Staff Product Manager, Fullscript

• 8+ years of product management experience, with a track record of leading complex, cross-functional initiatives
• Strong systems thinking and comfort working at the intersection of product, engineering, and data
• Experience collaborating deeply with engineering teams on technically complex products, including contributing to discussions around architecture, tradeoffs, and sequencing of technical work
• Ability to understand and reason about how modern AI-powered systems are built and operated, even if you’re not hands-on with implementation
• Backgrounds in software engineering, data, or other technical disciplines are welcome, but not required
• Familiarity with concepts such as APIs, distributed systems, experimentation, observability, and system reliability, and how they impact product quality and user experience
• Experience using AI both as a product capability and as a tool to improve discovery, delivery, and decision-making across the product development lifecycle
• Demonstrated curiosity and informed perspectives on emerging AI patterns (e.g., copilots, agents, automation) and how they may shape future product opportunities
• A track record of elevating teams by sharing practical insights, patterns, or approaches others can learn from

Desirable

• We’re hiring a Staff Product Manager, AI Platform & Experiences to help shape how AI meaningfully supports practitioners across the Fullscript platform
• In this role, you’ll be responsible for defining strategy and driving execution for practitioner-facing AI experiences, with a strong understanding of the systems that power them
• You’ll work across product, engineering, and data teams to ensure our AI capabilities are reliable, scalable, and thoughtfully integrated into the platform
• This is a senior individual contributor role with broad scope and high autonomy
• You’ll be expected to navigate ambiguity, make informed technical tradeoffs, and help establish what “great” looks like for AI-powered product experiences at Fullscript
• Set direction and strategy:
• Define the vision, strategy, and roadmap for practitioner-facing AI experiences, aligning near-term delivery with long-term platform evolution
• Bring focus and cohesion to AI initiatives across the platform, helping teams align around shared goals, principles, and success metrics
• Translate ambiguous problem spaces into clear product opportunities, prioritization decisions, and execution plans
• Help establish guardrails for how AI is used at Fullscript, with an emphasis on practitioner trust, usability, and control
• Make informed product decisions that account for system-level constraints such as performance, cost, reliability, and extensibility
• Help align short-term product delivery with longer-term technical investments in AI and platform capabilities
• Deliver meaningful AI-powered experiences:
• Lead the evolution of assistive and embedded AI experiences that support practitioners within their existing workflows
• Ensure AI features are grounded in accurate platform context and designed to complement, not replace, professional judgment
• Balance speed of iteration with quality, safety, and reliability, particularly in care-adjacent experiences
• Advocate for calm, intuitive interactions that reduce cognitive load rather than adding new complexity
• Partner closely with Engineering to define how AI capabilities are orchestrated, composed, and exposed to the product surface
• Partner closely with Engineering to define how AI capabilities are orchestrated, exposed, and safely operated within the product, including clear failure modes and fallback behaviors
• Ensure AI quality, evaluation, and readiness:
• Define clear product goals, user outcomes, and delivery paths for AI features with non-deterministic behavior
• Establish acceptance criteria and launch readiness standards for AI features where behavior is probabilistic rather than deterministic
• Partner with Engineering and Data teams to shape evaluation approaches, including offline testing, human-in-the-loop review, and production monitoring
• Ensure AI quality, reliability, and trust considerations evolve alongside models, prompts, and user workflows—not as post-launch fixes
• Work cross-functionally at scale:
• Act as a strong product counterpart to Engineering and Data leadership, contributing meaningfully to discussions around architecture, system evolution, and technical tradeoffs
• Collaborate on evaluation, observability, and feedback mechanisms to ensure AI systems remain understandable and improvable over time
• Help define shared patterns and primitives that enable other teams to build AI-powered features more quickly and consistently
• Help bridge product intent and technical execution by ensuring clarity around requirements, constraints, and tradeoffs throughout discovery and delivery
• Serve as a cross-functional leader across Product, Engineering, Data Science, Design, Legal, and Security, clearly communicating AI performance, risks, tradeoffs, and decision-making frameworks to both executive and non-technical stakeholders
• Mentor other PMs on AI product best practices, including evaluation and quality considerations
• Measure impact:
• Define and own success metrics tied to practitioner value and business outcomes
• Use a mix of qualitative insight and quantitative data to guide prioritization and iteration
• Ensure learnings from launches and experiments are shared and inform broader product strategy