AI Agent Product Manager
About The Position
Hello Patient is hiring a technical, high-agency AI Agent Product Manager to own the end-to-end delivery of AI agents in real customer environments. The company builds AI-powered voice, SMS, and chat agents that integrate into healthcare practices. Each new customer deployment involves new workflows, edge cases, integration requirements, and agent behavior. The role owns deployments from scoping through production go-live and manages the customer-facing roadmap for each deployment, including requirements, sequencing, and stakeholder tradeoffs. The position combines product ownership with hands-on agent building. The Product Manager gathers requirements directly from customers, translates them into agent logic and workflows, and implements behavior using prompts, guardrails, tools, and evaluations. The role designs Mia's behavior, ships production-ready multi-agent workflows, and iterates on performance through structured evaluation, testing, live-call review, and customer feedback. The Product Manager is the accountable owner for net-new deployments, coordinating with Conversational Design, Customer Engineering, and engineering teams. They scope integrations, manage timelines and stakeholder communication, unblock delivery, and prioritize requirements for new platform capabilities. They also identify patterns across launches, codify playbooks, and transition proven workflows and integrations to implementation teams.
Requirements
- At least 3 years in Product Management or a closely related role, such as technical program management at a product-led company or a founder or early employee performing PM work; alternatively, a technical background such as software engineering or forward-deployed engineering with PM-like experience.
- Strong technical product background and comfort with APIs, integrations, and understanding how systems connect.
- Experience shipping in ambiguous, fast-moving environments without an established playbook.
- Ability to work across functions through influence rather than authority.
- Ownership-oriented and action-biased, with willingness to make decisions and course-correct.
Nice To Haves
- Experience with AI-native products, agents, LLMs, or automation platforms, including hands-on prompt or agent building.
- Background in healthcare, revenue cycle, or other industries with legacy systems.
- Experience building, breaking, and refining bots and their conversations.
- Founder, co-founder, or early startup experience.
- Familiarity with voice AI or real-time orchestration systems.
- Portfolio or examples of shipped conversational experiences such as IVR, voice assistants, chatbots, or SMS flows, including rationale for key design decisions.
- Familiarity with evaluation practices for agent quality.
Responsibilities
- Lead AI agent deployments from gathering customer requirements through production go-live as the single accountable owner.
- Define deployment scope, manage tradeoffs, meet timelines, and ensure quality.
- Own the customer-facing roadmap for each deployment, including what ships, in what order, and why.
- Translate customer requirements into agent behavior using the internal platform, including prompts, tools, guardrails, and multi-agent workflows.
- Use AI tools for hands-on prompt engineering, creating conversation flows, decision logic, edge-case handling, and integration behaviors.
- Ship production-ready agents that handle healthcare workflows, scheduling logic, patient context, EMR data, and practice-specific edge cases.
- Improve agent performance through structured evaluations, live-call review, and direct customer feedback.
- Lead deployments for new workflows, integrations, and verticals where no playbook exists.
- Identify unknowns, reduce risk, and make tradeoff decisions to keep launches on track.
- Own requirements and prioritization with engineering when deployments require new platform capabilities.
- Scope integrations with Customer Engineering and coordinate cross-team work, timelines, stakeholder communication, and issue resolution.
- Identify patterns across launches and codify them into playbooks.
- Determine when workflows or integrations are ready to move from zero-to-one ownership to steady-state implementation.
- Hand off proven patterns to implementation teams and take on new challenges.
Benefits
- Meaningful equity ownership in a fast-growing healthtech startup.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
