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Salary: USD 180,000 - 200,000 / annual
Parabola is a workflow automation platform that helps teams organize, transform, and automate data from any source—PDFs, emails, spreadsheets, and more—without requiring engineering support. Customers like Brooklinen, On Running, and Flexport use Parabola to save hundreds of hours automating previously manual work.
As a Senior Site Reliability Engineer, you will be a core member of a small, rapidly growing team responsible for ensuring Parabola's platform operates reliably and scales efficiently. Your work will span performance optimization, developer experience, security & compliance, and foundational architecture. You'll be on-call and will drive continuous improvements to our technical operations.
Key responsibilities include:
- Monitoring core business-logic software and defining SLOs/SLAs that guide incident response and reliability improvements
- Extending and managing our infrastructure stack to support business-critical customer workflows
- Building and maintaining mental and documented models of our systems to estimate risk, plan projects, and debug efficiently
- Collaborating with engineering and leadership, providing specialized expertise in site reliability
- Working on our orchestration logic (recently rebuilt on Temporal) that efficiently runs tens of thousands of concurrent workflows
- Advising major backend engineering projects from planning through release
- Optimizing services for scalability, stability, and observability as the customer base and product sophistication grow
- Improving developer experience and engineering processes, including navigating opportunities and challenges from LLM coding agents
You'll work hybrid from either our NYC or SF office, approximately 3 days per week on-site.
Requirements:
- 5+ years of SRE, DevOps, or Platform engineering experience
- Proven track record building efficient, performant, and extensible systems
- Experience maintaining quantitative site reliability metrics and demonstrating judgment about appropriate SLO/SLA strictness
- Familiarity with containerization and orchestration tools (Docker, Kubernetes) and their interaction with backend services, plus Linux proficiency
- Experience implementing and managing AWS infrastructure
- Strong communication skills and enthusiasm for collaborative teamwork with mutual support and thoughtful critique
- Comfort asking for and offering help
Nice to haves:
- Experience with Temporal
- Experience building AI platforms or tooling/systems behind AI products
- Kubernetes/Helm expertise (we use Amazon EKS)
- Infrastructure-as-a-service (IaaS) tool implementation and deployment
- CI/CD pipeline management for multiple environments and developer experience improvements
- Cloud storage or data modeling product experience
- Early-stage startup experience
