Senior Python GenAI Engineer (Agents & RAG)

**About The Opportunity** We are looking for an enthusiastic Python Developer with a keen interest in Generative AI (GenAI), Retrieval\-Augmented Generation (RAG), and related AI/ML technologies. This is an exciting opportunity for a passionate developer to work on cutting\-edge AI\-driven applications and contribute to the development of intelligent systems and Agentic workflows. **Responsibilities** * Develop \& Maintain Python\-based applications leveraging GenAI, RAG, Agentic Workflow and LLM (Large Language Models) technologies. * Implement and Optimize retrieval pipelines using vector databases and other indexing techniques. * Integrate APIs \& Models such as OpenAI, LLamaParse, and LangChain into AI\-powered applications. * Enhance AI Workflows by integrating retrieval and knowledge augmentation techniques to improve response accuracy and relevance. * Collaborate with other AI engineers, Product Manager, and software developers to deploy AI\-powered solutions in real\-world applications. * Write efficient, scalable, and maintainable code following best software engineering practices. * Debug and Optimize AI/ML applications to ensure efficiency, accuracy, and robustness. * Stay Updated with the latest advancements in GenAI, NLP, RAG, and Python\-based AI frameworks. **Required Qualifications** * Proficiency in English * Proficiency in Python and experience with frameworks like FastAPI, Flask, or Django. * Knowledge of GenAI models (GPT, LLaMA, etc.) and their applications. * Familiarity with retrieval mechanisms such as FAISS, or dense vector embeddings. * Basic understanding of machine learning and deep learning concepts. * Hands\-on experience with APIs and libraries like OpenAI, LangChain and Hugging Face Transformers. * Experience with SQL databases * Good problem\-solving and debugging skills. * Strong communication and teamwork abilities. * Python, Gen AI, indexing experience, prompt management, Python, and Google ADK. **Nice To Have Skills** * Experience with Docker, Kubernetes, or cloud platforms (AWS, Azure). * Familiarity with prompt engineering.