Key Responsibilities
Design Development : Lead the design, development, and optimization of LLM-based chatbots and AI agents.
LangChain Implementation : Implement LangChain to build scalable and effective AI-driven applications.
RAG Pipeline Integration : Develop and integrate Retrieval-Augmented Generation (RAG) pipelines to enhance knowledge retrieval for chatbots.
VectorDB Usage : Leverage VectorDB to enable productive similarity search and retrieval of relevant data.
AI Inference with Groq : Utilize Groq for AI inference and acceleration, ensuring optimal performance and scalability.
LLM Fine-Tuning : Fine-tune and optimize large language models (LLMs) like GPT-4 , LLama , Mistral , or Falcon to meet specific business use cases.
Cross-Functional Collaboration : Work closely with product managers, data scientists, and engineers to integrate AI models into applications.
Scalability Performance : Ensure AI solutions are scalable, secure, and performant in real-world environments.
Continuous Learning :



Stay abreast of advancements in AI, NLP, and machine learning to incorporate the latest technologies.

Required Skills Qualifications :
Proven experience in developing LLM-based chatbots and AI agents.
Expertise in LangChain , RAG , and VectorDB technologies.
Hands-on experience with Groq and AI acceleration techniques.
Robust proficiency in Python and Node.js for AI/ML development.
Experience with fine-tuning LLMs like LLama , GPT-4 , Mistral , or Falcon .
Solid understanding of machine learning, deep learning, and Natural Language Processing (NLP) techniques.

Preferred Qualifications :
Experience with OpenAI , Hugging Face , and Anthropic APIs .
Knowledge of prompt engineering and reinforcement learning from human feedback (RLHF) .
Prior experience in developing multimodal AI solutions (e.g., text, image, video, speech models).

📌 Generative Ai Expert Chandigarh (India)
🏢 Cogniter Technologies
📍 India