Naveen Vignesh

Architecting and evaluating large language models with focus on prompt design, rubric creation, and model response validation to improve generative AI accuracy and relevance. Built React/Next.js evaluation platforms to enable scalable, user‑centric model assessment workflows.

Technical lead delivering micro‑frontend architectures for ANZ using React, TypeScript and Spring Boot; modernized Financial Management Suite, reducing technical debt by 40%. Championed testing and CI/CD practices to achieve 95%+ test coverage and improve release reliability.

Executed comparative benchmarks of AI models assessing code correctness, executability, and business adherence, and reviewed trainer submissions, increasing evaluation accuracy by 30%. Developed structured evaluation frameworks to raise overall model integrity for engineering and research teams.

Spearheaded delivery of a scalable mobile trading platform for ADSS using React Native, TypeScript, RxJS and Tailwind, impacting 10k+ end users and shipping robust test suites and automated E2E tests.

Consulted for ANZ Bank (via PwC) modernizing financial applications with React, TypeScript, Java Spring Boot and Node.js, boosting application performance and scalability. Designed reusable component libraries that accelerated multi‑team UI development by 25%.

Developed core React Native modules for HODLMedia's crypto tracking app, integrating native Android/iOS code and Node.js/Express APIs to enable real-time asset tracking and seamless user interactions.

Founding engineering team member who built high‑performance video streaming solutions using React, WebRTC, and Node.js to enable real‑time communications. Implemented scalable RESTful APIs and automated outreach pipelines, improving marketing and user engagement workflows.

Designed and developed React and React Native modules for GraphQL‑based SaaS student testing platforms and real‑time audio/video streaming features; integrated native bridges and AWS S3 for secure media storage. Contributed to front‑end documentation and component implementations supporting product growth.

Grade: First Class, CGPA 8.14

Activities and societies: Organized Android workshop (JEC, 2016); team leader/mentor in Smart India Hackathon events (2017–2019) and participant in college hackathons.

Completed Bachelor of Engineering in Computer Science and Engineering at Anna University (Aug 2014–May 2018), graduating First Class with a CGPA of 8.14.