> Markdown version of [/jobs/ext/4425338-staff-software-engineer-discovery-platform](https://www.wearedevelopers.com/jobs/ext/4425338-staff-software-engineer-discovery-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer, Discovery Platform

- **Company:** Whatnot Inc.
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $230,000.0 - $290,000.0
- **Contract:** Permanent contract
- **Skills:** Distributed Systems, Elasticsearch, Machine Learning, Recommender Systems, Redis, Software Engineering, Data Streaming, Backend, Event Driven Architecture, Information Technology, Apache Kafka, Stream Processing, OpenSearch
- **Published:** October 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6cf57c16992f1776

## About the Role

People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it., * A bachelor's degree in Computer Science, a related field, or equivalent practical experience.

 * 8+ years of full-time software engineering experience, including building and operating large-scale distributed systems in production.
 * A track record of leading substantial technical initiatives across teams, defining problems clearly, aligning partners, and shipping solutions through ambiguity.
 * Experience designing reliable, low-latency backend systems such as search infrastructure, retrieval services, event-driven systems, or streaming data pipelines. Experience with search or recommendations at scale is a strong plus.
 * Hands-on experience with technologies such as OpenSearch or Elasticsearch, Redis or Valkey, and Kafka or similar streaming systems. We value strong fundamentals and relevant systems experience over an exact match to our tools.
 * An understanding of how recommendation systems fit together, including candidate generation, ranking, and feature serving, and the ability to partner effectively with machine learning engineers.
 * Strong product instincts: you connect performance and reliability decisions to whether buyers discover things they want and whether sellers reach the right audience.
 * A commitment to hands-on engineering, with the judgment to write code, document architectural decisions, and drive alignment when needed.
 * Experience mentoring engineers and improving the quality of designs, code, and operational practices.

## Description

Discovery shapes what buyers see when they open Whatnot, from the For You feed and search results to recommended live shows and listings. Discovery Platform builds the systems that make those experiences possible. Our team owns search infrastructure on OpenSearch, a low-latency feature and key-value serving layer, the retrieval framework that assembles feeds, and the pipelines that keep our indices fresh. Teams across Discovery and beyond rely on these systems to build and ship products., We're hiring a Staff Software Engineer to lead technical work across Discovery Platform and product-facing retrieval and recommendations. You'll spend roughly 60% of your time strengthening the platform's capacity, reliability, and shared building blocks, and 40% partnering with ranking and machine learning engineers to bring new discovery experiences to buyers. You'll join a small team of senior backend engineers who own their systems from design through production and on-call.

This is a high-impact, hands-on role for someone who finds the most important problems in ambiguous spaces, creates a path forward, and builds solutions that improve both the buyer experience and the pace at which other teams can ship.

What You'll Do:

 * Design and evolve search and serving infrastructure that performs reliably through live shopping traffic spikes, including our largest sales events.
 * Build retrieval systems that let feed and search teams add candidate sources safely and quickly.
 * Partner with ranking and machine learning engineers to bring models and features into production with the latency and freshness they need.
 * Set technical direction for Discovery Platform and influence roadmaps across partner teams, using data and product outcomes to guide decisions.
 * Own complex systems end to end, from architecture and implementation through production operations and on-call.
 * Raise the engineering bar through hands-on contributions, design and code reviews, and mentorship.