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EduReel.ai is an AI-native learning platform that generates highly personalized micro-learning content using LLMs, RAG, and agent-based workflows. I built the backend pipelines end-to-end, including content ingestion, retrieval, generation, and evaluation, with a strong focus on reliability and iteration. The system emphasizes real-world production concerns such as structured data models, feedback loops, and scalable APIs rather than prototypes or demos.…EduReel.ai is an AI-native learning platform that generates highly personalized micro-learning content using LLMs, RAG, and agent-based workflows. I built the backend pipelines end-to-end, including content ingestion, retrieval, generation, and evaluation, with a strong focus on reliability and iteration. The system emphasizes real-world production concerns such as structured data models, feedback loops, and scalable APIs rather than prototypes or demos.

Yash Pokharna

Web Developer, Full Stack Developer, Programmer, +4

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EduReel.ai is an AI-native learning platform that generates highly personalized micro-learning content using LLMs, RAG, and agent-based workflows. I built the backend pipelines end-to-end, including content ingestion, retrieval, generation, and evaluation, with a strong focus on reliability and iteration. The system emphasizes real-world production concerns such as structured data models, feedback loops, and scalable APIs rather than prototypes or demos.…EduReel.ai is an AI-native learning platform that generates highly personalized micro-learning content using LLMs, RAG, and agent-based workflows. I built the backend pipelines end-to-end, including content ingestion, retrieval, generation, and evaluation, with a strong focus on reliability and iteration. The system emphasizes real-world production concerns such as structured data models, feedback loops, and scalable APIs rather than prototypes or demos.

Available to hire

EduReel.ai is an AI-native learning platform that generates highly personalized micro-learning content using LLMs, RAG, and agent-based workflows. I built the backend pipelines end-to-end, including content ingestion, retrieval, generation, and evaluation, with a strong focus on reliability and iteration. The system emphasizes real-world production concerns such as structured data models, feedback loops, and scalable APIs rather than prototypes or demos.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Software Development Intern at Miller Center for Global Impact

July 1, 2025 - September 1, 2025

Built and optimized real-time logistics APIs with Redis caching, ensuring low-latency delivery tracking for 5,000+ daily shipments. Eliminated redundant status calls and improved data consistency across microservices, reducing API response time by 30%. Developed a full-featured Careers module— designed database schema, backend logic, REST APIs, and HR dashboard for job postings and applications. Containerized backend services with Docker and deployed to AWS ECS, enhancing scalability and uptime.

Software Engineer Intern at Career Launch

May 1, 2025 - July 1, 2025

Developed modular backend services to manage large question banks and handle 5,000+ content requests efficiently. Implemented caching and optimized SQL queries for serving 10,000+ MCQs, improving content load time by 40%.

Software Engineer at Indexnine Technologies

January 1, 2024 - August 1, 2024

Designed scalable backend pipelines using ZUS APIs to automate data synchronization and reporting across enterprise systems. Developed a headless automation engine with Puppeteer, reducing manual data processing by 50%. Created a Node.js browser extension for high-volume data extraction across dynamic e-commerce sources. Contributed to API performance optimization and implemented error-handling middleware to improve system reliability.