Sr. Product Manager II - AI Platform (Remote Eligible)

Smartsheet is a company that empowers teams to manage work seamlessly and scale solutions smarter. They are seeking a Senior Product Manager II to own the product roadmap for their AI platform, bridging the engineering and product feature teams while ensuring quality and governance in AI capabilities.

Responsibilities:

• Own the AI platform roadmap: Define and drive strategy and execution for model serving, the LLM gateway, agent orchestration, and the infrastructure that keeps models and agents running reliably in production -- partnering with data engineering to define what the AI platform needs from the data layer without owning it directly
• Bridge platform and product teams: Own the seams between infrastructure and the teams shipping AI-powered product features, ensuring agent capabilities are governed, discoverable, and consistently delivered
• Own AI monetization as a product surface: Map agent activity to consumption-based AI credits, ensure logging infrastructure supports that mapping, and surface usage and cost data to enterprise admins
• Make evaluation and observability first-class: Ship pre-deployment eval gates plus production tracing, monitoring, alerting, and regression detection so you catch quality issues before customers do
• Build the AI governance and responsible AI layer: Own output-quality guardrails, agent access controls, data classification, audit logging, and enterprise compliance (SOC 2, EU AI Act, ISO 42001) as a horizontal control plane across every AI feature -- including the responsible AI framework governing how we evaluate bias, fairness, and safe agent behavior
• Define the AI admin experience: Own the controls governing which AI features are on or off and for whom, and which usage, cost, and audit data gets surfaced to enterprise admins

Requirements:

• 8+ years of product management experience with technically complex platforms, ideally in enterprise SaaS
• Deep fluency in AI/ML concepts -- agent and sub-agent architectures, orchestration, tool use, prompt engineering, and quality measurement
• Experience building or managing evaluation and quality infrastructure for AI or ML systems, including reading traces and eval runs to form your own opinion on technical tradeoffs
• Track record of shipping enterprise software from inception to launch with measurable business impact
• Comfort operating in high-ambiguity environments with significant autonomy and the ability to influence without authority across engineering, security, legal, and executive stakeholders
• Experience building or managing evaluation and quality infrastructure for AI or ML systems, including reading traces and eval runs to form your own opinion on technical tradeoffs (strongly preferred)
• Familiarity with data and ML platforms, particularly Databricks (Delta Lake, Unity Catalog, MLflow) or equivalent lakehouse environments (strongly preferred)
• Demonstrated experience with responsible AI frameworks -- governance policy, agent access controls, audit logging, or enterprise AI compliance (preferred)