With over 12 years of overall software development experience and over 5 years as a cloud software engineer and technical lead, Yuriy specializes in designing and developing scalable, secure, and efficient back-end solutions using AWS serverless technologies and Python/TypeScript. He has a strong background in cloud native architectures, event-driven systems, and data engineering.
Working as a Blockchain infrastructure engineer focused on high-SLA gateway services with millisecond-level performance optimization across DB, network, and runtime components.
Implementing Datadog monitoring for critical metrics visibility.
Working on back-end development with Python and TypeScript, RDBMS optimization, and AWS/EKS deployment for scalable Blockchain infrastructure.
Refactoring legacy code and participating in 24/7 on-call rounds once in a few months.
Built an E2E security SaaS product for software supply chain protection.
Contributed to the design and development of internal products with a strong focus on scalability, speed of delivery, and adaptability in a dynamic startup environment.
Spearheaded the transition from a Kubernetes-based setup to a serverless architecture, optimizing for rapid prototyping, MVP validation, and faster time-to-market.
Integrated AWS serverless technologies (Lambda, API Gateway, DynamoDB, S3) to enhance scalability, fault tolerance, and operational efficiency.
Used Python as the primary back-end language and TypeScript for the web application layer, ensuring consistency across the stack.
Introduced pragmatic, out-of-the-box solutions tailored for a resource-constrained startup environment, enabling high agility and minimizing overhead.
Accelerated iteration and product feedback loops, allowing quick experimentation and alignment with evolving business goals.
Constructed serverless data pipelines that were fully hosted using AWS.
Built a batch processing system for ML processes.
Defined all company procedures (CI/CD, documentation flow, and more).
Integrated GCP Composer as the main orchestration system.
Constructed a serverless data processing pipeline that was also integrated with CI/CD.
Developed internal services for text analysis based on Elasticsearch and the NLTK Python library.
Consolidated and standardized back-end infrastructure across multiple Gartner-acquired platforms, including GetApp, enabling centralized ingestion, storage, and indexing of all software product reviews.
Designed and implemented a leads funnel using LinkedIn-crawled professional profiles to match software products with relevant business prospects.
Created technical tools based on an internally developed Linux network driver for the network adapters in order to serve the silicon validation teams.
Supported the LAN simulation environment written in C++.
Constructed a testing framework for the L2 network protocols, NCSI and MCTP.
Super Signal is an AI-based investment management company.
It utilizes latest technologies and alternative data sources to predict stock behaviors.
The project focuses on an Engineering Platform.
