Staff Engineer
PhonePe
| Company | PhonePe |
| Category | Engineering |
| Location | Bangalore |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 3 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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.
Key Responsibilities
Own our internal Kafka distribution: branch management, patch curation, release cutting, upgrade planning
Contribute upstream to Apache Kafka — bug fixes, KIPs, code reviews, design discussions
Diagnose and fix deep broker/controller issues: replication, partition reassignment, KRaft consensus, log storage, ISR management, protocol handling
Build custom patches for production needs that aren't suitable for upstream (performance tuning for our workload profile, observability hooks, operational safety valves)
Establish engineering practices for Kafka development within the team: how we test, how we benchmark, how we validate patches before rolling them out
Mentor a supporting engineer and grow the team's capability over time
Act as the internal authority on Kafka internals — advise platform teams on configuration, capacity planning, and architectural decisions that require knowledge of broker behavior
Act as the primary interface for audit and compliance teams, ensuring PhonePe Kafka distribution meets various compliance and regulatory standards
What are we looking for?
Deep familiarity with the Kafka codebase — you have read, modified, and debugged the broker, controller, or client internals. Not just operated Kafka, but worked on it.
Track record of upstream contribution — committed patches, participated in KIP discussions, reviewed PRs, or equivalent engagement with the Apache Kafka community. Active committer/PMC status is strongly preferred but not strictly required if your contribution history demonstrates equivalent depth.
Strong distributed systems fundamentals — consensus protocols, replication, exactly-once semantics, log-structured storage, distributed state machines. You understand these not as buzzwords
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