Director of Product Management - US Remote

Required

• 8+ years of product management experience, with at least 3 years owning AI, NLP, or conversational AI products in production.
• Demonstrated ability to lead customer discovery in complex B2B environments; experience interviewing clinical or operational end users is a strong differentiator.
• Working knowledge of healthcare interoperability standards: HL7 v2, FHIR, and API integration patterns. Able to engage in technical interoperability discussions without an engineer in the room.
• Familiarity with HIPAA and the product design considerations it requires: data minimization, audit trails, access controls, and PHI handling.
• Technical fluency sufficient to evaluate AI capabilities critically, write clear functional specifications, and prototype concepts using no-code or AI-assisted tools.
• Track record of shipping AI features at scale and iterating based on production data and user feedback.
• Strong written communication; able to produce clear PRDs, executive summaries, and customer-facing feature descriptions.
• Experience working with outsourced development partners, including delivery accountability and quality review.
• Experience with healthcare contact center operations, patient access workflows, or clinical communication platforms.
• Hands-on familiarity with conversational AI platforms, voice agent frameworks, or telephony product design.
• Exposure to LLM evaluation practices, prompt engineering workflows, or AI product safety frameworks.
• Experience in a growth-stage company where product practice is still being built, not just inherited.
• Ability to prototype using tools such as Figma, Claude, Replit, or equivalent AI-assisted development environments.

Why This Role

You will own the product direction of one of PerfectServe’s highest-priority strategic platforms, with direct access to the CTO and the latitude to shape how AI is applied to real clinical and operational problems. This is not a role for someone who wants to manage a large backlog from a distance — it is for a product leader who wants to be close to the work, close to the customer, and deeply invested in getting AI right in a domain where quality genuinely matters. As the platform and team grow, this role has a clear path to VP of Product.

• Apply working knowledge of healthcare interoperability standards — HL7, FHIR, and API integration patterns — to shape AI feature design and integration requirements.
• Ensure AI features are designed with clinical workflow reality in mind: how nurses, physicians, schedulers, and operators interact with systems under time pressure.
• Identify and manage product-level compliance and safety considerations including HIPAA, minimum necessary data principles, and the appropriate use of AI in clinical decision-adjacent contexts.
• Collaborate with Clinical and Operations teams to ensure AI behavior aligns with care protocols, escalation paths, and patient safety standards.
• Own the relationship between product requirements and engineering delivery — writing precise, well-scoped specifications that reduce ambiguity without over-constraining implementation.
• Serve as the product accountability owner for the outsourced development partner, reviewing deliverables against acceptance criteria and escalating quality issues promptly.
• Collaborate with Marketing and Customer Success on go-to-market sequencing for new AI features, including packaging, positioning, and customer communication.
• Represent the product perspective in executive conversations; communicate roadmap priorities, tradeoffs, and AI adoption risks clearly to non-technical stakeholders.
• Metrics, Learning & Continuous Improvement
• Define the measurement framework for AI product performance: establish baselines, set targets, and drive quarterly reviews of key metrics with engineering and executive leadership.
• Build a culture of learning from production data: use real-world call outcomes, error logs, and user feedback to continuously improve AI model performance and product design.
• Identify and act on leading indicators of customer churn or dissatisfaction related to AI feature quality.
• Initially operate as an individual contributor; build out a product and design team as the platform and organization scale.
• Establish PM practices and norms that support AI-native development: lightweight documentation, fast feedback loops, and outcome-oriented delivery measurement.
• Mentor and develop junior product team members as the function grows.