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Scribd

Senior Backend Engineer (Python + Distributed systems)

Posted Yesterday
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In-Office
23 Locations
120K-228K Annually
Senior level
In-Office
23 Locations
120K-228K Annually
Senior level
Seeking a Senior Software Engineer to design scalable backend services and optimize data pipelines in Python, working with AWS in a team-oriented environment.
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About The Company:

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our four products: Everand, Scribd, Slideshare, and Fable.

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.

When it comes to workplace structure, we believe in balancing individual flexibility and community connections.  It’s through our flexible work benefit, Scribd Flex, that employees – in partnership with their manager – can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location.

So what are we looking for in new team members? Well, we hire for “GRIT”. The textbook definition of GRIT is demonstrating the intersection of passion and perseverance towards long term goals. At Scribd, we are inspired by the potential that this can unlock, and ask each of our employees to pursue a GRIT-ty approach to their work. In a tactical sense, GRIT is also a handy acronym that outlines the standards we hold ourselves and each other to.  Here’s what that means for you: we’re looking for someone who showcases the ability to set and achieve Goals, achieve Results within their job responsibilities, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and attitude.

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.

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 love collaborating and investing time in our Scribd community, and we create intentional in-person moments with each other to build culture and connection. And, it is through our flexible work benefit – Scribd Flex – that we enable employees, in partnership with their manager, to choose the work-style that best suits their individual needs and preferences.


About the team:

The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across all Scribd brands. We process hundreds of millions of documents, billions of images, and deliver high-quality metadata to enable content discovery and trust for millions of users worldwide.

Our systems operate at massive scale, supporting diverse datasets like user-generated content (UGC), ebooks, audiobooks, and more. We work at the intersection of machine learning, data engineering, and distributed systems, collaborating closely with applied research and product teams to deploy scalable ML and LLM-powered solutions in production.

Role Overview:

We’re seeking a Senior Software Engineer with deep experience building event-driven, distributed, and scalable systems in Python. In this role, you’ll design and optimize large-scale data and service pipelines running on AWS, supporting Scribd’s content enrichment and metadata systems. You’ll work closely with cross-functional teams to design reliable backend services that integrate machine learning models and LLM-based components when needed. This role offers the opportunity to work on cutting-edge generative AI and metadata enrichment problems at a truly global scale.

Tech Stack:

Our backend systems are primarily built in Python, leveraging AWS services such as Lambda, ECS, SQS, and ElastiCache for event-driven and distributed processing. We also use Airflow, Spark, Databricks, Terraform, and Datadog for orchestration, data processing, and observability.

Key Responsibilities:

  • Provide technical leadership, mentorship, and guidance to engineers across the organization, driving secure coding best practices.

  • Lead the design, implementation, and scaling of event-driven, distributed systems to extract, enrich, and process metadata from large-scale document and media datasets.

  • Partner with Data Science, Infrastructure, ML Engineering, and Product teams to architect and deliver robust systems that balance scalability, high performance, and rapid iteration.

  • Contribute to the team’s engineering strategy, identifying gaps, proposing new initiatives, and improving existing frameworks.

  • Build and maintain scalable APIs and backend services for high-throughput content processing.

  • Leverage AWS services (ECS, Lambda, SQS, ElastiCache, CloudWatch) to design and deploy resilient, high-performance systems.

  • Optimize and refactor existing backend systems for scalability, reliability, and performance.

  • Ensure system health and data integrity through monitoring, observability, and automated testing.

Requirements:

  • 7+ years of professional software engineering experience with a focus on backend or distributed systems development.

  • Strong proficiency in Python (5+ years). Experience with Scala is a plus.

  • Expertise in designing and architecting large-scale event-driven and distributed systems

  • Strong cloud expertise with AWS services (ECS, Lambda, SQS, SNS, CloudWatch, etc.).

  • Experience with infrastructure-as-code tools like Terraform.

  • Solid understanding of system performance, profiling, and optimization.

  • Experience leading technical projects and mentoring engineers

  • Bachelor’s degree in Computer Science or equivalent professional experience.

  • Bonus: Familiarity with data processing frameworks (Spark, Databricks) and workflow orchestration tools.

  • Bonus: Experience integrating ML or LLM-based models into production systems.

At Scribd, 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 $146,500 [minimum salary in our lowest geographic market within California] to $228,000 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $120,000 [minimum salary in our lowest US geographic market outside of California] to $217,000 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $153,000 CAD[minimum salary in our lowest geographic market] to $202,000 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 is able to 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, Perks, and Wellbeing at Scribd

*Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work.

  • Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees

  • 12 weeks paid parental leave

  • Short-term/long-term disability plans

  • 401k/RSP matching

  • Onboarding stipend for home office peripherals + accessories

  • Learning & Development allowance

  • Learning & Development programs

  • Quarterly stipend for Wellness, WiFi, etc.

  • Mental Health support & resources

  • Free subscription to the Scribd Inc. suite of products

  • Referral Bonuses

  • Book Benefit

  • Sabbaticals

  • Company-wide events

  • Team engagement budgets

  • Vacation & Personal Days

  • Paid Holidays (+ winter break)

  • Flexible Sick Time

  • Volunteer Day

  • Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace.

  • Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation.

Want to learn more about life at Scribd? www.linkedin.com/company/scribd/life

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 [email protected] about the need for adjustments at any point in the interview process.

Scribd 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.

Top Skills

Airflow
AWS
Databricks
Datadog
Ecs
Elasticache
Lambda
Python
Spark
Sqs
Terraform

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