Saruar Nurlybek

Software Engineer

AI research startup automating financial audit and accounting workflows for Big4.

• Engineered automated Sarbanes-Oxley (SOX) control testing using agentic workflows, increasing the speed of manual control testing by 40% and reducing audit overhead for Big 4 clients.
• Optimized PDF ingestion latency for web scraping workflows by 40% by implementing magic bytes and head validators, preventing unnecessary downloads and streamlining data extraction for financial reports.
• Implemented a distributed caching and storage system for agentic logs using Redis and AWS S3, reducing log retrieval latency by 70% and enabling persistence of execution history.

Full Stack Developer

A fast-growing startup transforming the fashion industry with a scalable multi-tenant e-commerce for European clothing brands.

• Developed a Next.js e-commerce website serving 35,000 monthly active users, implementing core features such as product catalog, shopping cart, and checkout process using JavaScript.
• Improved rendering time by moving from client-side to server-side, reducing page load times by 3 times, while cutting down server overhead by 10% using pre-rendering, dynamic data fetching, and caching.
• Engineered a responsive and intuitive user interface using a React-based UI component library, leading to a 25% increase in user engagement and 60 fewer page bounces per day, resulting in a significant reduction in user drop-off.
• Integrated InPost postal service into the platform’s frontend server using Next.js, reducing shipping time from 4 to 2 days and increasing delivery success rate by 15%.
• Rewrote an existing backend service from Node.js to Golang, leveraging pipeline aggregation to handle 415,000 collections of conversations, reducing response times by up to 50% and improving system performance.

Software Engineer Intern

10-week incubator focused on building AI startups with mentorship in development, design, and strategy.

• Implemented a real-time car search and notification system by parsing data for over 50,000 vehicle listings from an online marketplace, enabling users to receive instant alerts for new listings that matched their criteria.
• Integrated GPT-3.5 with vector databases using Python, enhancing natural language processing capabilities and improving query accuracy by 40%.
• Secured a $1,500 scholarship from Chevron Corporation for the nFactorial Incubator program, ranking in the top 5% of 2000+ applicants.