Backend Software Engineer; Python

Join to apply for the Backend Software Engineer (Python) role at Scribd, Inc.

Mid‑Senior level

Full‑time

Engineering and Information Technology

Industries:
Software Development

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 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 in balancing individual flexibility and community connections. With our flexible work benefit, Scribd Flex, employees can choose the daily work‑style that best suits their needs. We also prioritize intentional in‑person moments to build collaboration, culture, and connection; occasional in‑person attendance is required for all employees regardless of location.

We hire for “GRIT”—the intersection of passion and perseverance toward long‑term goals. We look for someone who can set and achieve goals, achieve results within responsibilities, contribute innovative ideas and solutions, and positively influence the broader team through collaboration and attitude.

The ML Data Engineering team powers metadata extraction, enrichment, and content understanding across all Scribd brands. We process hundreds of millions of documents and billions of images, delivering high‑quality metadata to enable content discovery and trust for millions of users worldwide. Our systems operate at massive scale, supporting diverse datasets such as user‑generated content, ebooks, audio books, 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.

We’re seeking a Software Engineer II 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 opportunity to work on cutting‑edge generative AI and metadata enrichment problems at a truly global scale.

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

• Design and implement event‑driven, distributed systems to extract, enrich, and process metadata from large‑scale document and media datasets.
• Build and maintain scalable APIs and backend services for high‑throughput content processing.
• Leverage AWS services (ECS, Lambda, SQS, Elasti Cache, Cloud Watch) to design and deploy resilient, high‑performance systems.
• Collaborate with cross‑functional teams to deliver backend solutions that power ML‑driven features.
• Optimize and refactor existing backend systems for scalability, reliability, and performance.
• Ensure system health and data integrity through monitoring, observability, and automated testing.

• 5+ years of professional software engineering experience in Python or distributed systems development.
• Strong proficiency in Python (3+ years). Experience with Scala is a plus.
• Proven experience designing and building event‑driven, distributed, and scalable systems.
• Hands‑on experience with AWS services (ECS, Lambda, SQS, SNS, Cloud Watch, etc.).
• Experience with infrastructure‑as‑code tools such as Terraform.
• Solid understanding of system performance, profiling, and optimization.
• Bachelor’s degree in Computer Science or equivalent professional experience.
• Bonus:
  Familiarity…