Artificial Intelligence Developer

Role & Responsibilities

• Develop and maintain Python-based applications integrated with LLMs such as OpenAI, HuggingFace, Anthropic, and Ollama.
• Build end-to-end RAG pipelines, including document ingestion, chunking, embeddings, retrieval, and vector search.
• Develop GenAI application interfaces using React, Streamlit, Gradio, Vue, or similar UI frameworks.
• Build and integrate REST APIs using FastAPI or Flask to connect AI backends with front-end applications.
• Implement prompt engineering, LLM orchestration, and techniques to improve response quality and retrieval accuracy.
• Work with vector databases such as FAISS, Pinecone, Qdrant, Chroma, or Weaviate.
• Integrate AI capabilities into intuitive and responsive user experiences such as chatbots, AI assistants, dashboards, and document-based applications.
• Implement authentication, session management, and application state management for interactive AI solutions.
• Write clean, modular, testable, and well-documented Python code using engineering best practices.
• Use Git, Docker, and CI/CD practices for application development and deployment.
• Debug and optimize both LLM/backend performance and UI responsiveness.
• Collaborate with product and UX teams to convert designs and requirements into functional AI-powered applications.

Preferred candidate profile

• 3+ years of professional Python development experience with strong hands-on application development.
• Practical experience building LLM/GenAI applications, not just theoretical or POC-level exposure.
• Strong hands-on experience with RAG, embeddings, vector search, and LLM integration.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
• Hands-on experience with at least one UI technology such as React, Streamlit, Gradio, Vue, or similar.
• Strong backend/API experience with FastAPI or Flask and REST API development.
• Experience with vector databases such as FAISS, Pinecone, Qdrant, Chroma, or Weaviate.
• Good understanding of prompt engineering and LLM response evaluation/optimization.
• Exposure to Docker, Git, CI/CD, unit testing, and clean/modular architecture.
• Strong debugging, problem-solving, communication, and collaboration skills.
• Preferred candidates will have experience building end-to-end GenAI applications combining Python + LLM/RAG + API + UI