Preparation for Alpaca Health should focus on demonstrating a "builder" mindset. You are not being interviewed to see if you can manage a process; you are being interviewed to see if you can solve hard problems with code, data, and intuition.

Technical Competence – We expect you to understand the "how" behind the "what." Be prepared to discuss APIs, data pipelines, and how AI systems interact with existing healthcare infrastructure.

Customer Obsession – You must demonstrate a deep, nuanced understanding of the clinician’s workflow and the family’s journey. Theoretical product knowledge is secondary to your ability to speak to the specific pain points of our users.

Bias for Action – We value speed and the ability to work in high-ambiguity environments. Use your interview time to show how you default to creating working demos rather than waiting for perfect specs.

The interview process at Alpaca Health is designed to test your ability to act as a founding team member. It is intense, fast-paced, and heavily focused on your ability to deliver high-quality output in a compressed timeframe. You should expect a mix of deep-dive conversations on your past projects and practical, hands-on sessions where you demonstrate your technical and product judgment.

This timeline outlines the typical stages from initial contact through the final decision. Use this to pace your preparation, ensuring you have enough time to review your portfolio of "builder" projects before the later, more technical rounds.

AI & Rapid Prototyping

We evaluate your fluency with modern AI-native tooling. A strong candidate doesn't just talk about AI—they show how they use it to build.

• Prototyping velocity – Can you turn an idea into a working demo quickly?
• Tooling mastery – Familiarity with the current ecosystem (Claude Code, Cursor, etc.).
• System understanding – Knowing when to use AI and when to use traditional deterministic logic.

Example scenarios:

• "Build a prototype for a scheduling flow that reduces clicks by 50%."
• "Explain how you would integrate an LLM into our current EHR data pipeline."

Product Growth & Funnel Optimization

You will be evaluated on your ability to move business-critical metrics like conversion rates and time-to-care.

• Funnel instrumentation – How do you measure success at every stage of the patient journey?
• Experimentation rigor – How do you design tests that yield statistically significant insights?
• Outcome ownership – Proving that you are driven by KPIs, not just feature delivery.

Example scenarios:

• "How would you optimize the referral-to-intake conversion funnel?"
• "Walk me through an A/B test you ran that failed, and what you learned."

As a Founding Product Manager, you will be responsible for the full lifecycle of product initiatives. You will work closely with engineering to build AI-native features that power our provider growth platform. This involves both high-level strategy—defining the long-term vision of our EHR—and granular execution, such as instrumenting data pipelines to track patient conversion.

You will spend significant time in the field, speaking directly to clinicians and families to pressure-test your assumptions. You will be expected to bridge the gap between technical constraints and business goals, ensuring that every product decision contributes to our 30% MoM growth target.

We are looking for candidates who can hit the ground running. You must have a track record of owning products from 0 to 1 and the technical depth to understand complex data architecture.

• Must-have skills: 3–6 years of PM experience, deep experience with AI tools, and a proven ability to bridge engineering and business teams.
• Nice-to-have skills: Prior experience in B2C healthcare or SMB B2B SaaS, and a background in developer-adjacent environments.
• Cultural fit: You must be NYC-based, as we operate 5 days a week in person to maintain the velocity required for a founding team.

Q: What is the best way to stand out during the interview? A: Bring a portfolio of things you have built. Show us the prototypes you’ve developed using AI tools, and be ready to explain the trade-offs you made in your design.

Q: How much time should I spend preparing? A: Given the technical nature of the role, you should spend 10–15 hours reviewing your past technical projects and familiarizing yourself with current AI-native development workflows.

Q: What is the culture like at Alpaca Health? A: We are high-intensity and mission-driven. We value builders who can navigate ambiguity and who are comfortable with the fast, iterative nature of a company growing 30% MoM.

• Show, don't tell: Whenever possible, use your laptop to demonstrate a working prototype.
• Be opinionated: We value product thinkers with strong, well-reasoned perspectives on the future of healthcare technology.
• Focus on the "Why": Don't just explain how a feature works; explain why it is the correct solution for the specific clinical or business problem at hand.
• Own your time: If an interviewer is late or a meeting is disorganized, be professional but clear about your time expectations. It is a sign of a strong, self-respecting PM.

The Founding Product Manager role at Alpaca Health is a rare opportunity to shape the future of clinical care through AI-native software. It is a demanding position that requires a unique blend of technical skill, product intuition, and a relentless drive for execution. By focusing your preparation on your "builder" history and your ability to solve complex system problems, you will be well-positioned to succeed.

We encourage you to leverage these insights as you prepare for your interviews. For further resources on navigating high-growth startup interviews, consult additional materials on Dataford. You have the potential to make a material impact on the families and clinicians we serve; prepare with confidence and focus on your ability to deliver value from day one.

The compensation data above reflects the range for this role. Use this to ensure your expectations align with the market and the stage of Alpaca Health, keeping in mind that total compensation includes significant equity upside.