Director of Product Management, AI/ML

Workiva is a company focused on providing solutions in AI and Machine Learning. The AI/ML Director of Product Management will lead the product strategy and execution for AI capabilities, managing a team and collaborating with various departments to deliver valuable products to enterprise customers.

Responsibilities:

• Define the multi-year AI/ML product vision and translate ambiguous opportunities into focused bets with clear success metrics (adoption, quality, cost)
• Incubate 0→1 and scale 1→N AI features: copilots/agents, document & spreadsheet intelligence, workflow automation, and data intelligence across Workiva surfaces
• Establish responsible AI standards (safety, privacy, evaluations, bias testing, and model/feature gating) in partnership with Security, Legal, and Compliance
• Build an experimentation and evaluation engine (A/B testing, offline evaluations, red-teaming, human-in-the-loop)
• Own portfolio outcomes and product economics, including pricing/packaging, usage metering, and inference COGS optimization
• Hire, coach, and develop a high-performing Product Management team; raise the bar for PRDs, roadmaps, and product reviews
• Drive cross-functional execution with Engineering/ML and Design; align with Sales, Customer Success, and Alliances on enablement and customer evidence
• Represent Workiva externally with customers and partners; gather market insight and translate it into roadmap impact

Requirements:

• 10+ years of relevant experience, including 5+ years building AI/ML-powered products and 4+ years leading PM managers
• Demonstrated depth in modern AI (LLMs, retrieval, agents, evaluation, and safety) and enterprise SaaS at scale
• Track record of shipping both 0→1 products and scalable platform features
• Strong data fluency (analytics, SQL or equivalent, experimentation)
• Excellent stakeholder leadership and executive communication skills
• Proven experience in regulated or compliance-sensitive domains; hands-on operationalization of Responsible AI
• Expertise in pricing/packaging for AI add-ons or usage-based models
• Public customer evidence (case studies, talks) and strong writing/storytelling
• Strong executive presence with public-facing experience, including customer case studies, thought leadership, conference talks, and high-impact storytelling
• Familiarity with cost/performance trade-offs in model selection, retrieval, latency, and observability
• Deep understanding of model cost-performance trade-offs, including retrieval strategies, latency optimization, and observability in production AI systems