Software Engineer, Backend-leaning Full Stack or Backend; Runner Team

Overview

About Zapier We’re humans who simply think computers should do more work.

At , we’re not just making software-we’re building a platform to help millions of businesses globally scale with . Our mission is to make automation work for everyone by delivering products that delight . You’ll collaborate with brilliant people, use the latest tools, and leverage the flexibility of remote work. Your work will directly fuel , and as they grow, so will you.

Engineer, Backend-leaning Full Stack or Backend

Job Posted:
October 20th, 2025

Location:

North America

Hi there! Zapier’s Workflow Zone is responsible for the core engine that powers our automation platform. As more teams and organizations depend on Zapier to automate critical workflows, we’re investing in scaling the capabilities, reliability, and intelligence of our core product experience. If you’re passionate about building robust systems, enabling advanced user workflows, and shaping the future of automation, we’d love to hear from you.

The Runner team is responsible for ensuring the reliability, consistency, and scalability of Zap execution. We’re focused on the core infrastructure that powers Zapier’s workflows, including scaling for high volume and reducing latency across millions of executions daily.

• In this role, you’ll:
  
  Develop and maintain Zapier’s execution engine, scaling it to handle millions of daily runs
• Improve system performance, reduce latency, and strengthen failure handling
• Design and implement execution primitives that power reliable automation
• Collaborate across infrastructure, product, and platform teams on core system design
• Proposed amendments
  
  Design, implement, and scale Zapier’s execution engine to support millions of daily task runs with high reliability and low latency.
• Optimize system performance through improved queuing strategies, latency reduction, and stronger fault tolerance.
• Architect and evolve core execution primitives that underpin reliable and observable automation at scale.
• Build resilient distributed systems on AWS, with a focus on throughput, failover, and degradation handling.
• Develop and refine sharding and queuing strategies to ensure task fairness and efficient load distribution across the system.
• Implement coordinated work-packing techniques to effectively manage third-party service limits and partner API throttling.
• Collaborate with infrastructure, product, and platform teams on system design, cross-cutting features, and long-term architecture.
• Participate in on-call rotations and own time-to-execution SLAs ensuring fast and reliable task initiation across workflows.
• This is a foundational team at the platform layer-ideal for engineers who like deep technical challenges and shipping resilient, high-scale services.

• We’re looking for experienced engineers who bring:
• Strong backend experience with Python building reliable, scalable, and observable distributed systems.
• Experience with infrastructure observability tooling (e.g. Databricks, Looker, Grafana, Graylog), combining data engineering skills with a data-driven approach to reliability and team culture
• Experience architecting, building, debugging and operating distributed systems at scale is essential.
• Familiarity with AWS primitives, including S3, SQS, Lambda, RDS, etc.
• Familiarity with relational databases like Postgre
  
  SQL or MySQL, and the ability to model, query, and optimize data effectively
• Experience designing and consuming RESTful APIs, building event-driven systems, and working with data integrations across services
• Proven ability to lead complex technical projects-owning design decisions, balancing tradeoffs, and guiding implementation across multiple contributors
• You proactively coach and support teammates, foster growth through mentorship, and contribute to a culture of feedback and continuous improvement
• You navigate ambiguity with confidence-able to clarify priorities, align stakeholders, and drive toward meaningful outcomes even when goals shift
• You’ve used AI tooling for work or personal use. You explore new tools, workflows, and ideas to make things more efficient, and are eager to deepen your understanding of AI and use it regularly.

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