---
title: 'New Product Development Lead at Qualified Health PBC'
canonical: 'https://feeny.ai/job/new-product-development-lead-qualified-health-pbc-united-states-503qavp5m45n'
type: 'job'
last_seen: '2026-09-12'
---

# New Product Development Lead at Qualified Health PBC

- **Company:** Qualified Health PBC
- **Location:** United States
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-06-02
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/qualified-health-pbc/23a33982-8007-4a4d-8501-d0ead98bd846

## Job description

Transform healthcare with us. At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change. This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board. Join us in shaping the future of healthcare.

Job Summary The New Product Development Lead is one of the most important individual-contributor hires we'll make this year. This is a 0-to-1 role. Given a new product idea, whether it's a clinical use case, a hospital operations problem, a revenue cycle workflow, or any other place AI can drive real value inside a health system, you independently take it from an open question to a working, deployed product, and you stay with it as it matures with real clients.

That means doing the data discovery yourself: figuring out what signal actually exists in a client's data, whether it's usable, and what it would take to turn it into something trustworthy enough to run in production. It means designing and building whatever pipeline or agentic workflow the product needs, often something bespoke, built for the specific problem rather than forced into an existing pattern. And it means judgment: knowing when existing platform components are the right foundation to build on, versus when the product calls for something new, and when something new proves out, bringing it back into the platform so it's available for the next product.

Ownership doesn't stop at a working prototype. You'll carry products through production deployment and into post-launch iteration directly with health system clients, refining based on what real data and real feedback tell you. Our platform spans a growing set of AI products across clinical, operational, and revenue cycle domains, with several active pipelines already in production or in deployment with clients. And the next one is likely something none of us have scoped yet.

## Key Responsibilities

- Take new product ideas, spanning clinical, hospital operations, revenue cycle, and other health system domains, from an open, often ambiguous problem statement through to a deployed, working product, owning the full 0-to-1 lifecycle
- Independently perform data discovery against client data: assess what signal exists, its quality and completeness, and whether it can support a trustworthy production product
- Design and build the data pipeline and agentic AI workflow each product needs, choosing a bespoke approach when the existing platform doesn't fit rather than forcing a mismatched pattern
- Exercise judgment on when to build on existing platform infrastructure versus when to build something new
- Once an initial bespoke build proves out, bring it into the core data platform: harden it, integrate it with existing pipelines and standards, and make it a supported, reusable part of the platform rather than a one-off
- Collaborate directly with clinical, operational, product, and client stakeholders during discovery and validation to ensure the product reflects real domain logic and real workflow needs
- Carry products through production deployment and own post-launch iteration directly with health system clients as real-world data and feedback come in
- Own data spec documentation for each product you build
- Work within platform principles (empirical verification before building, annotations over hardcoded logic, loud failures over silent nulls) without those principles constraining the pace or shape of 0-to-1 discovery

Required Qualifications

- Education: Bachelor's degree in Computer Science, Engineering or a related field. Master's degree is preferred.
- Deep Databricks/Spark expertise at the architecture level — performance tuning, cluster management, Delta Lake design patterns
- Experience building reusable data frameworks, tooling, or platforms
- Demonstrated ability to hire, develop, and retain strong engineers

Ideal Experience

- Hands-on experience building ML/LLM pipelines: agent/tool-based architectures, model serving, prompt engineering in production, evaluation frameworks
- Background as a founding or early engineer on a new product or platform, where you defined the approach rather than inherited one
- Direct experience working with clients or end users to validate and refine a product post-launch

Desirable Skills

- 0-to-1 Judgment: Comfortable starting from an open problem, clinical or otherwise, with no defined data path, and independently figuring out what's real, what's usable, and what to build
- Build vs. Reuse Instincts: Knows when to build something bespoke for a specific product versus when to lean on existing platform infrastructure, and can generalize a bespoke solution into something reusable once it's proven
- Product Engineering Instincts: You think about your output as a product: validated with real data and real domain stakeholders, deployed, and owned through post-launch iteration, not handed off at "done"
- Client-Facing Comfort: You're effective working directly with health system clients and their stakeholders during discovery and after launch, not just with internal teams
- Builder Mentality: You're energized by creating something from nothing: taking a product from a rough idea to something real in production, independently and end-to-end

Travel Requirements This role is primarily remote. Occasional travel may be required for team on-sites, leadership meetings, or partner-facing architecture discussions. Candidates should be prepared for 5-10% travel.

