Python AI Backend Developer

Python AI Backend Developer

• 5+ years of experience in backend development, with strong hands-on expertise in Python .
• Strong experience developing RESTful APIs and scalable backend services using Python frameworks such as FastAPI, Flask, or Django .
• Hands-on experience with Azure Functions and building serverless, event-driven applications on Microsoft Azure.
• Strong experience with Azure OpenAI and integrating LLMs into production-grade applications.
• Good understanding of NLP, embeddings, semantic search, vector databases, and Retrieval-Augmented Generation (RAG) .
• Hands-on experience with LangGraph for building stateful, multi-step AI workflows and agentic applications.
• Experience designing and implementing AI Agents , including tool calling, agent orchestration, workflow management, memory, and multi-agent patterns.
• Strong experience with document processing , including document ingestion, parsing, chunking, metadata extraction, classification, and information retrieval.
• Experience working with PDFs, Word documents, OCR, structured/unstructured data , and document-based AI solutions.
• Strong understanding of prompt engineering, LLM evaluation, context management, and hallucination mitigation .
• Experience integrating AI/LLM capabilities with backend services, databases, APIs, and external systems.
• Good understanding of Azure cloud services and designing secure, scalable cloud-native solutions.
• Experience with Git, CI/CD, automated testing, logging, monitoring, and production troubleshooting .
• Strong understanding of software engineering principles, clean code, design patterns, error handling, and API security .
• Ability to translate business requirements into scalable AI/agent-based technical solutions .
• Good communication skills and ability to collaborate with frontend, data, cloud, and product teams.

Must-Have Skills

Python | Azure Functions | Azure OpenAI | NLP | Embeddings | LangGraph | AI Agents | Document Processing | REST APIs | RAG

Good-to-Have

• Vector databases such as Azure AI Search, Pinecone, Weaviate, or pgvector
• LangChain
• Azure AI Document Intelligence
• OCR and document extraction pipelines
• Event-driven architecture / Azure Service Bus
• Docker and Kubernetes
• PostgreSQL / NoSQL databases
• LLM evaluation and observability
• Experience with multi-agent architectures and agent orchestration