I’m a Backend Engineer with 2+ years of experience building high-scale systems across search, discovery, and monetization at magicpin. My work focuses on designing low-latency, reliable systems that directly impact user experience and business outcomes. I’ve contributed to and owned parts of platforms powering AI-driven search, ads automation, and merchant engagement, where improvements translate into measurable gains in CTR, conversion, and revenue. I enjoy working at the intersection of backend engineering, data systems, and applied AI. From building distributed data pipelines and scalable APIs to designing hybrid search systems that combine lexical and vector ranking, I aim to make systems faster, smarter, and production-ready. Some highlights: • Improved search and discovery systems with significant gains in engagement and conversion • Built internal automation tools reducing debugging and resolution time from days to minutes • Worked on revenue-critical systems contributing to a large share of business impact • Developed LLM-driven workflows and agentic systems for real-world use cases Currently, I’m exploring LLM-powered systems, agentic workflows, and production-grade AI, with a focus on solving practical problems at scale. I value clean system design, scalability, and reliability as much as speed of execution. Always open to conversations around backend engineering, system design, and ML in production.