AI ML Python Developer
This role focuses on building scalable backend services and REST APIs in Python, leveraging FastAPI/Flask/Django to support generative AI and LLM-based applications. The developer will integrate Azure OpenAI, LangChain, LiteLLM, and Langfuse to manage LLM workflows, observability, and cost, while ensuring robust rate limiting, caching, and database support with PostgreSQL, MongoDB, and Redis.
Skills required
About this role
Design and develop scalable backend services and REST APIs using Python, FastAPI/Flask/Django.
Build and integrate Generative AI/LLM-based applications, including RAG, AI agents, embeddings, and tool/function calling.
Work with Azure OpenAI and other LLM providers.
Use AI frameworks such as LangChain, LlamaIndex, LangGraph, or similar.
Implement LiteLLM for LLM gateway, routing, fallback, and usage/cost management.
Implement rate limiting, throttling, caching, retries, and API quotas for scalable services.
Use Langfuse for LLM observability, tracing, prompt management, token/cost tracking, and evaluation.
Design and work with PostgreSQL/MySQL, MongoDB, and Redis.
Deploy and manage applications using Microsoft Azure, Docker, and CI/CD.
Develop unit/integration tests, troubleshoot production issues, and optimize performance and cost.
Participate in system design, code reviews, and technical architecture discussions.
Required
5–7 years of software development experience with strong Python and backend development skills and hands-on experience in Generative AI/LLM applications.
Strong understanding of REST APIs, microservices, RAG, embeddings, vector databases, prompt engineering, AI agents, rate limiting, and distributed systems.
Hands-on experience with Azure OpenAI, LiteLLM, and Langfuse is preferred, along with exposure to LangChain/LlamaIndex/LangGraph or similar AI frameworks.
Experience with Microsoft Azure, Docker, CI/CD, databases, Redis, API security, and cloud-native application development is required.
Strong problem-solving, communication, ownership, and ability to build production-grade AI solutions are essential.
