Senior Backend Engineer

1 day ago Be among the first 25 applicants 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 bold, debate, commit, and embrace plot twists; every employee is empowered to take action and prioritize the customer. We pride ourselves on balancing individual flexibility and community connections: through our flexible work benefit, Scribd Flex, employees – in partnership with their manager – can choose the daily work-style that best suits their needs. Intentionally in‑person moments build collaboration, culture, and connection; occasional in‑person attendance is required for all Scribd employees, regardless of location. 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. Working at the intersection of machine learning, data engineering, and distributed systems, we collaborate 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. Compensation 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. In San Francisco, the expected salary range is between $146,500 and $228,000. Outside California, the range is $120,000 to $217,000. In Canada, the range is $153,000 CAD to $202,000 CAD. This position also eligible for competitive equity ownership and a comprehensive benefits package. Location Eligibility Employees must have their primary residence in or near one of the following cities. 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 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. Additional Information Want to learn more about life at Scribd? 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 at any point in the interview process by emailing 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. #J-18808-Ljbffr