Roles

• Develop and optimize AI-powered applications using Large Language Models (LLMs).
• Build prompts and prompt engineering workflows for different business use cases.
• Integrate LLM APIs and AI services into web applications and internal tools.
• Assist in developing Retrieval-Augmented Generation (RAG) pipelines.
• Work with vector databases, embeddings, and semantic search techniques.
• Fine-tune and evaluate AI models where required.
• Collaborate with product, engineering, and business teams to identify automation opportunities.
• Conduct testing, debugging, and performance optimization of AI applications.
• Stay updated with emerging trends in Generative AI, LLMs, and AI frameworks.
• Document solutions, experiments, and technical implementations.

Requirements

• Strong knowledge of Python programming.
• Understanding of Machine Learning and Deep Learning fundamentals.
• Basic knowledge of Large Language Models (GPT, Llama, Gemini, Claude, etc.).
• Familiarity with Prompt Engineering concepts.
• Exposure to frameworks such as LangChain, LlamaIndex, Hugging Face, or similar.
• Understanding of REST APIs and API integration.
• Basic knowledge of vector databases and embeddings.
• Knowledge of SQL and Git.
• Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.