Python developer for AI agents

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• Design, develop, and maintain AI agents using Python.
• Integrate LLM providers and third-party AI services.
• Develop AI agent workflows, tool calling, and orchestration logic.
• Implement RAG pipelines for searching and retrieving information from documents and databases.
• Develop and maintain backend APIs for AI-powered applications.
• Integrate AI agents with internal systems, databases, and external services.
• Optimize AI agent performance, response quality, and processing time.
• Implement error handling, logging, testing, and monitoring.
• Work with the development team to deliver reliable and scalable AI solutions.
• Participate in code reviews and technical discussions.

• 3–4 years of commercial experience in Python development.
• Strong knowledge of Python Core, OOP, and asynchronous programming (Asyncio, async/await).
• Hands-on experience with Django.
• Experience developing and integrating AI-powered applications and AI agents.
• Practical experience working with LLM APIs (OpenAI, Anthropic Claude, or similar).
• Understanding of prompt engineering and structured outputs.
• Experience with AI agent frameworks such as LangChain and LangGraph.
• Understanding of RAG (Retrieval-Augmented Generation) architecture and practical experience implementing it.
• Experience with vector databases.
• Knowledge of embeddings, semantic search, and document processing.
• Experience with function calling, tool calling, and integrating external APIs into AI agents.
• Strong knowledge of REST API development and third-party integrations.
• Experience with PostgreSQL, SQL, and ORM technologies.
• Experience with Redis and background task processing (Celery or similar).
• Knowledge of Git, Docker, and Linux environments.
• Experience writing unit and integration tests.
• Understanding of application security, error handling, logging, and performance optimization.
• Ability to independently develop, debug, and maintain backend and AI-powered solutions.
• Будет плюсом: Experience developing AI agents for Finance, FinTech, or enterprise applications; Experience with multi-agent systems and agent orchestration; Knowledge of MCP (Model Context Protocol); Experience with LangSmith or similar LLM observability and evaluation tools; Experience with AI agent memory management and context handling; Knowledge of document parsing, OCR, and information extraction; Experience with microservices architecture; Familiarity with Kafka or RabbitMQ; Experience with cloud platforms and CI/CD pipelines

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