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Ellipsis Health

Forward Deployed Product Manager, AI Assistant

United States - Remote · San Francisco - Hybrid

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hirly's read of this role

Role family
Product management
Seniority
Lead / management
Stated salary
$100,000 – $165,000 per year
Country
US
Work mode
Remote-friendly
First seen by hirly
28 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Ellipsis Health is redefining how care teams engage and support patients through voice-based artificial intelligence. Our Voice AI Care Manager, Sage, delivers empathetic, real-time conversations that help health plans and care management teams scale outreach, reduce operational bottlenecks, and improve member experience and outcomes.

Built on a foundation of more than 3 million real clinical conversations, Ellipsis Health’s proprietary vocal biomarker technology enables Sage to understand not just what is said—but how it is said—bringing emotional intelligence into care at scale.

Today, Ellipsis Health partners with leading health plans, PBMs, provider, pharma, care management organizations, and healthcare innovators to support engagement across a variety of care management and patient engagement use cases.

Backed by top investors including CVS Health/Aetna, Salesforce Ventures, and Khosla Ventures, Ellipsis Health is entering its next phase of growth—expanding market presence, deepening enterprise partnerships, and defining the category for empathetic voice AI in healthcare.

About the team

The Product team at Ellipsis Health builds and deploys voice-based AI systems that operate inside real clinical and operational workflows. We partner closely with Customer Success, Engineering, and Commercial to ensure our platform is not only innovative but operationally deployable and scalable across complex healthcare environments.

About the role We’re hiring a high-agency Forward Deployed Product Manager, AI Assistant to own the end-to-end delivery of Sage — our conversational voice AI care manager — in real customer environments.

Every new customer deployment is a product launch. New workflows, new edge cases, new integration requirements, new ways the agent needs to behave in live clinical and operational settings. This role exists to own that launch from scoping through go-live.

  • This is not a traditional roadmap-focused product role. You will work directly with health plans, providers, and operational leaders to translate their needs into shipped agent behavior — gathering requirements from customers, configuring Sage to match their workflows, and validating that what we build works in the real world, not just on paper.
  • You will operate at the intersection of Product, Engineering, and Customer Success, shaping workflows, defining integrations, guiding configuration decisions, and ensuring solutions are deployed successfully in production environments. You’ll also own the customer-facing roadmap for each deployment: defining requirements, sequencing what gets built, and aligning stakeholders on trade-offs.

This role combines product ownership with hands-on agent configuration, translating requirements into shipped agent behavior using prompts, guardrails, and evaluations. You’ll work at the forefront of applying cutting-edge language models and voice technology in live clinical environments, helping organizations scale patient engagement in ways that were not previously possible.

This is a remote US-based role with occasional travel for key customer engagements.

Who we’re looking for

We’re looking for a sharp, high-agency problem solver who can command a room with operational leaders and dive into technical details with engineers on the same day.

You are structured in your thinking, calm under pressure, and proactive in solving problems before they happen. You’re deeply accountable for delivering something that works in the real world — not just on paper — and energized by the fact that each deployment is a fresh product launch with its own constraints and edge cases.

You are highly detail-oriented and organized, capable of translating messy workflows, scripts, training guides, and FAQs into clear product decisions. You’re comfortable learning new technical systems quickly and are motivated by being close to both the product and the customer.

What you’ll own

Customer Discovery & Workflow Design: Lead structured discovery sessions to understand customer workflows, operational constraints, data needs, and integration requirements. You don’t just gather requirements — you challenge assumptions, clarify trade-offs, and guide customers toward scalable solutions.

Agent Configuration & Customization: Design and configure Sage to meet customer needs while balancing scalability and product integrity. Translate requirements into agent logic and behavior — including prompts, guardrails, and tooling — and validate that configurations perform correctly in real production environments.

Technical Deployment Leadership: Own the product layer of implementations end-to-end: integration coordination, data mapping, configuration management, UAT support, and go-live readiness. When something isn’t working, you drive it to resolution — you don’t hand it off and wait.

Requirement Translation & Engineering Partnership: Translate customer needs into clear product requirements, user stories, and acceptance criteria for Engineering. Write specs that are unambiguous: inputs, tools, data flows, failure modes, and success criteria.

Evaluation & Quality: Define what “good” looks like for each deployment — task completion, escalation rates, conversation quality, workflow adherence — and work with Engineering to build the evaluation and monitoring infrastructure that keeps deployments healthy over time.

Executive Client Communication: Serve as the product authority in customer conversations, articulating trade-offs, timelines, and solution design clearly and confidently. Customers should see you as a trusted product advisor, not just a liaison.

Voice of the Customer: Continuously synthesize customer feedback and deployment learnings to inform roadmap prioritization and platform improvements. Deployment learnings are systematically fed back into how we build.

Post-Launch Optimization: Monitor adoption, performance, and workflow effectiveness, recommending iterative improvements where needed. Time-to-deployment should decrease as reusable solution patterns emerge.

What Success Looks Like (6-9 months)

Enterprise deployments launch with well-defined requirements and minimal rework

Customer workflows are clearly documented and translated into scalable product configurations

Engineering teams receive high-quality, actionable requirements that reduce back-and-forth

UAT cycles are structured and efficient, with issues surfaced early and resolved quickly

Customers view you as a trusted product advisor, not just a liaison

Deployment learnings are systematically fed back into product improvements

Time-to-deployment decreases as reusable solution patterns emerge

Requirements

Preference for a Computer Science background , or similar/equivalent technical experience

Preference for San Francisco-based and West Coast-based candidates due to focus on West Coast-based customers

Demonstrated Product Aptitude (2–4 years): Proven ability to own complex problems, communicate clearly with stakeholders, and deliver structured solutions in ambiguous environments

Academic Rigor & Analytical Strength: Bachelor’s degree in engineering, computer science, economics, business, or a similarly rigorous field; strong evidence of intellectual discipline and structured thinking

Ownership in High-Responsibility Settings : Experience — through internships, consulting, research, startups, or technical roles — where you were accountable for delivering real outcomes, not just supporting work

Client-Facing Communication Skills: Comfort presenting ideas clearly and confidently to external stakeholders, including the ability to explain technical concepts in accessible terms

Technical Curiosity & Fluency: Strong comfort with technical systems and concepts; exposure to APIs, data structures, integrations, LLMs, or software development is preferred

Structured Problem Solving: Ability to decompose messy workflows into clear requirements, identify trad

Original posting on Ellipsis Health's site ↗

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