| Title | Stage | AI score |
|---|---|---|
| Staff AI Security Engineer Staff AI Security Engineer to design, implement, and operationalize security and governance frameworks for Cribl's internal AI systems and workflows. This role focuses on enabling safe AI adoption by building shared infrastructure, security guardrails, and reusable patterns, addressing areas like API tokens, secrets management, shadow AI mitigation, AI telemetry, and compliance readiness. The goal is to provide a secure and governed platform for AI at Cribl. | Agent | 8 |
| Staff AI Platform Engineer, Corporate AI Systems Staff AI Platform Engineer responsible for designing, deploying, and operating a governed AI platform for internal systems and workflows. This role focuses on building the foundational infrastructure, security guardrails, and reusable patterns to enable secure and scalable AI adoption across the company, integrating with various enterprise systems and ensuring compliance. | Agent |
| 8 |
| Forward Deployed Solutions Lead This role involves acting as an embedded engineering partner for strategic enterprise customers, integrating Cribl's telemetry platform into their existing tools and workflows. The focus is on building custom solutions, search experiences, and data flows to meet specific customer needs, including those ahead of the product roadmap. The role also involves creating reusable assets like Packs and integrations, and bridging the gap between current customer requirements and future product development by providing feedback to the product and engineering teams. The core function is to engineer complex data and pipeline logic using JavaScript/Node.js and Cribl's framework to solve last-mile problems in large-scale IT and security environments. | Agent | 5 |
| Senior Data Scientist Senior Data Scientist to join and grow internal data science practice, using predictive models and advanced analytics to provide foresight into business outcomes. Role involves end-to-end data science initiatives, building and operationalizing ML models, evaluating model performance, conducting deep-dive analyses, applying statistical modeling and AI-assisted analytics, and communicating findings to stakeholders. Requires experience in experiment design, causal inference, predictive modeling, SQL, Python, and working with large datasets. Familiarity with leveraging LLMs as tools is a plus. | Agent | 5 |