About the RoleEvery new customer deployment is a product launch-new workflows, new edge cases, new integration requirements, new ways the agent needs to behave in the real world. This role exists to own that launch from scoping through go-live. You'll also own the customer-facing roadmap for each deployment-defining requirements, sequencing what gets built, and aligning stakeholders on tradeoffs.
This role combines product ownership with hands-on agent building - translating requirements into shipped agent behavior. You'll gather requirements directly from customers, translate them into agent logic and workflows, and implement that behavior hands-on using prompts, guardrails, tools, and evals.
You'll design Mia's behavior, ship production-ready multi-agent workflows, and turn real-world healthcare complexity into systems that actually hold up on live calls. This is a rare seat: you'll get direct exposure to frontier LLM failure modes in production, and you'll continuously iterate on agent performance using structured evaluation, testing, and real customer feedback.
What You'll DoOwn customer deployments end-to-end- Lead delivery of net-new AI agent deployments as the single accountable owner-from customer requirements through production go-live
- Treat every deployment as a product launch: define scope, manage tradeoffs, hit timelines, ensure quality
- Own the customer-facing roadmap for each deployment-what are we shipping, in what order, and why
Build agents, not just specs- Gather requirements directly from customers and translate them into agent behavior yourself using our internal platform-prompts, tools, guardrails, multi-agent workflows
- Do hands-on prompt engineering using AI tools to build the components that make agents work: conversation flows, decision logic, edge case handling, integration behaviors
- Ship production-ready agents that handle real healthcare complexity: scheduling logic, patient context, EMR data, practice-specific edge cases
- Continuously improve agent performance using structured evals, live call review, and direct customer feedback
Drive zero-to-one execution- Lead deployments for new workflows, integrations, and verticals where no playbook exists
- Identify unknowns early, derisk them, and make tradeoff decisions that keep launches on track
- When deployments require net-new platform capabilities, own requirements and prioritization with the engineering team
Work alongside Conversational Design and Customer Engineering- Conversational designers design and optimize agent behavior-they review real conversations, identify patterns, design conversation flows, and ship agent behavior
- Customer engineers build integrations into our customers' systems of record-EHRs, PMS, and PIMS
- You own everything else: integration scoping with Customer Engineering, cross-team coordination, timeline management, stakeholder communication, and unblocking whatever's in the way
Build toward repeatability- Identify patterns across launches and codify them into playbooks
- Know when a workflow or integration is ready to transition from zero-to-one ownership to steady-state implementation
- Hand off proven patterns to implementation teams and move on to the next net-new challenge
What We're Looking ForMust have- 3+ years in Product Management or a closely related role (e.g., technical program management at a product-led company, founder/early employee wearing the PM hat) or a technical background (software engineer / forward-deployed engineer) who has operated in a PM-like capacity
- Strong technical product background-comfortable with APIs, integrations, and understanding how systems connect
- Experience shipping in ambiguous, fast-moving environments where the playbook doesn't exist yet
- Proven ability to work across functions through influence, not authority
- Bias toward ownership and action-you'd rather make a call and course-correct than wait for clarity
Nice to have- Experience with AI-native products, agents, LLMs, or automation platforms including hands-on prompt/agent buildingBackground in healthcare, revenue cycle, or other legacy-system-heavy industries
- You've spent time playing with bots - building them, breaking them, and tweaking conversations to make them feel more natural.
- Founder, co-founder, or early startup experience
- Familiarity with voice AI or real-time orchestration systems
- Portfolio or examples of shipped conversational experiences (IVR, voice assistants, chatbots, SMS flows) and the rationale behind key design decisions
- Familiarity with evaluation practices for agent quality
CompensationBase salary: $160K-$200K
Equity: Meaningful ownership in a fast-growing healthtech startup
