Generative AI Lead

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.