PerfectServe - Director of Product Management - US Remote

• AI Product Vision & Roadmap Ownership • 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. • Customer & Clinical Discovery • 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. • AI-Native Product Development Practices • 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. • Healthcare Interoperability & Workflow Expertise • 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. • Cross-Functional Alignment & Delivery • 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. • Team Leadership • Team Leadership • 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.