Senior Conversational Designer

Hello Patient•Austin, TX

About The Position

Hello Patient is hiring a Senior Conversational Designer to shape how our AI agents communicate with patients in real, high-stakes conversations. This is a senior individual contributor role that sits at the intersection of product, behavior, and language. You’ll improve and refine live agent behavior in production — helping our systems become more effective, more reliable, and more human in real-world conditions. Our agents have seconds to build trust, handle objections, and complete tasks without human intervention. You’ll work closely with Product, Engineering, and QA to evaluate how conversations perform in production, identify failure modes and missed opportunities, and translate those insights into better conversational behavior. You’ll also help raise the bar for conversational quality across the team by reviewing work, contributing frameworks and best practices, and helping less experienced teammates develop stronger instincts. We’re looking for someone who combines strong language judgment with practical experience building or improving AI-driven conversational systems. The right person is thoughtful, rigorous, highly curious, and excited by solving ambiguous problems through iteration in a fast-moving environment.

Requirements

2+ years of experience in forward deployed engineering, implementation, solutions, technical account management, or similar high-context customer-facing technical roles
Experience designing, improving, or evaluating AI-driven conversational experiences in production
Strong prompt writing and systems-thinking skills
Exceptional critical thinking and problem-solving skills
Strong instinct for human behavior, language, and how trust is built in conversation
Ability to assess conversational quality and give clear, actionable feedback
Desire to take on greater responsibility for team coordination, prioritization, and mentorship as the function grows

Nice To Haves

Experience working on AI agents, chatbots, or LLM-based products in production
Experience operating across multiple customers, workflows, or deployments at once
Strong judgment in prioritizing production issues and balancing competing stakeholder needs
Experience creating frameworks, standards, or training materials for other team members
Comfort operating in ambiguity and moving quickly in an early-stage environment

Responsibilities

Design AI Behavior in Real Conversations: Define how agents respond across real-world scenarios (frustration, urgency, confusion, resistance). Design conversations that balance empathy, efficiency, and task completion. Help agents establish trust fast and guide users toward successful outcomes.
Improve Performance & Outcomes: Analyze real interaction data to identify failure points, drop-offs, and opportunities to improve outcomes. Optimize for containment rate, task completion, and patient experience. Iterate quickly based on production metrics, QA feedback, and qualitative conversation review. Help define the systems, processes, and standards that allow the conversational design function to scale.
Own Inbound Requests & Prioritization: Own or help manage the intake and prioritization of conversational issues coming from QA and customer-facing teams. Triage and prioritize live conversational issues across customers, balancing urgency, effort, and business impact. Move fluidly across multiple customer environments, diagnosing failures and driving fixes in production. Define what “high / medium / low priority” means for conversational issues.
Build & Refine Prompting Systems: Write, test, and improve structured prompts that shape agent behavior, reasoning, and tone. Partner with Product and Engineering to translate conversational logic into production systems. Develop reusable patterns and frameworks that scale across conversation types and use cases.
Raise the Standard: Review conversational work and identify where approaches need to be strengthened. Partner closely with QA to improve issue reporting, debugging workflows, and signal quality. Identify patterns across conversations and translate them into clear fixes. Help build standards, documentation, and training materials that improve team quality over time.