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Country/Region:  IN
Requisition ID:  35793
Work Model: 
Position Type: 
Salary Range: 
Location:  INDIA - NOIDA - BIRLASOFT OFFICE SEZ

Title:  Generative AI Lead

Description: 

Area(s) of responsibility

  1. 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. 

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