Rahul Gurnani is a software engineer with 11 years of experience building scalable infrastructure for modern AI, currently contributing to Google from Seattle. He specializes in backend and distributed systems, with hands-on expertise in Go and database internals gained through contributions to the high-performance Dgraph graph database—fixing edge-case panics, improving upserts, and hardening restore/versioning logic. Rahul’s career spans startups and large engineering teams, including roles at Dgraph Labs, Indihood, and a machine learning internship at Cure.Fit, giving him a strong blend of production systems and ML exposure. An IIT Kharagpur computer science graduate, he combines deep technical problem-solving with practical tooling work (e.g., test-aggregation scripts and index cleanup) that keeps large systems reliable at scale.
11 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Indian Institute of Technology, Kharagpur
high-performance graph database for real-time use cases
Role in this project:
Back-end Developer & Database Engineer
Contributions:3 releases, 45 reviews, 19 commits in 5 months
Contributions summary:Rahul primarily contributed to bug fixes and feature enhancements within the Dgraph database project. They addressed issues related to nil map panics in the worker/groups.go file, demonstrating proficiency in Go and understanding of data structures. Furthermore, the user implemented a script to fetch aggregate test stats from TeamCity and contributed to the ludicrous mode upserts on the list type and index cleanup, showcasing experience with the database's internal operations and testing. This included fixing the restore function to correctly set the version after marshalling.
Contributions:36 commits, 2 PRs, 28 pushes in 3 years 3 months
python
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