Project Leader

Description

Summary: Seeking an Individual Contributor Gen AI Developer to solve real-world problems using cutting-edge Generative AI capabilities and emerging technologies. Highlights: 1. Work with cutting-edge LLM/GenAI/GPT technologies 2. Develop and deploy advanced Data Science capabilities 3. Build and deploy Generative AI solutions using Langchain and RAG **Position Summary** -------------------- Gen AI Developer with Agentic AI experience **Job Responsibilities** ------------------------ * Be an Individual Contributor in the Analytics and Development team and solve real\-world problems using cutting\-edge capabilities and emerging technologies based on LLM/GenAI/GPT * Software development experience in python is needed as backend for UI based applications * Be a part of large delivery teams working on advanced projects when expert assistance is required. * Deliver advanced Data Science capabilities to businesses in a meaningful manner through successful proof\-of\-concept solutions, and later smoothly transition the proof\-of\-concept into production. * Create Technical documents, develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms * Can interact with client on GenAI related capabilities and use cases **Education** ------------- BE/B.Tech Master of Computer Application**Work Experience** ------------------- * Require 4\-10 years experience to develop, test, and deploy Python based applications on Azure platforms * Must have basic knowledge on concepts of Generative AI / LLMs / GPT * Deep understanding of architecture and work experience on Web Technologies * Python, SQL hands\-on experience * Good to have Databricks Genie * Design and develop LLM\-based systems: * Build and deploy Generative AI solutions, often using frameworks like Langchain and techniques like Retrieval\-Augmented Generation (RAG). * Model development and fine\-tuning: Train, fine\-tune, and refine large language models to meet specific business requirements or improve performance on particular tasks. * Integration: Collaborate with cross\-functional teams to integrate LLM models into broader applications and products. * Prompt engineering: Develop and implement effective prompts to guide the LLM and improve the accuracy and relevance of its outputs. **Behavioural Competencies** ---------------------------- Ownership Teamwork \& Leadership Cultural Fit Motivation to Learn and Grow**Technical Competencies** -------------------------- AIML Databricks**Skills** ----------