Generative AI Lead

Birlasoft•INDIA - NOIDA - BIRLASOFT OFFICE SEZ, IN•On-site
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About the Role

Area(s) of responsibility - Job Title: DataScience GEN AI Lead Location: Noida/Pune/Bengaluru/Chennai/Mumbai Experience: 6-8 years Mode - Hybrid Role - Fulltime JOB DESCRIPTION: The Technical Lead will focus on the development, implementation, and engineering of GenAI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Technical Lead will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.     Required Skills :  1.    Python Programming: Deep expertise in Python for building GenAI applications and automation tools.  2.    Productionization of GenAI application beyond PoCs – Using scale frameworks and tools such as Pylint,Pyrit etc.  3.    LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.  4.    Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.  5.    Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.  6.    Fine-tune SLM(Small Language Model) for domain specific data and use cases.  9.    Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development.  10.    Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications.  11.    Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods.  12.    LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.  13.    Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.  14.    RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.  15.    Data Modernization: Expertise in modernizing and transforming data for GenAI applications.  17.    API Integration: Experience with REST, SOAP, and other protocols for API integration. <div class="