cribl
Staff Software Engineer, Cribl AI
At a Glance
- Location
- United States
- Work Regime
- remote
- Experience
- 8+ years
- Compensation
- ted environment Salary Range ($185,000 - $255,000) The salary for this role is
- Posted
- 2026-03-17T12:39:25-04:00
Key Requirements
Required Skills
Domain Knowledge
- Engineering
- Insurance
Benefits & Perks
o offers a generous benefits package which includes health, dental, vision,
Compensation & Benefits
The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus.
#LI-JB1
Bring Your Whole Self
Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We’re building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.
Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you’ll ever meet at
cribl.io/about-us
Responsibilities
5–8+ years of professional software engineering experience building and operating modern web applications in production
Proven fullstack experience, including designing and scaling React-based UIs and backend services/APIs
Deep expertise in TypeScript/JavaScript plus experience with at least one backend language/runtime (e.g., Node.js, Go, Java, or similar)
Hands-on experience with data and infrastructure: databases, APIs, observability, and integrating with third-party services in production environments
Experience building AI agent–driven conversational user interfaces and wiring them to robust backend and data systems
Hands-on experience with LLM application patterns (RAG, agents, prompt engineering) and how to implement them end-to-end, from prototype to production