Generative AI Developer

Role Overview: As a GEN AI Developer, you will be responsible for developing GenAI applications and solutions from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. You will work on Python programming to create high-quality, efficient, and maintainable code for GenAI solutions. Additionally, you will design and implement architectures for handling large-scale structured and unstructured data, as well as work on multi-modal LLM applications and front-end integration using technologies like React, Streamlit, and AG Grid. Key Responsibilities: - Develop GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Write high-quality, efficient, and maintainable Python code for GenAI solutions. - Design and implement architectures for handling large-scale structured and unstructured data. - Work on multi-modal LLM applications including text chat completion, vision, and speech models. - Fine-tune SLM (Small Language Model) for domain-specific data and use cases. - Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid for seamless integration with GenAI backends. - Design and implement data modernization and transformation pipelines to support GenAI applications. - Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases. - Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring. - Ensure ethical AI practices are embedded in the development process. Qualification Required: - Deep expertise in Python programming for building GenAI applications and automation tools. - Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Experience in designing and implementing architectures for handling large-scale structured and unstructured data. - Familiarity with multi-modal LLM applications including text chat completion, vision, and speech models. - Strong knowledge of front-end technologies like React, Streamlit, AG Grid, and JavaScript. - Extensive experience with cloud platforms such as Azure, GCP, and AWS for deploying and managing GenAI applications. - Mastery of fine-tuning techniques like PEFT, QLoRA, and LoRA. - Strong knowledge of LLMOps practices for model deployment, monitoring, and management. - Expertise in implementing ethical AI practices and ensuring compliance with regulations. - Proficiency in OCR and document intelligence using cloud-based tools. - Experience with API integration using REST, SOAP, and other protocols. - Ability to build automated data curation and preprocessing pipelines. - Strong collaboration and communication skills to work effectively with cross-functional teams. Role Overview: As a GEN AI Developer, you will be responsible for developing GenAI applications and solutions from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. You will work on Python programming to create high-quality, efficient, and maintainable code for GenAI solutions. Additionally, you will design and implement architectures for handling large-scale structured and unstructured data, as well as work on multi-modal LLM applications and front-end integration using technologies like React, Streamlit, and AG Grid. Key Responsibilities: - Develop GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Write high-quality, efficient, and maintainable Python code for GenAI solutions. - Design and implement architectures for handling large-scale structured and unstructured data. - Work on multi-modal LLM applications including text chat completion, vision, and speech models. - Fine-tune SLM (Small Language Model) for domain-specific data and use cases. - Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid for seamless integration with GenAI backends. - Design and implement data modernization and transformation pipelines to support GenAI applications. - Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases. - Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring. - Ensure ethical AI practices are embedded in the development process. Qualification Required: - Deep expertise in Python programming for building GenAI applications and automation tools. - Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Experience in designing and implementing architectures for handling large-scale structured and unstructured data. - Familiarity with multi-modal LLM applications including text chat completion, vision, and speech models. - Strong knowledge of front-end technologies like React, Streamlit, AG Grid, and JavaScript. - Extensive experience with cloud platforms such as Azure, GCP, and AWS for deploying and managing GenAI applications. - Mastery of fine-tuning t