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Senior Backend Engineer, Content FoundationsScribd • San Francisco, California, United States
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Senior Backend Engineer, Content Foundations

Scribd
  • US
    San Francisco, California, United States
  • US
    San Francisco, California, United States
Jetzt Bewerben

Über

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise.
About the Team & Role The Content Foundations team builds the systems that power how content enters, evolves, and is delivered across Scribd. This includes everything from ingestion, metadata extraction, early quality controls, and the core artifacts that power search, recommendations, AI/ML systems, and the reading and listening experience.
Why this role is interesting You’ll be joining a small and growing team working at the boundary between messy, real‑world content and highly structured systems, where file formats vary, metadata can be inconsistent, and scale amplifies every edge case. Scribd operates a hybrid catalog of premium publisher content and user‑generated uploads, spanning diverse formats, decade‑old systems, and modern services evolving alongside them. Decisions made at ingestion ripple across every downstream system.
Current focus areas
Content quality and early‑stage validation
Spam detection at upload time
OCR and content extraction for ML/LLM use cases
Evolving content formats to support downstream AI workflows
Security hardening in partnership with Content and Infra‑Security
Architectural improvements to how content and metadata flow across systems, including improving data observability for complex, asynchronous pipelines
What You’ll Do
Own and drive technical initiatives: Lead the design, implementation, and scaling of core content systems, including ingestion pipelines, metadata services, and content processing workflows.
Build scalable, reliable systems: Design robust solutions that handle diverse file formats and edge cases while maintaining high availability and strong data integrity.
Collaborate across teams: Partner with Content Security, ML Data Engineering, Search & Discovery, the Content Library squad, and Product to build systems that balance performance, scalability, and user experience.
Improve content quality and discoverability: Work with ML and Discovery teams to improve metadata extraction, classification, and enrichment that power personalization and search.
Drive platform evolution: Identify architectural opportunities, propose new capabilities, and help evolve Scribd’s content platform to meet growing scale and complexity.
Mentor and lead: Provide technical guidance across teams and help raise the bar on system design, data modeling, and production excellence.
Champion AI‑driven engineering: Help shape how we leverage AI and LLM‑based systems within content processing, while maintaining a high bar for quality and reliability. In addition to building AI into our pipeline, you will help lead the team’s adoption of AI coding agents and advanced developer tools to accelerate how we build and scale our systems.
Who You Are
7+ years of software engineering experience, including experience navigating the trade‑offs of refactoring legacy systems while maintaining high availability.
Experience building and scaling ingestion pipelines, ETL workflows, or document/content processing systems.
Comfortable working with messy data and building systems resilient to real‑world inputs.
Proficient in Ruby, Python, or Go (our stack includes all three).
Experience with AWS (Lambda, SQS/SNS, S3, Step Functions) and distributed workflows.
Strong database design skills (SQL and/or NoSQL), with a focus on reliability and resilience.
Able to communicate technical complexity to non‑technical stakeholders and have a track record of building consensus across cross‑functional engineering teams.
Enjoy mentoring others and working collaboratively across teams.
Nice‑to‑Have
Experience with document formats (PDF, ebooks, markdown) and internals (OCR, parsing, transformation).
Familiarity with ML/AI systems (embeddings, chunking, retrieval pipelines).
Background in spam or content security systems.
Benefits
Scribd Flex (flexible work model)
Comprehensive health, dental, and vision coverage
Mental health support and disability coverage
Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
Paid parental leave and family support benefits
Retirement matching and employee equity
Learning and development programs and professional growth opportunities
Wellness and home office stipends
Complimentary access to the Scribd, Inc. suite of products
Enterprise access to leading AI tools
Compensation In the United States, San Francisco: $146,500–$228,000. In California, other markets: $120,000–$217,000. In Canada: $153,000 CAD–$202,000 CAD. These ranges are based on local labor benchmarks and each role’s level and geographic location. The position is also eligible for competitive equity and a generous benefits package.
Equal Employment Opportunity Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
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  • San Francisco, California, United States

Sprachkenntnisse

  • English
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