Job Designation: Intermediate Python Developer (LLMs & GenAI)

Job Overview:
We are looking for an experienced Python developer with a strong background in Large Language
Models (LLMs), Generative AI (GenAI), excellent knowledge prompt engineering, tools for RAG
development. The ideal candidate will have hands-on experience in prompt engineering, working with
advanced AI frameworks such as LlamaIndex, LangChain, LangGraph, and AutoGen.

Key Responsibilities:
• Develop and implement AI-driven solutions using Python and state-of-the-art LLMs like Azure
OpenAI, Lama, Gemini.
• Design and optimize prompt engineering strategies to improve model responses and
performance.
• Work with tools like LlamaIndex, LangChain, and LangGraph to integrate AI into business
workflows.
• Use LangGraph and AutoGen to design and manage multi-step reasoning workflows for complex
applications by using poly LLMs.
• Develop APIs and interfaces for integrating LLM-based models into existing systems on Flask.
• Perform performance testing, debugging, and continuous improvement of APIs.
• Research on developing conversational agents, personalized recommendations, and other
GenAI-powered products like intelligent chatbots, assistants and digital twins.
• Keep up with the latest developments in AI/ML and apply new techniques to improve our models
and tools.

Required Skills & Qualifications:
• Experience: 2-4 years of Python development experience with a focus on AI/ML.
• Knowledge: In-depth understanding of LLMs, GenAI, and prompt engineering.
• Frameworks: Proficiency in LlamaIndex, LangChain, LangGraph, and AutoGen.
• Machine Learning , Speech processing , NLP , APIs , Problem Solving 

Preferred Qualifications:
• Knowledge on Speech synthesis and Sentience simulation
• Experience with cloud platforms (Azure and GCP) for deploying and scaling AI/ML models.
• Familiarity with containerization (Docker) and orchestration tools (Kubernetes) for deploying
microservices.
• Experience with reinforcement learning, transformers, or other cutting-edge techniques.
• Understanding of ethical AI, data privacy, and responsible AI practices.