AI Agent Product Manager

Summary

OhMD is an AI patient communication platform used by thousands of healthcare organizations. The AI Agent Product Manager will define and manage the behavior of the AI agent for various healthcare practices, ensuring effective communication and integration with existing systems.

Responsibilities

• You’ll sit with the people who actually answer the phones, learn their workflows, and turn what you hear into working agent behavior — conversation flows, decision logic, escalation rules, edge case handling. Not a spec you hand to someone else. You’ll build it, in our platform, with prompts, tools, and guardrails
• Our practices go live in about three weeks: platform setup, EHR integration, AI configuration, staff training. You’re the single owner of what the agent does across that window — scoping what’s in and out, making the calls when something doesn’t fit the standard path, and making sure the practice’s first week live is a good one
• You’ll listen to real calls. A lot of them. You’ll build evals that catch failures before a practice does, read the transcripts where the agent got it wrong, and close the loop. When you find a failure mode our platform can’t handle yet, you’ll write the requirement and work it through with engineering
• You’ll scope those integration requirements alongside our engineering team and design agent behavior that holds up when the data doesn’t cooperate
• You’ll notice when something’s ready to graduate from custom work to repeatable setup, write it down, hand it to the implementation team, and move on to the next unsolved thing
• Occasional appearances at industry conferences, webinars, or partner events (Twilio, EHR partners) to talk about how the AI agent actually works in practice
• Sitting in on interviews for future AI PM or implementation hires as the team grows, since you'll know better than anyone what 'good' looks like for this seat
• Other duties as assigned

Skills

• 3+ years in product management or an adjacent seat — technical program management at a product company, a founding-team role where you wore the PM hat, or an engineering background where you've been the one talking to customers and deciding what gets built
• Technical enough to be dangerous. You're comfortable with APIs and integrations and you can reason about how systems connect. You don't need to ship production code, but you shouldn't need a translator
• Hands-on instincts. When you want to know if something works, you go build a version of it
• Comfort with ambiguity. Much of this work has no playbook yet. You'd rather make a decision and correct course than wait for someone to hand you clarity
• Influence without authority. You'll coordinate across engineering, implementation, and customer success without managing any of them
• Care about the end user. The patient on the other end of that call is often stressed, sick, or worried about someone they love. That should matter to you
• Hands-on work with LLMs, AI agents, or prompt engineering. Extra credit if you've broken a few on purpose to see what happens
• Background in healthcare, or another industry where the underlying systems are old and unforgiving
• Experience with voice AI or real-time conversational systems
• Examples of conversational experiences you've shipped — voice, chat, SMS, IVR — and the reasoning behind the choices you made
• Familiarity with evaluating agent quality in a structured way
• Early-stage startup experience

Qualifications

Must Haves

• 3+ years in product management or an adjacent seat — technical program management at a product company, a founding-team role where you wore the PM hat, or an engineering background where you've been the one talking to customers and deciding what gets built
• Technical enough to be dangerous. You're comfortable with APIs and integrations and you can reason about how systems connect. You don't need to ship production code, but you shouldn't need a translator
• Hands-on instincts. When you want to know if something works, you go build a version of it
• Comfort with ambiguity. Much of this work has no playbook yet. You'd rather make a decision and correct course than wait for someone to hand you clarity
• Influence without authority. You'll coordinate across engineering, implementation, and customer success without managing any of them
• Care about the end user. The patient on the other end of that call is often stressed, sick, or worried about someone they love. That should matter to you
• Hands-on work with LLMs, AI agents, or prompt engineering. Extra credit if you've broken a few on purpose to see what happens

Nice to Haves

• Background in healthcare, or another industry where the underlying systems are old and unforgiving
• Experience with voice AI or real-time conversational systems
• Examples of conversational experiences you've shipped — voice, chat, SMS, IVR — and the reasoning behind the choices you made
• Familiarity with evaluating agent quality in a structured way
• Early-stage startup experience

Benefits

• Location: Burlington, VT (hybrid) or remote