Why Join Qualified Health? This is an opportunity to join a fast-growing company and a world-class team that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers. Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.

Our Commitment to Diversity Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.

Pay & Benefits The pay range for this role is between $195,000 and $240,000, and will depend on your skills, qualifications, and experience. This role is also eligible for equity and benefits.

## About Qualified Health PBC

## Company Overview
- **One-liner**: Qualified Health is the healthcare-native enterprise AI platform that enables health systems to safely deploy, govern, and scale AI across clinical, operational, and financial workflows.
- **Entity Type**: Private (Series B)
- **Headquarters**: Palo Alto, California, United States
- **Founded**: 2024
- **Founders**: Justin Norden (CEO), Kedar Mate (CMO), Beau Norgeot (Chief AI Officer)

## Core Business
- **Primary industry**: Healthcare AI infrastructure and governance
- **Target customers**: B2B – large health systems, academic medical centers, and clinically integrated networks
- **Mission**: To help health systems deploy safe, compliant, and impactful AI at enterprise scale by providing a unified platform with built-in governance, monitoring, and outcomes tracking.

## Products & Services
- **Qualified Health Platform**: A single, healthcare-native enterprise AI platform that includes a governed operating layer, one data integration, agent builder tools, workforce education, and a curated library of validated AI solutions. Covers HIPAA-compliant guardrails, real-time monitoring, audit trails, and role-based access controls.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metrics**: Annual revenue ~$3.1M (LinkedIn); total funding $155M (Series B of $125M led by New Enterprise Associates, Seed of $30M led by Town Hall Ventures and Frist Cressey Ventures)
- **Notable Investors/Partners**: New Enterprise Associates (lead Series B), Town Hall Ventures, Frist Cressey Ventures
- **Growth Signals**: 10× revenue growth in the past year; 241.9% YoY headcount growth (75 employees); reached over 500,000 users across top US health systems; identified $37M in run-rate value in 10 days for one partner; $15M in value realized within six months for another; platform go-live in under one month

## Competitive Advantages
- **Healthcare-native governance**: Governance is built into the platform, not bolted on, with risk-based guardrails, human-in-the-loop controls, and continuous post-deployment monitoring.
- **Single integration**: Connects once to core clinical, operational, and financial systems to power every AI workflow, eliminating duplicate data extraction.
- **Deep domain expertise**: Founders and team bring experience from Waymo (self-driving safety), Stanford Medicine, IHI, and major health systems – they understand regulated environments firsthand.
- **Proven traction**: Over 500,000 users on the platform with measurable clinical, operational, and financial outcomes.

## Strategic Focus
- Scale safely: Continue deploying the platform across more health systems while maintaining rigorous compliance and safety standards.
- Bold innovation: Expand agent and workflow builder tools to empower health system teams to create their own AI solutions on a governed foundation.
- Last-mile delivery: Operate as an embedded partner to drive adoption, measure ROI, and tune solutions for sustained impact.

## Why Work Here
- **Culture**: High-talent-density team with backgrounds from Waymo, Stanford, Elevance Health, and top consultancies. Emphasis on safety as an enabler of speed in healthcare.
- **Growth trajectory**: Fast-growing (10× revenue, 241% headcount growth) with a clear path to becoming a category-defining company in healthcare AI.
- **Mission-driven**: Direct impact on reducing clinician burnout, improving patient outcomes, and lowering healthcare costs.
- **Work environment**: Based in Palo Alto, CA with international presence (Italy, Canada, South Korea). Remote/hybrid policy not explicitly stated but likely flexible; check current job postings for specifics.
- **Perks**: Competitive salaries (e.g., Software Engineer ~$106K); the opportunity to shape the operating system for AI in healthcare alongside industry leaders.

## Sources
1. [qualifiedhealthai.com](https://www.qualifiedhealthai.com/)
2. [qualifiedhealthai.com/careers](https://www.qualifiedhealthai.com/careers)
3. [qualifiedhealthai.com/about-us](https://www.qualifiedhealthai.com/about-us)
4. [linkedin.com](https://www.linkedin.com/company/qualifiedhealth)
5. [bloomberg.com](https://www.bloomberg.com/profile/company/2540760D:US)

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