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Applied AI Specialist

Dallas🌐 Remote💼 Full-time💰 $75,000–$75,000🗓 2026-07-14 → 2026-07-31

Core

Apply AI in practical, measurable ways to improve customer/member support workflows, client experience, and internal operations for a health insurance startup.

Role type

Applied AI Specialist (Customer Experience & Operations)

Builds

Intercom Fin (AI-powered customer support tool) and broader AI-enabled workflows for health insurance clients

Domain

Health Insurance / Customer Experience / AI Operations

Deliverable

product features

Required skills

Customer support workflows, operational problem solving, analytical thinking, clear writing, cross-functional collaboration, AI tool evaluation, knowledge management, process improvement, data gap identification, pilot program management

Preferred skills

Technical skill development, compliance guardrail design, success metric definition, feedback loop creation

Technologies

Intercom Fin

Responsibilities

Own day-to-day performance, quality, and improvement of Intercom Fin; Monitor Fin metrics such as resolution rate, escalation rate, customer satisfaction, conversation quality, and recurring failure patterns; Review unresolved or escalated conversations to identify root causes and improvement opportunities; Improve Fin knowledge sources, instructions, workflows, routing, escalation logic, and guardrails; Partner with CX, Product, Compliance, Operations, Sales, Marketing, and technical teams to ensure AI-powered experiences are accurate, helpful, compliant, and aligned to business goals; Identify content, process, configuration, or data gaps that prevent AI tools from delivering a great user experience; Support internal pilots and beta tests for expanded AI use cases, including experiences beyond traditional customer support; Help define requirements, success metrics, test plans, rollout steps, and feedback loops for AI-enabled workflows; Evaluate when Intercom Fin is the right solution and when another tool, workflow, automation, or process change may be a better fit; Document learnings, risks, decisions, and recommendations so AI improvements can scale responsibly

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