Senior Backend Engineer; Python + Distributed systems

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 products:
Everand, Scribd, Slideshare, and Fable. We support a culture where employees can be real and bold, debate and commit, and prioritize the customer. We balance individual flexibility with community connections through Scribd Flex, allowing flexible work style and intentional in‑person moments. We hire for GRIT—setting and achieving goals, results, innovative ideas, and positive influence.

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 scale, supporting diverse datasets such as user‑generated content, ebooks, and audio books. We work at the intersection of machine learning, data engineering, and distributed systems, collaborating with applied research and product teams to deploy scalable ML & LLM‑powered solutions.

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 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 components when needed. This role offers the opportunity to work on generative AI and metadata enrichment problems at a truly global scale.

Python, AWS Lambda, ECS, SQS, Elasti Cache, Airflow, Spark, Databricks, Terraform, Datadog.

• 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, Elasti Cache, Cloud Watch) 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.

• 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, Cloud Watch, 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.

San Francisco: $146,500 – $228,000 (USD). Outside California: $120,000 – $217,000. Canada: $153,000 CAD – $202,000 CAD. Eligible for competitive equity and comprehensive benefits.

Employees must have their primary residence in or near the following cities:

• United States:
  Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles,…