Scribd Inc

Staff Software Engineer (Backend) - Everand Core

$171KFull-time · San Francisco (Remote)
✓ Verified live on the employer's own system · added 30 days ago
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DevopsProcess ImprovementTeam LeadershipData AnalysisDistributed SystemsPythonTroubleshootingCad
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Full job description

As a Staff Software Engineer on the Everand Core team, you’ll help shape the future of how people discover, organize, and enjoy books. Everand is growing, and we’re evolving our reading and listening experiences to make stories more accessible, personal, and engaging for our readers.

You'll play a vital role in connecting readers with the stories they love by owning the backend platform that powers Everand's web and mobile experiences. This includes everything from rapid experimentation to the services driving discoverability, personalization, and our core consumption journeys. You'll work closely with engineers across search, recommendations, web, and mobile, as well as design and product partners, to align technical decisions with user needs and platform capabilities.

Along the way, you'll build systems that drive performance, personalization, and reliability, and help shape the technical direction of our backend team.

We value quality over speed, thoughtful planning over short-term hacks, and continuous improvement over “just good enough.” We’re looking for engineers who share these values and who are energized by writing clean, scalable code, trying new technologies, and collaborating with diverse teams.

We believe the best experiences come from teams who care deeply about the people they build for, and each other.

- Your main focus will be to set technical direction for the Everand backend: writing and socializing design documents, driving architecture reviews, and turning ambiguous product intent into concrete backend design.

- Own backend reliability and platform health, including staging, CI/CD, databases, queues, cost, and observability.

- Raise the ceiling for the team through PR review, mentorship, pairing, and by setting a high bar on design, testing, and ops.

- Be the Everand backend voice in cross-team planning, and the glue in cross-functional execution.

- Foster a culture of technical excellence while driving scalable, resilient, and observable systems that let teams move fast, simplify complexity, and deliver with confidence.

- Modernize legacy systems and eliminate technical debt to improve velocity and scalability.

- Partner with Product, Design, Analytics, and Web, Mobile, and ML Engineers to deliver backend systems that support experimentation and a single source of truth across platforms, using data, metrics, and telemetry to uncover trends, resolve anomalies, and guide the team with clarity and foresight.

- Champion a user-first mindset, grounding technical decisions in how they enhance the reading and listening experience.

- You bring significant experience in backend engineering, with a strong track record building and scaling distributed systems.

- You write clean, maintainable, and secure code in at least one modern backend language such as Ruby (preferred), Scala, Go, or Python.

- You have a keen eye for reliability and observability, and care about defining SLOs, implementing metrics and alerts, and debugging distributed systems.

- You have a proven track record of technical leadership: setting architectural direction, mentoring engineers, and driving large-scale migrations or modernization efforts.

- You thrive in cross-functional collaboration, holding your own with senior PM, design, and ML partners, and caring more about the system landing well than about being right.

- You enjoy mentoring, knowledge-sharing, and contributing to cross-team initiatives, including architecture review groups and design discussions that shape Scribd's engineering culture.

- You care deeply about the users; understanding what makes Everand impactful in their daily lives and translating that empathy into the systems you build.

- Experience improving reliability, latency, or throughput in large-scale distributed systems.

- Experience working alongside ML teams on recommendation or feed systems.

- Familiarity with experimentation or feature-flagging platforms.

In the state of California, the reasonably expected salary range is between $171,000 [minimum salary in our lowest geographic market within California] to $267,000 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $141,000 [minimum salary in our lowest US geographic market outside of California] to $254,000 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $179,000 CAD[minimum salary in our lowest geographic market] to $228,500 CAD[maximum salary in our highest geographic market].

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This posting was published by Scribd Inc on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.