Responsibilities
- Own the support operating model and redesign it around automation and agentic AI rather than linear headcount growth.
- Design, deploy, and continuously improve agentic support systems across the full lifecycle: triage, resolution, escalation, and follow-up.
- Build the knowledge and data infrastructure these systems depend on, including knowledge bases, retrieval systems, and the telemetry that feeds them.
- Define and instrument the metrics that prove the model works: deflection rate, automated resolution rate, cost-to-serve, time-to-resolution, and CSAT.
- Integrate support tooling with the product, internal systems, and customer telemetry so that resolution becomes increasingly automated over time.
- Partner with Product and Engineering to convert recurring support signals into product fixes and self-service capabilities.
- Maintain support quality and SLAs for a technical cybersecurity customer base throughout the transition.
- Lead a small, high-leverage team of support and automation engineers, hiring for technical and systems capability.
Requirements
- A demonstrated track record of operationalizing agentic AI or automation in a technical support environment, with measurable deflection and cost-to-serve outcomes.
- A strong systems and engineering orientation. You are comfortable with APIs, integrations, data pipelines, LLM-based tooling, and support platform configuration.
- Experience supporting a technical B2B SaaS product. Cybersecurity, identity, or SaaS security context is strongly preferred.
- Fluency in support of economics and the metrics that govern cost-to-serve and scale.
- The ability to own and execute the technical roadmap for the support function end-to-end.
Nice to Have
- An engineering or technical IC background.
- Direct experience building or integrating LLM and agent frameworks.
- Prior hands-on support engineering experience in a security or infrastructure product.
