via Career pages·4w ago

Staff Engineer

PhonePe

Full-timeOn-site

Location:BangaloreType:Full-timePosted:4w ago

About PhonePe Limited:

Headquartered in India, its flagship product, the PhonePe digital payments app, was launched in Aug 2016. As of April 2025, PhonePe has over 60 Crore (600 Million) registered users and a digital payments acceptance network spread across over 4 Crore (40+ million) merchants. PhonePe also processes over 33 Crore (330+ Million) transactions daily with an Annualized Total Payment Value (TPV) of over INR 150 lakh crore.

PhonePe’s portfolio of businesses includes the distribution of financial products (Insurance, Lending, and Wealth) as well as new consumer tech businesses (Pincode - hyperlocal e-commerce and Indus AppStore Localized App Store for the Android ecosystem) in India, which are aligned with the company’s vision to offer every Indian an equal opportunity to accelerate their progress by unlocking the flow of money and access to services.

Culture:

At PhonePe, we go the extra mile to make sure you can bring your best self to work, Everyday!. And that starts with creating the right environment for you. We empower people and trust them to do the right thing. Here, you own your work from start to finish, right from day one. PhonePe-rs solve complex problems and execute quickly; often building frameworks from scratch. If you’re excited by the idea of building platforms that touch millions, ideating with some of the best minds in the country and executing on your dreams with purpose and speed, join us!

About the Role

We are building an in-house team to maintain and contribute to our internal Apache Kafka distribution. This is not an operations role — you will work on the Kafka codebase itself: the broker, the KRaft controller, the protocol, the clients, and the storage layer. You will be our technical anchor for all things Kafka internals, driving upstream contributions, backporting critical fixes, and shaping our internal distribution to meet the needs of a large-scale production fleet.

We already do this successfully with GlusterFS, where we maintain an in-house distribution backed by deep upstream expertise. We want to replicate that model for Kafka.