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About the role
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.
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