Senior Python Developer (AI/LLM)
8.0/10
Bell Integrator
Not specified
Office / on-site
senior
3 days ago
aidevPythonAIMLFastAPIDjangoPostgreSQLRedisMongoDBDockerKubernetes
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Description
What you'll do
You will be the sole Python developer in the team responsible for implementing AI agents from scratch to production.
- •Design and develop production systems using Python 3.12+ for AI agents and LLM models
- •Implement multi-agent architecture: integrate components, implement pipelines and custom orchestrators (LangChain, LangGraph, RAG)
- •Develop and maintain APIs (FastAPI, Django): create microservices, REST, asynchronous services
- •Integrate with relational, NoSQL, and vector databases (PostgreSQL, Redis, MongoDB, VectorDB: ChromaDB, QDrant)
- •Create, train, and deploy ML models (ML pipeline, Prompt Engineering, RAG, quality assessment, A/B testing)
- •Containerization (Docker, Docker Compose) and deployment in Kubernetes, partial setup of DevOps processes (CI/CD: Jenkins, ArgoCD)
- •Develop unit tests, code review, performance optimization, ensure security
- •Collaborate in Agile teams, participate in planning, mentoring
Conditions
- •Opportunity to participate in an interesting project
- •Opportunity for professional and career growth in the company
- •Experience working in a team of professionals
- •Salary level is discussed individually
- •Work in the office in Moscow or St. Petersburg
Requirements
- •Proficiency in Python 3.12+: deep knowledge of standard and modern features of the language (asyncio, typing, dataclasses, pydantic, pytest)
- •Practical experience in developing AI/ML solutions using LangChain, LlamaIndex, RAG, integration with LLM API
- •Experience in designing and maintaining high-load REST APIs on FastAPI/Django (architecture, DI, serialization, OpenAPI)
- •Advanced work with PostgreSQL/Redis, designing complex schemas, indexing, optimization, vector databases
- •Skills in containerization, deployment in Kubernetes
- •Experience in implementing CI/CD pipelines, monitoring, alerting, organizing logging
- •Confident knowledge of Git, experience in team work (Agile, Scrum)
- •English B2+ for reading documentation and communications
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