Python Backend Developer (MLOps/LLMOps Platform)

Vacancy: Python Backend Developer (MLOps/LLMOps Platform) Grade: Senior Company: JETLY Format: remote Location: Russia Citizenship: RU Salary Range: from 260,000 to 370,000 rubles net per month Employment Terms, Format: Labor Code/Sole Proprietor

🟡Project Description: Development of the Analytical Platform — a unified MLOps ecosystem for the bank.

We are looking for a Python developer with over 5 years of experience who wants to work at the intersection of data engineering, microservice architecture, and AI infrastructure. You will design and implement services that ensure the complete lifecycle of ML models and LLM applications.

🟡Requirements:

• Python experience from 5 years
• Confident command of frameworks and libraries: FastAPI, aiohttp, SQLAlchemy, AsyncIO
• Practical experience with Docker and Kubernetes (building images, deployment, configuration management)
• Understanding of principles and design patterns for distributed systems and microservice architectures
• Experience working with LLMs, RAG architectures
• Independence in bringing tasks to completion
• Proactiveness and initiative in proposing technical solutions
• Full immersion in the project code and team
• Teamwork, willingness to help colleagues and users
• Ability to grasp the overall picture of the expected result, rather than solving a specifically assigned task

✅Will be an advantage: Familiarity with MLOps practices: model versioning, drift monitoring, CI/CD for ML Experience with message queues (Kafka, RabbitMQ) and event-driven architectures Knowledge of monitoring tools: Prometheus, Grafana, Loki, OpenTelemetry Understanding of principles for working with big data (Spark, ClickHouse, Hadoop) Experience in the banking or fintech domain

📝Tasks:

• Break down and estimate tasks (together with the team), be responsible for deadlines and quality of solutions
• Communicate with clients, clarify needs, adapt solutions to requirements
• Develop and deploy functional services and microservices
• Support and improve existing services and components
• Scale developed systems