Senior Software Engineer; Python + Distributed systems
Salário Estimado
R$ 12.167,00 - R$ 19.000,00
Regular
Score da Vaga
Descrição da Vaga
Position: Senior Software Engineer (Python + Distributed systems) Join to apply for the Senior Backend Engineer (Python + Distributed systems) role at Scribd, Inc.
About The Company At Scribd (pronounced “scribbed”), our mission is to spark human curiosity.
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 authentic, bold, and collaborative, prioritizing the customer while balancing individual flexibility and community connections.
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 to enable content discovery for millions of users worldwide.
Tech Stack Our backend systems are primarily built in Python.
We leverage AWS services such as Lambda, ECS, SQS, and Elasti Cache for event‑driven and distributed processing.
Airflow, Spark, Databricks, Terraform, and Datadog support orchestration, data processing, and observability.
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 on AWS, supporting Scribd’s content enrichment and metadata systems.
You’ll work closely with cross‑functional teams to deliver reliable backend services that integrate machine learning models and LLM‑based components when needed.
Key Responsibilities • Provide technical leadership, mentorship, and guidance to engineers across the organization, driving secure coding best practices.
Requirements • 7+ years of professional software engineering experience with a focus on backend or distributed systems development.
Experience with Scala is a plus. • Expertise in designing and architecting large‑scale event‑driven and distributed systems.
Compensation Base pay ranges: San Francisco – $146,500 to $228,000; other U.
S. locations – $120,000 to $217,000; Canada – $153,000 CAD to $202,000 CAD.
This position also offers competitive equity, benefits, and additional compensation.
Benefits, Perks, And Wellbeing At Scribd • Healthcare insurance (Medical/Dental/Vision) – 100% paid for employees.
Requisitos
- We’re seeking a Senior Software Engineer with deep experience building event‑driven, distributed, and scalable systems in Python
- 7+ years of professional software engineering experience with a focus on backend or distributed systems development
- Strong proficiency in Python (5+ years)
- 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
- Familiarity with data processing frameworks (Spark, Databricks) and workflow orchestration tools
- Experience integrating ML or LLM‑based models into production systems
Responsabilidades
- Airflow, Spark, Databricks, Terraform, and Datadog support orchestration, data processing, and observability
- 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 deliver reliable backend services that integrate machine learning models and LLM‑based components when needed
- 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
Benefícios
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