Headline

Backend Engineer | Python & C++ | AI/ML Integration | Ex-intern @ Genesis

About

Backend + AI/ML engineer focused on building production-ready systems that solve real problems. Currently leading backend development at Genesis, where I design intelligent workflows for an AI-powered product discovery platform using Python and modern API architecture. Previously built CrossBench at Cognifyz — a C++ analytics engine that aggregates live AI model benchmark data into a unified interactive leaderboard using WinHTTP, nlohmann/json, Chart.js, and Tailwind. My core areas: ▸ Backend development & API design (Python, C++, FastAPI) ▸ AI/ML integration and LLM-powered decision workflows ▸ Data aggregation, parsing, and scalable processing systems ▸ Systems thinking — reliability, performance, and production deployment I care about the intersection of engineering and product: building systems that are technically sound, scalable, and genuinely useful for real users. Open to backend, AI/ML engineering, and full-stack opportunities.

Location

Bengaluru

Work experience

Lead Software Engineer Intern at Genesis training, Feb 2026 - May 2026 · 4 mos, Bengaluru, ▸Architected backend systems in Python for an AI-powered product discovery platform, designing REST APIs and scalable data-processing workflows to support intelligent user interactions ▸Integrated LLM capabilities into core application workflows, enabling automated decision-making and content processing pipelines ▸Built data aggregation modules that ingest, parse, and normalize product data from external sources, preparing the system for production-scale deployment ▸Designed system architecture with scalability and maintainability as first-class constraints — documenting API contracts and data flow for team alignment ▸Led a team of 10 engineers, conducting code reviews and establishing backend development standards

Software Developer Intern at Cognifyz Technologies, Nov 2025 - Dec 2025 · 2 mos, Bengaluru, ▸Built CrossBench — a C++ web scraping and analytics engine that aggregates AI model benchmark data from 5+ authoritative sources into a unified, real-time leaderboard [GitHub: link] ▸Engineered HTTP request workflows using WinHTTP and implemented structured JSON parsing via nlohmann/json to fetch, normalize, and version live benchmark results ▸ Designed an interactive performance visualization dashboard using Chart.js and Tailwind CSS, enabling side-by-side model comparisons across accuracy, speed, and cost dimensions ▸Implemented a persistent file I/O system with robust error handling and data serialization, ensuring reliable data storage across sessions without data loss

Education

Bachelor of Engineering - BE, Computer Science, JSS Academy Of Technical Education Karnataka