Job description

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. CULTURE AT SCRIBD, INC. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. About the team and role: - Core Infrastructure builds and operates the foundations of Scribd, Inc.: the paved roads of cloud infrastructure, networking, databases, and observability that let every product team move fast with confidence. Over the past two years, our charter has grown, and today we own the Content Library, the unified storage and governance platform for all content across Scribd®, Slideshare®, Everand™, and Fable. - The Content Library is one of the more interesting storage problems you'll find anywhere. Nearly twenty years of accumulated content, hundreds of billions of objects in S3, served to hundreds of millions of people every month. It provides transactional storage, dataset transforms with full lineage tracking, low-latency online reads, and the governance layer (access control, trust, deletion propagation) for our most valuable asset: the content that powers our products and our inference-driven features. - The core of the platform is written in Rust and built on the excellent Rust data ecosystem (Apache Arrow, Parquet, and DataFusion), with a Python "userland" that teams across the company contribute to directly. If you want a taste of the work, read about Content Crush on our tech blog: tech.scribd.com - This role will join an existing team of Senior, Staff, and Principal engineers building the Content Library and Core Infrastructure of Scribd, Inc. for all our production datastores. Working alongside the Content Library's architect and lead engineer, you'll take ownership of the application codebase, drive feature development forward, and help shape where the platform goes as it becomes the foundation for all content at Scribd, Inc. About you: - You're a systems engineer who loves owning software end-to-end: design, implementation, deployment, operations, and the inevitable "why is this slow?" investigations. - You're pragmatic about technology choices; you keep things simple, and you write things down. Design docs, runbooks, and thoughtful code reviews are how you scale yourself. - You enjoy being the engineer other teams come to, whether that's reviewing their contributions, unblocking an integration, or turning an ambiguous ask into well-scoped work. - You've made agentic AI tools part of your daily engineering practice, and you know they accelerate great engineers rather than replace engineering judgment. Humans stay in the loop on quality, security, and ownership. What you will do: - Design, build, and operate the Content Library's core Rust services (transactional storage, transform coordination, and low-latency retrieval paths) at the scale of hundreds of billions of objects. - Own features end-to-end, from technical design through implementation, testing, deployment, and production operations (observability, on-call, and incident response for the systems you own). - Evolve the Python userland (the transform framework, tooling, and developer experience) and support engineers across the company who build on the platform through code reviews, guidance, and well-designed APIs. - Lead cross-functional projects with stakeholders in ML, search, product, and data teams: defining roadmaps, milestones, and technical designs that balance scalability, performance, cost, and delivery. - Drive performance and cost-efficiency across the stack: query execution (DataFusion), Parquet file layouts, S3 access patterns, caching strategies, and PostgreSQL/Aurora tuning. - Strengthen the platform's governance capabilities: data lineage, authorization and access controls, and deletion propagation across brands. - Raise the engineering bar on the team through mentorship, design reviews, and improvements to our developer environment, including making agentic AI workflows more effective within our codebase while preserving quality, security, and ownership. Requirements: - 10+ years of professional software engineering experience building backend, distributed, or data-intensive systems. - Production experience writing Rust and strong proficiency in Python. - A deep understanding of storage and data fundamentals: object storage (S3), columnar formats (Apache Parquet/Arrow), and relational databases (PostgreSQL and/or MySQL). - A track record of designing and operating high-throughput, low-latency services, including the operational side: metrics, tracing, alerting, and debugging production systems. - Demonstrated technical leadership: leading projects across team boundaries, writing design docs that build alignment, and mentoring engineers. - Experience with AWS (e.g., S3, Lambda, ECS, Aurora) and infrastructure-as-code workflows (e.g., Terraform). - Clear communication with both technical and non-technical stakeholders, and comfort turning ambiguous requirements into shipped software. Ideally, you have: - Direct experience with Apache DataFusion, arrow-rs, the parquet crate, or building query engines and database internals. - Contributions to open source, especially in the Rust data ecosystem (delta-rs, Arrow, DataFusion, etc.). - Experience with data governance at scale: lineage, access