Summary:
We are seeking an experienced Python Backend Developer to design, build, and deploy scalable AI-powered applications using Retrieval-Augmented Generation, large language models, and agentic AI frameworks. The role will focus on delivering a production-grade RAG system and AI chatbot that can securely integrate with enterprise data, APIs, databases, and cloud services.
General information:
The organization is developing an AI-powered platform and requires an experienced individual contributor to build its RAG architecture and conversational AI capabilities. The developer will work closely with a distributed team and should be available for several hours of overlap with US working hours.
The project involves designing AI systems that go beyond basic prompt engineering, including multi-step workflows, autonomous agents, vector search, knowledge retrieval, memory management, and tool integration. The solution must be scalable, secure, observable, and suitable for production use.
The technology environment includes Python, FastAPI, large language models, LangGraph, LangChain, vector databases, Azure AI services, AWS, Docker, Kubernetes, and microservice-based architectures.
Task and deliverables:
- Design the end-to-end architecture for a scalable RAG system and AI chatbot.
- Develop Python backend services, REST APIs, and microservices using FastAPI or similar frameworks.
- Build document ingestion, chunking, embedding, indexing, retrieval, and reranking pipelines.
- Implement vector search solutions using Azure AI Search or comparable vector databases.
- Design autonomous AI agents capable of planning, reasoning, tool usage, and decision-making.
- Develop multi-step AI workflows using LangGraph, LangChain, CrewAI, AutoGen, or similar orchestration frameworks.
- Integrate commercial and open-source LLMs, including Azure OpenAI, OpenAI, Anthropic Claude, Gemini, and comparable models.
- Implement conversation memory, session management, context management, and agent collaboration patterns.
- Connect AI workflows with APIs, databases, enterprise systems, and external tools.
- Develop asynchronous, high-performance services capable of handling concurrent AI workloads.
- Implement prompt management, structured outputs, guardrails, fallback logic, and model evaluation processes.
- Establish logging, monitoring, tracing, observability, security, and error-handling standards.
- Containerize and deploy AI services using Docker, Kubernetes, Azure, or AWS.
- Translate business requirements into technical designs, delivery milestones, and production-ready AI solutions.
- Collaborate with the wider team while independently owning architecture and implementation decisions.
Required experience:
- Required: 8 or more years of professional Python backend development experience.
- Required: Strong experience designing REST APIs, microservices, asynchronous services, and distributed backend systems.
- Required: Hands-on experience building production-grade RAG applications.
- Required: Strong understanding of embeddings, document chunking, semantic search, vector indexing, retrieval strategies, and reranking.
- Required: Hands-on experience developing AI agents and multi-step LLM workflows.
- Required: Experience with agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or comparable platforms.
- Required: Experience integrating LLMs through OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or open-source model APIs.
- Required: Ability to design AI architecture beyond basic prompt engineering.
- Required: Experience integrating AI applications with APIs, databases, data pipelines, and enterprise systems.
- Required: Experience implementing security, monitoring, logging, tracing, and observability for production services.
- Required: Experience deploying containerized applications using Docker and cloud platforms such as Azure or AWS.
- Required: Ability to independently translate business requirements into scalable technical solutions.
- Required: Strong communication and collaboration skills in a distributed working environment.
- Required: Availability for several hours of overlap with US working hours.