Senior Software Engineer (Python + Distributed systems)

Scribd, Inc. is on a mission to advance human understanding through its products Scribd®, Slideshare®, Everand™, and Fable, which help billions of people worldwide move beyond access into insight, application, and expertise. Culture We support a culture where employees can be real and bold, debate, commit, and embrace plot twists. Every employee is empowered to take action while prioritizing the customer. Scribd Flex allows flexible work styles and locations, with occasional in‑person attendance required for all employees. 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 and billions of images, delivering high‑quality metadata that supports content discovery and trust for millions of users worldwide. Role Overview We are seeking a Senior Software Engineer with deep experience building event‑driven, distributed, and scalable systems in Python. In this role, you will design and optimize large‑scale data and service pipelines on AWS to support Scribd’s content enrichment and metadata systems. You will collaborate with cross‑functional teams to build reliable backend services that integrate machine learning models and LLM‑based components. Tech Stack Our backend systems are built primarily in Python and leverage AWS services such as Lambda, ECS, SQS, and ElastiCache. We also use Airflow, Spark, Databricks, Terraform, and Datadog for orchestration, data processing, and observability. Key Responsibilities Provide technical leadership, mentorship, and secure coding guidance across the organization. Design, implement, and scale event‑driven, distributed systems to extract, enrich, and process metadata from large‑scale datasets. Partner with Data Science, Infrastructure, ML Engineering, and Product teams to deliver robust, scalable systems. Contribute to the team’s engineering strategy, identifying gaps and proposing new initiatives. 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 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 focusing on backend or distributed systems. Strong proficiency in Python (5+ years); experience with Scala is a plus. Expertise in designing and architecting large‑scale event‑driven and distributed systems. Deep familiarity with AWS services (ECS, Lambda, SQS, SNS, CloudWatch, etc.). Experience with infrastructure‑as‑code tools such as 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. Benefits 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 Equal Opportunity Employer 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. #J-18808-Ljbffr Scribd