with GenAI backends.
• Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications.
• OCR and Document Intelligence: Develop solutions for Optical Character Recognition (OCR) and document intelligence using cloud-based tools.
• API Integration: Use REST, SOAP, and other protocols to integrate APIs for data ingestion, processing, and output delivery.
• Cloud Platform Expertise: Leverage Azure, GCP, and AWS for deploying and managing GenAI applications.
• Fine-Tuning LLMs: Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases.
• LLMOps Implementation: Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.
• Responsible AI Practices: Ensure ethical AI practices are embedded in the development process.
• RAG and Modular RAG: Implement Retrieval-Augmented Generation (RAG) and Modular RAG architectures for enhanced model performance.
• Data Curation Automation: Build tools and pipelines for automated data curation and preprocessing.
• Technical Documentation: Create detailed technical documentation for developed applications and processes.
• Collaboration: Work closely with cross-functional teams, including data scientists, engineers, and product managers, to deliver high-impact solutions.
• Mentorship: Guide and mentor junior developers, fostering a culture of technical excellence and innovation.