Lead full-stack development of a quantitative trading-analytics SaaS platform, managing its AWS infrastructure to ensure high availability, security and cost efficiency.
Act as the primary technical partner to the CEO and quant research team, translating trading strategies and custom indicators into interactive chart components.
Drive early architecture decisions—e.g. selecting TimescaleDB for time-series data—refactoring and streamlining legacy code for maximum efficiency, and leveraging AWS services (Lambda, ECS, RDS, CloudFront, etc.) to deliver bespoke solutions that boost performance and minimize costs.
Architect and maintain CI/CD pipelines, and build out the SaaS feature set—including user management, payment integration and AI-driven capabilities—to satisfy custom requirements.
Tech Stacks:
JavaScript, TradingView Advanced Chart Library, Python, FastAPI, TimescaleDB, AWS (EC2, CloudFront, CodePipeline, CloudWatch), Docker, Git
Led the design of end-to-end cloud-native architectures, collaborating with global teams to deliver cutting-edge cloud and AI solutions. Specialized in cloud-native application development, Generative AI solutions, and cloud migration projects on AWS platforms.
Tech Stacks:
Java, Python, FastAPI, LangChain, LangGraph, LangSmith, Pinecone, Quarkus, GraalVM, AWS, Azure, Docker, Kubernetes, Hibernate, Querydsl, MySQL, Oracle, PostgreSQL, Redis, Flyway, Maven, Groovy Scripts, Spock, Git, OpenAPI.
Developed medical data systems using Java and Spring Boot, ensuring stability and high performance across hospital networks.
Java, Spring Boot, Spring MVC, Maven, MyBatis, MySQL, JUnit, Git, Linux, Tomcat, Nginx.
Computing and Software Systems