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 qualified 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.
Solid backend/API experience with FastAPI or Flask and REST API development.
Experience with vector databases such as FAISS, Pinecone, Qdrant, Chroma, or Weaviate.
Valuable understa

📌 Artificial Intelligence Developer Bengaluru
🏢 Allegis Group
📍 Bengaluru