control, GDPR and deletion compliance. - A FinOps mindset: you've bent a cloud bill downward through architecture, not just instance right-sizing. - Experience building platforms that other engineers build on: SDKs, contribution models, and paved-road developer experience. - Recent, hands-on investment in agentic engineering practices, using tools like Claude Code as a core part of your development workflow while keeping human review at the center of quality and security. ----------------------------------------------------------------------------------------------- At Scribd, Inc. your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $176,500 [minimum salary in our lowest geographic market within California] to $275,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $145,000 [minimum salary in our lowest US geographic market outside of California] to $261,500 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between $184,500 CAD[minimum salary in our lowest geographic market] to $244,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. WORKING AT SCRIBD, INC. Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: United States: Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C. Canada: Ottawa | Toronto | Vancouver Mexico: Mexico City Benefits at Scribd, Inc. - 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 Get to Know Scribd, Inc. About Scribd, Inc. scribdinc.com Life at Scribd, Inc. bit.ly We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process. If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here support.scribd.com. 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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CULTURE AT SCRIBD, INC.
We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer.
This posting reflects an approved, open position within the organization.
You're a systems engineer who loves owning software end-to-end: design, implementation, deployment, operations, and the inevitable "why is this slow?" investigations.
You're pragmatic about technology choices; you keep things simple, and you write things down. Design docs, runbooks, and thoughtful code reviews are how you scale yourself.
You enjoy being the engineer other teams come to, whether that's reviewing their contributions, unblocking an integration, or turning an ambiguous ask into well-scoped work.
You've made agentic AI tools part of your daily engineering practice, and you know they accelerate great engineers rather than replace engineering judgment. Humans stay in the loop on quality, security, and ownership.
Design, build, and operate the Content Library's core Rust services (transactional storage, transform coordination, and low-latency retrieval paths) at the scale of hundreds of billions of objects.
Own features end-to-end, from technical design through implementation, testing, deployment, and production operations (observability, on-call, and incident response for the systems you own).
Evolve the Python userland (the transform framework, tooling, and developer experience) and support engineers across the company who build on the platform through code reviews, guidance, and well-designed APIs.
Lead cross-functional projects with stakeholders in ML, search, product, and data teams: defining roadmaps, milestones, and technical designs that balance scalability, performance, cost, and delivery.
Drive performance and cost-efficiency across the stack: query execution (DataFusion), Parquet file layouts, S3 access patterns, caching strategies, and PostgreSQL/Aurora tuning.
Strengthen the platform's governance capabilities: data lineage, authorization and access controls, and deletion propagation across brands.
10+ years of professional software engineering experience building backend, distributed, or data-intensive systems.
Production experience writing Rust and strong proficiency in Python.
A deep understanding of storage and data fundamentals: object storage (S3), columnar formats (Apache Parquet/Arrow), and relational databases (PostgreSQL and/or MySQL).
A track record of designing and operating high-throughput, low-latency services, including the operational side: metrics, tracing, alerting, and debugging production systems.
Demonstrated technical leadership: leading projects across team boundaries, writing design docs that build alignment, and mentoring engineers.
Experience with AWS (e.g., S3, Lambda, ECS, Aurora) and infrastructure-as-code workflows (e.g., Terraform).
Clear communication with both technical and non-technical stakeholders, and comfort turning ambiguous requirements into shipped software.
Direct experience with Apache DataFusion, arrow-rs, the parquet crate, or building query engines and database internals.
Contributions to open source, especially in the Rust data ecosystem (delta-rs, Arrow, DataFusion, etc.).
Experience with data governance at scale: lineage, access control, GDPR and deletion compliance.
A FinOps mindset: you've bent a cloud bill downward through architecture, not just instance right-sizing.

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rustpythonaimlaws

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Effort: quick

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