Principal Product Manager, AI/ML

Set the multi-year vision and strategy for Tatari's AI/ML recommendation and prediction products as a hands-on Principal PM. Requires 10+ years PM experience including 3+ years leading ML/AI products, with proven experience building recommendation systems or GNNs at scale.

About the job

Responsibilities

Own the vision and multi-year roadmap for AI/ML recommendation and prediction products end-to-end — from ideation and business case through market research and competitive differentiation — to drive growth and sustained competitive advantage.
Secure executive alignment on technology investments tied to business goals; guide engineering teams in sequencing short-term deliverables that ladder to long-term strategy.
Serve as the org's go-to expert on customers and market: synthesize usage data, qualitative research, and competitive/industry intelligence to validate and prioritize the roadmap.
Evangelize AI/ML product innovation across the org, raising the bar on what "good" looks like and driving the organizational changes needed to support it.
Mentor and set the standard for other PMs working on adjacent AI/ML or data-driven initiatives — acting as a force-multiplier beyond your own roadmap.
Partner closely with design, data science, and engineering through the full delivery lifecycle (including Agile ceremonies) to define requirements and ship on time at the right quality bar.

Qualifications

10+ years in Product Management, including 3+ years leading ML/AI products end-to-end, with demonstrated Staff/Principal-level scope (influence across multiple teams or roadmaps, not just one product line).
Proven track record building and scaling recommendation systems and/or graph neural network (GNN) products in production, at meaningful user/data scale.
Experience shaping product strategy and driving buy-in without formal authority — across engineering, leadership, and cross-functional stakeholders — with results tied to specific business outcomes.
Skilled at partnering with UX/design and data science to ship AI/ML features, balancing model capability against usability constraints.
Strong grasp of Agile/iterative development, adapted for ML timelines (training cycles, data dependencies, experimentation loops).
Exceptional written/verbal communication; able to translate technical ML tradeoffs for non-technical stakeholders and think analytically across systems.
Big plus (not required): Direct experience in ad tech, CTV/streaming, linear TV, or programmatic media.