Valery Zimichev

Designed and maintained Python microservices and REST APIs (FastAPI) powering AI and NLP workflows. Built MCP services integrating LLMs, vector stores, and processing pipelines. Implemented CI/CD and cloud deployments using GitHub, Docker, Cloud Run, and Terraform. Improved observability, performance, and reliability through monitoring, logging, and incident response.

Responsibilities: - Integration of AI services for generating content (text, images, videos) and building intelligent chatbots. - Developed and maintained backend services, including new feature implementation, system improvements, and performance optimization. - Designed and delivered scalable features based on product requirements and architectural guidelines. - Refactored existing systems to improve performance, reliability, and code clarity. - Provided technical support, investigated issues, and resolved bugs in production environments. - Collaborated with frontend, DevOps, and product teams to deliver end-to-end solutions. Technologies: Python (FastAPI/Flask), PostgreSQL Achievements: - Contributed to several key product features, improving user experience and system reliability. - Optimized API response times and background task performance. - Strengthened monitoring, logging, and error handling across backend services. - Implemented integrations with AI services (OpenAI, Mistral, and internal generators) to automate and expand the product's capabilities. - He developed the architecture and API for a chatbot assistant that connects internal ML models with external AI providers.

Responsibilities: - Designed and developed backend microservices supporting complex clinical and research workflows. - Implemented layered architecture (domain-driven structure) to improve modularity, testability, and long-term maintainability of backend systems. - Refactored legacy services, reduced technical debt, and adopted modern architectural patterns. - Collaborated on API design and service-to-service contracts with frontend, DevOps, and analytics teams. - Provided production support, handled incident investigations, and contributed to monitoring and alerting via Prometheus/Grafana. - Participated in code reviews, architectural discussions, and RFC reviews for system-wide changes. Technologies: Python (FastAPI, Flask), PostgreSQL, Redis, Celery, Docker, Kubernetes Prometheus/Grafana, Elasticsearch, OpenAPI Achievements: - Successfully introduced layered (hexagonal/clean) architecture to several core services, improving scalability and maintainability. - Developed new backend systems to support bioinformatics pipelines, reporting engines, and clinical workflows. - Refactored and optimized legacy services, improving performance and simplifying business logic. - Actively maintained and supported production systems, contributing to system reliability and stability.

Responsibilities: - Led a cross-functional team of 5 engineers (backend, DevOps, frontend). - Designed the architecture of a scalable backend service. - Set up development processes and team collaboration workflows. - Conducted code reviews, mentored engineers, and supported team growth. - Managed cloud infrastructure using GCP (GCE, GKE). - Decomposed business goals into clear engineering tasks and distributed work across the team. Technologies: Python, Google Cloud Platform (GCE, GKE), GitLab, Docker, Flask, FastAPI, MongoDB Achievements: - Delivered and publicly launched the MVP of CodecWar — a web platform for automated evaluation and comparison of video codecs. - The platform tests encoding quality using objective metrics (e.g., PSNR, SSIM), visualizes artifacts, and assists engineers and researchers in making informed decisions on codec performance and optimization. - Built a scalable and automated testing infrastructure using CI/CD pipelines and Kubernetes orchestration.

Responsibilities: - Automated testing for video codecs, including quality, performance, and stability checks. - Set up and streamlined CI/CD processes across internal projects. - Full-stack web development of internal corporate tools. Technologies: Python, Docker, GitLab CI/CD Key Achievements: - Containerized and implemented CI/CD pipelines for 10+ company projects, successfully migrating from virtual machines to Docker. - Built a custom test automation framework for video codec validation. - Developed a web application for viewing and analyzing test results, improving debugging speed and team collaboration.