Pavel Shibanov

• Built and refactored connectors to real-time telematics APIs (GPS vehicle tracking) following best practices, improving reliability and maintainability. • Developed 10+ features in private APIs, including geocoding and emissions calculation, enhancing core system functionality. Tech stack: Python, FastAPI, Pandas, Polars, MS SQL, SqlAlchemy, PostgreSQL Infrastructure: Azure, Docker, Datadog AI: Claude Code, GitHub Copilot, CodeRabbit

• Led end-to-end projects from requirements and design to production deployment. • Designed, deployed, and operated large language models (LLMs) on GKE Autopilot and AWS SageMaker, ensuring scalability, and cost efficiency. • Fine-tuned Falcon-40B on financial data for sentiment analysis using LoRA, optimizing training and inference performance. Tech: Python, TensorFlow, PyTorch, Vertex AI, Typescript, React, SQL, NoSQL, Kubernetes, helm, terraform. Infra: AWS, GCP, CloudFlare, on-prem.

• Implemented backend services using Node.js, Express.js, and Sequelize ORM, supporting core business workflows for a global fashion trading platform. • Designed and implemented an ETL pipeline using ExcelJS, AWS Lambda, and Amazon S3, improving data ingestion reliability and automation. • Built CI pipelines with GitHub Actions, enabling automated testing and deployment. Tech stack: Node.js · Express.js · PostgreSQL · Sequelize · React · ExcelJS Infrastructure: AWS Lambda · Amazon S3 · ECS · GitHub Actions

• Reduced software and infrastructure complexity by introducing containerization and Kubernetes-based orchestration for a high-load, multi-region production system. • Designed and implemented a Continuous Deployment (CD) pipeline using Jenkins, improving deployment reliability and release frequency. Tech stack: Python, JavaScript, TypeScript, Node.js Infrastructure & Technologies: AWS, Amazon EKS, Kubernetes, Helm, Docker, Jenkins

• Led the migration of a high-load monolithic application from bare-metal servers to Docker and on-premises Kubernetes, improving reliability and operational consistency. • Designed and implemented multi-stage CI/CD pipelines using GitLab CI/CD, enabling automated builds, testing, and deployments. Tech stack: Python · JavaScript · TypeScript · Node.js · Go Infrastructure: Kubernetes · Helm · Docker · GitLab CI/CD · AWS · Linkerd2 · Puppeteer

Implementing new features, refactoring, reviews, lib updates. Tracking user interaction become my obsession. I always think how to measure something useful, how to analyze something new. Trying to write effective and compact code, that anyone can understand and maintain.

I was learning enterprise tooling and scientific approach to software development. My day-to-day job was implementing new functionality using AngularJS, AngularUI Bootstrap, Angular UI Router Leaflet.js, D3.js and a lot of other libraries. My code was reviewed by professionals with awesome level of expertise in front-end and back-end. I learned how important to write tests, how advanced tooling and unique developer environment saves great amount of time.

Web-development