Software Engineer, Consumer Engineering
About this role
Reddit seeks a Product Backend Engineer to build and scale consumer-facing products used by hundreds of millions of users. You'll own the full lifecycle of major features—from technical design to deployment—working across feeds, recommendations, community tools, and monetization while balancing high performance with rapid experimentation.
What you'll do
- Partner with Product, Design, Data Science, and Client Engineers to translate business needs into scalable, low-latency technical solutions
- Own end-to-end delivery of major product initiatives including design, development, testing, rollout, and monitoring
- Design and build A/B experiments; analyze user behavior and conversion metrics using BigQuery, HEX, or Firebase to inform engineering decisions
- Build and maintain scalable APIs (GraphQL, REST, gRPC) and distributed backend services optimized for consumer performance
- Establish engineering best practices, improve developer workflows, and mentor teammates on technical rigor
- Operate large-scale distributed systems in high-concurrency environments serving hundreds of millions of daily active users
What they're looking for
- Backend development in Go, Python, Java, Kotlin, Rust, or C++
- API design and implementation (GraphQL, REST, gRPC)
- Large-scale distributed systems architecture
- Data analysis and A/B experimentation
- Cross-functional collaboration and communication
- System performance optimization and observability
- Software lifecycle management (design, testing, deployment)
- Proficiency with data tools like BigQuery, HEX, or Firebase
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Reddit builds and operates a large-scale platform serving millions of users, with data infrastructure, advertising systems, and notification products at its core. The company is hiring Software Engineers, Machine Learning Engineers, and Fullstack Engineers to enhance data pipelines, optimize ad delivery, and scale user-facing features.
- Website
- reddit.com
Likely interview questions
- Walk us through a time you designed a scalable API for a high-traffic feature—what trade-offs did you make and why?
- How have you used experimentation and data analysis to inform backend engineering decisions in a product-driven environment?