Sr Manager, AI Product Management

Your role at Dynatrace

The Sr Manager - AI Product Management owns the identification, prioritization, and successful adoption of AI-powered capabilities embedded into business operations. This role translates operational pain points into deployable AI solutions and ensures delivered automation produces measurable business outcomes. Working closely with AI engineers, data teams, and business stakeholders, the AI Product Manager defines use cases, manages delivery, and drives adoption of AI copilots and automated workflows powered by enterprise data platforms.

The role focuses on applied AI – improving how work gets done – rather than research or model development. This role will report up into the VP of AI, Collaboration and Data's team.

• Partner with Operations, Sales, Finance, HR, Legal, Marketing, and IT leaders to identify high-impact opportunities where AI can reduce manual effort, improve decision quality, or accelerate workflows.

• Evaluate business processes for automation suitability – assessing volume, repeatability, decision complexity, and ROI potential – and maintain a prioritized backlog of AI opportunities across the organization.

• Lead discovery and scoping sessions with business stakeholders to translate operational pain points into clear product requirements: define use cases, success metrics, and acceptance criteria for AI copilots, agents, and automated workflows.

• Define user stories and requirements for AI-powered solutions – ensuring AI features integrate seamlessly into existing workflows rather than creating new tools employees must learn.

• Partner with AI engineers and data teams to design grounded, reliable AI experiences: specify when AI should assist vs. when humans must decide, define human-in-the-loop escalation points, and shape solution approaches that balance automation with appropriate oversight.

• Lead build/buy/partner evaluation for AI tooling and capabilities: assess SaaS vendor solutions, platform integrations, and custom-build trade-offs, and bring well-reasoned recommendations to engineering and leadership.

• Own rollout, adoption, and change management: design communication plans, user training, and onboarding experiences that build trust and encourage usage; measure adoption curves and behavioral change to ensure delivered solutions are actually used.

• Define acceptable use policies and decision thresholds for AI systems: determine when AI can auto-approve, auto-route, or auto-generate content vs. when human review is required – ensuring governance is practical and risk-appropriate for each use case.

• Work with Legal, Risk, Security, and Compliance teams to ensure AI solutions meet data usage, privacy, and regulatory requirements – translating governance constraints into product guardrails that protect the organization without blocking adoption.

• Own value realization: define success metrics (productivity gains, cycle time reduction, cost savings, manual work eliminated), build ROI dashboards in partnership with Data Analytics, monitor adoption and operational impact, and present value updates to leadership on a regular cadence.

• Track performance of deployed AI solutions: monitor accuracy, usefulness, user satisfaction, and business outcomes; identify improvement opportunities, gather feedback, and iterate on solutions to drive continuous improvement.

• Build a repeatable AI operating model: document lessons learned, standardize delivery practices, and identify expansion opportunities where proven AI patterns can be applied to new departments or workflows.

This is a remote eligible position. Candidates who live within a 45 mile radius of Boston, MA;
Detroit, MI;
Denver, CO; and Mountain View, CA will be required to work hybrid (2 days per week) out of our Dyntrace office. Candidates are required to work EST hours for this position.

• 5+ years of product management, operations transformation, or business systems experience – with a proven track record delivering workflow automation or enterprise software solutions that improved how teams work.

• Deep understanding some or all corporate…