Genai Python Lead Delhi (India)

Role & responsibilities Application Development: Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, etc. Python Programming: Develop high-quality, productive, and maintainable Python code for GenAI solutions. Implement Retrieval-Augmented Generation (RAG) & Modular RAG architectures for enhanced model performance. Familiarity with Multi-Modal LLM Applications. Fine-tune SLM(Small Language Model) for domain specific data and use cases. Cloud Platform Expertise: Leverage Azure, GCP, and AWS for deploying and managing GenAI applications. Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications. 8.Front-End Integration: Implement user interfaces using front-end technologies ensuring seamless integration with GenAI backends. Fine-Tuning LLMs techniques & LLMOps Implementation. Mentorship: Guide and mentor junior developers, fostering a culture of technical excellence and innovation. Preferred candidate profile Deep expertise in Python for building GenAI applications and automation tools. Productionization of GenAI application beyond PoCs Using scale frameworks and tools. LLM Frameworks: Proficiency in LLM frameworks like Autogen, Crew.ai. experienced in implementing architectures for handling large-scale structured and unstructured data. Experience with REST, SOAP, and other protocols for API integration. 6.Fine-tune SLM(Small Language Model) for domain specific data and use cases. Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc. Anti-hallucination and anti-gibberish tools such as Bleu etc. Front-End Technologies: Robust knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development. Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications. Advanced skills in RAG and Modular RAG Expertise in modernizing and transforming data for GenAI applications. .