Director of Product Management - US Remote

PerfectServe is a leading provider of clinical communication and physician scheduling solutions in the health IT space. The company is seeking a Director of Product Management – AI to own the product vision, strategy, and lifecycle of their AI-native answering service platform, focusing on customer needs and clinical workflows.

Responsibilities:

• Define and own the product strategy for PerfectServe’s AI answering service, including near-term delivery commitments and a longer-horizon vision for how AI evolves across the portfolio
• Translate business objectives and clinical workflows into a prioritized, clearly reasoned product roadmap — and maintain it as a living document that reflects new information, not a static plan
• Partner with the CTO and Director of Software Engineering to align roadmap sequencing with technical capacity, architecture constraints, and infrastructure investments
• Make and communicate clear product tradeoff decisions: what is in scope, what is deferred, and why
• Lead ongoing customer discovery efforts: conduct interviews, site visits (virtual or in-person), and workflow observation sessions with clinical and administrative end users
• Develop and maintain a deep understanding of how healthcare organizations use answering services, operator consoles, and AI-augmented communication — including the pain points, workarounds, and compliance constraints that matter most
• Synthesize input from cross-functional teams, market and customers into product insights; distinguish signal from noise when stakeholder demands conflict
• Define user personas and jobs-to-be-done for the AI platform’s primary audiences: clinical staff, contact center agents, patients, and healthcare administrators
• Use modern AI tools to accelerate your own product work: generate prototypes and wireframes, run rapid concept tests, and explore technical feasibility before committing engineering resources
• Design and run structured product experiments — A/B tests, pilot programs, shadow deployments — to validate hypotheses before broad rollout
• Define clear acceptance criteria and success metrics for every feature, including AI-specific measures such as containment rate, deflection accuracy, latency, and user-perceived quality
• Actively evaluate emerging AI capabilities (new LLMs, voice models, orchestration frameworks) and recommend adoption decisions based on product value and technical fit, not novelty
• 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
• 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

Requirements:

• 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