Priya Bharathi Arul
I’m Priya Bharathi Arul, an M.S. ECE student at the University of Washington focused on building AI-powered software and data systems.
About
I’m Priya Bharathi Arul, an M.S. ECE student at the University of Washington focused on building AI-powered software and data systems. I bring 5+ years of professional experience across Python, C++, and SQL, with a strong background in automation, scalable backend development, and delivering reliable pipelines. I’m especially passionate about using LLMs for practical applications—such as RAG and agentic workflows—paired with careful evaluation and safety considerations.
Beyond my coursework and internships, I’ve supported large student cohorts as a Graduate Teaching Assistant by building automated workflows and running advanced AWS-based data validation and processing. I also enjoy leadership and community work, serving as an IEEE WIE Board Administrator Coordinator and completing WE Rise Leadership Academy training in 2025. When I work on problems, I combine structured engineering practices with a growth mindset and cross-functional communication to ship solutions that scale.
- 8 years' experience
- Joined September 2026
Skills· 10
Languages
- EnglishAdvanced
Industry experience
- Computers & Electronics
- Software & Internet
- Professional Services
- Education
- Financial Services
Work experience· 6 roles
Designed scalable full-stack applications by translating system architecture and APIs into product requirements. Built NestJS microservices integrating Supabase, RabbitMQ, Cloudflare R2, and JWT-based authentication. Focused on robust backend integration patterns and deployment-ready service design.
Supported 60+ students through labs, office hours, and automated workflows, improving grading efficiency by 40%. Performed advanced AWS-based data validation and pipeline processing using Polars, Spark, Athena, and Redshift to strengthen scalable data systems learning outcomes.
Built TextWrapper, an LLM-based extraction tool that maps source text into a target document structure using prompt-guided retrieval. Validated performance with an automated evaluation pipeline using BLEURT and BERTScore to score extraction quality.
Education
Certifications and awards
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