redoxengine - Redox - Customer Success Operations & AI Agent Manager
Requirements
• 4–6+ years in CS Operations or a closely related function in B2B SaaS • Hands-on AI agent or workflow deployment — you've built and shipped LLM-based automations (using Claude, GPT-4, or comparable tools) that reduced measurable human effort in a business context; awareness of AI tools is not sufficient • Working knowledge of prompt engineering fundamentals — you understand how to write, test, and iterate on prompts; you know what makes an agent reliable vs. just impressive in a demo • Strong written communication: you'll be writing and refining agent copy, escalation logic, and internal documentation constantly • Comfort with ambiguity and a track record of prioritizing well when everything feels urgent • Familiarity with data privacy considerations in enterprise software, particularly around customer data handling • Experience designing agent governance frameworks — prompt quality standards, escalation logic, tone guidelines, accuracy thresholds, and testing protocols • Background in LLM evaluation, AI product management, or agentic workflow tooling (e.g., n8n, Make, Zapier AI, or similar) • Experience in healthtech or working with regulated data environments — or genuine eagerness to get up to speed on HIPAA constraints as they apply to AI outputs • Exposure to HL7, FHIR, or EHR ecosystem concepts — or a demonstrated ability to develop technical domain fluency fast • Experience with CS platforms such as Vitally, Salesforce, Zendesk, or comparable tools • ## Software Platform/Tools • Required: Claude, Vitally, Salesforce, Zendesk, Zapier • Preferred: SQL or data visualization tooling; additional automation or integration platforms
Responsibilities
• AI Agent Management: • Audit the AI agents already being built across the CS team — document what exists, where quality gaps are, and what needs governance • Define standards for how agents are built, tested, and maintained: prompt quality, escalation logic, tone, and accuracy thresholds • Own the activation and configuration of AI features in existing CS tools as they are turned on — not just the toggle, but the setup, testing, and rollout • Monitor agent performance via CSAT, deflection rates, resolution accuracy, and escalation patterns — and act on what the data shows • Design clean handoff points between AI agents and human CSMs, ensuring context is preserved and customers don't feel the seam • Partner with Legal and Compliance to ensure agent interactions meet HIPAA obligations and do not surface PHI inappropriately • Channel the team's existing agent-building energy into a shared framework — libraries, approved tools, quality standards — so individual experiments can be scaled safely • CS Operations: • Own, administer, and continuously improve the CS tooling stack including Vitally, Salesforce, Zendesk, and Zapier • Maintain CRM data integrity, health scoring logic, and reporting infrastructure that CSMs and leadership depend on daily • Build and maintain playbooks, process documentation, and onboarding materials for the CS team • Produce recurring reporting on retention, expansion, CSAT, and CSM productivity for CS leadership • Identify and eliminate manual work through light automation, even before formal AI agent deployment
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