Customer Success Operations & AI Agent Manager

Redox is on a mission to accelerate healthcare’s transformation with useful data. Redox Engine, a flexible interoperability platform, connects and powers real-time healthcare data exchange. With just one connection, data can be orchestrated across a growing network of 12,000+ systems and organizations, including 100+ electronic health record systems (EHRs). Redox processes over 1.2 billion messages per month across our health tech vendor, provider, payer, EHR, and life sciences customers.

Job 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

Required Skills & Experience

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4–6+ years in CS Operations or a closely related function in B2B SaaS

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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

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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

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Strong written communication: you'll be writing and refining agent copy, escalation logic, and internal documentation constantly

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Comfort with ambiguity and a track record of prioritizing well when everything feels urgent

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Familiarity with data privacy considerations in enterprise software, particularly around customer data handling

Preferred Skills & Experience

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• Experience designing agent governance frameworks — prompt quality standards, escalation logic, tone guidelines, accuracy thresholds, and testing protocols
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• Background in LLM evaluation, AI product management, or agentic workflow tooling (e.g., n8n, Make, Zapier AI, or similar)
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• 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
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• Exposure to HL7, FHIR, or EHR ecosystem concepts — or a demonstrated ability to develop technical domain fluency fast
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• Experience with CS platforms such as Vitally, Salesforce, Zendesk, or comparable tools

Software Platform/Tools

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Required: Claude, Vitally, Salesforce, Zendesk, Zapier

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• Preferred: SQL or data visualization tooling; additional automation or integration platforms