Dmytro

Led a small team of Python backend developers in the rapid development and scaling of a charitable social networking platform. This project combines a Django backend with a React frontend with a demand to support continuous feature expansions and marketing initiatives. - Worked in tandem with management and the frontend team lead to develop and refine the system's architecture, ensuring it supported a stream of new features and met marketing requirements. - Participated in design and refactoring of the system and its classes, focusing on scalability and coherent structure to accommodate the platform's rapid expansion. - Orchestrated the development of a comprehensive Django application, utilizing a stack comprised of Python, Django, PostgreSQL, Celery, Pytest, Docker and Redis. - Mentored junior developers, overseeing task assignments and conducting code reviews...

Working as one of the core developers to build a product to simplify and enhance the work for developers and managers by providing transparency in third-party API usage and offering a variety of monitoring and analysis tools. Project utilizes microservices architecture and Kafka as a message broker. - Collaborated in system design and architecture decisions, contributing to discussions on product development. - Migrated data from MongoDB to PostgreSQL and AWS. - Designed and implemented a complex error monitoring and collection system from scratch using Kafka and microservices architecture. Developed a simple and useful API for microservices to invoke and process exceptions on both user and service sides. - Employed technologies such as Django, DRF, Celery, Kubernetes, Kafka, FastAPI, MongoDB, and PostgreSQL to design and implement microservices and their APIs. - Developed and maintained tests for services using pytest...

Our team collaborated closely with customers to roll out new features and create AI-powered products that help manage and troubleshoot infrastructure at scale. - Built aggregation queries, SQL functions, and database indexes on massive tables, ensuring performance at production scale. - Contributed to HolmesGPT AI agent development by building integration toolsets and utilities to connect client-specific observability and data-collection systems, architecting backend components and feature logic for AI-driven capabilities. - Designed and implemented the backend for an interactive, chat-based AI interface, enabling users to ask follow-up questions about their Kubernetes clusters’ status and AI-generated analysis—supported by an evaluation framework to ensure consistent, accurate responses. -​ Participated in development of an LLM-powered Slack chatbot that integrates with Robusta’s AI and observability tools to trigger on-demand cluster investigations directly from Slack.