Cribl
Software Engineer, Core Platform
Remote - United States (Remote)From $175kfull-timemidAdded today
About this role
Cribl seeks a Backend Software Engineer to develop scalable distributed systems for their AI-powered telemetry platform. You'll design and build backend services handling real-time data ingestion, processing, and routing while collaborating with cross-functional teams on the Core Platform team.
What you'll do
- Develop backend systems and APIs for data ingestion, processing, and routing at scale
- Design, code, test, and maintain robust software solutions with end-to-end ownership
- Collaborate with engineers, designers, and product managers to translate requirements into implementations
- Create comprehensive test plans and automated tests to ensure product quality
- Participate in on-call rotation and support responsibilities for production systems
- Drive initiative to help the team achieve outcomes and improve internal tools and processes
What they're looking for
- Node.js and TypeScript
- Data structures and algorithms
- Distributed systems and scalability principles
- Systems-level debugging and performance profiling
- Cloud platform development
- Networking fundamentals
- Agile development practices
- Root cause analysis and troubleshooting
Benefits
- Health, dental, and vision insurance
- 401(k) retirement plan
- Equity compensation
- Paid time off and paid holidays
- Fertility treatment benefit
- Short-term disability and life insurance
Opens the official application on the employer’s site. No login required.
Cribl
Cribl builds an AI-powered telemetry platform for processing and analyzing enterprise data at scale. The company is hiring backend engineers to develop core distributed systems and sales engineers at various levels to drive adoption among enterprise customers.
- Website
- cribl.io
Likely interview questions
- Describe your experience building large-scale data processing systems—what challenges did you encounter and how did you solve them?
- Tell us about a time you debugged a complex performance issue in a distributed system. What tools and techniques did you use?