Top Artificial Intelligence Product Manager Jobs

Own the vision, strategy, roadmap, and execution of Snapchat safety, law enforcement, and regulatory compliance products. Define goals and metrics, identify opportunities through data and user research, collaborate with engineering and cross-functional partners, translate regulatory requirements into product solutions, and drive launches. The role requires strong analytical, communication, prioritization, relationship management, and AI-focused problem-solving skills.

Own the trade promotion management roadmap and customer experience, covering sales forecasting, trade planning, promotion optimization, reconciliation, and ROI reporting. Lead customer discovery, TPM implementations, workflow configuration, and training while translating trade expertise into product requirements. Partner with Product, Engineering, Sales, Marketing, Implementation, and Customer Success, represent the company externally, and develop scalable playbooks and competitive positioning.

Own the wealth experience within NYL360 by translating advisor and stakeholder needs into prototypes, user stories, acceptance criteria, and sprint-ready backlogs. Coordinate with Design, Engineering, Data, Testing, and field teams; manage dependencies and delivery; support QA and user acceptance testing; document defects and resolutions; and contribute to releases, pilots, communications, and feedback loops. The role also requires applying AI tools and simplifying complex wealth and legacy-system workflows.

Own the product lifecycle for Rubrik’s cloud and virtual scale-out cluster software, including vision, strategy, roadmap, development, launch, and enhancements. Partner with engineering, design, marketing, sales, resellers, customers, and field teams to drive product improvements, enablement, and adoption. Analyze market trends and KPIs, document product status, communicate technical concepts, and support strategic initiatives across cloud, on-premises, virtualization, and data management environments.

Own DocSend customer-facing product experiences from discovery through launch and iteration. Define product strategy, prioritize customer problems, guide Engineering and Design, evaluate quantitative and qualitative insights, establish success measures, and drive foundational improvements, AI-powered workflows, and multi-product experiences across Dropbox and DocSend.

Own the strategy and execution of Datadog’s Feature Flagging and Experimentation product, integrating flags with observability signals and designing AI-native workflows. Collaborate with engineering, observability, RUM, and APM teams; guide roadmap decisions; support enterprise sales; improve developer experience and documentation; and lead go-to-market execution. The role requires strong software architecture knowledge, production coding experience, B2B expertise, and familiarity with CI/CD and observability tools.

Leads digital product strategy and delivery for client engagements, from discovery through execution and go-to-market. Defines product vision, gathers requirements, creates user stories and process artifacts, advocates for users, measures product impact, and drives improvements. Facilitates workshops, supports stakeholder adoption, mentors colleagues, contributes to thought leadership and business development, and collaborates with cross-functional teams in a consulting environment.

Drive the roadmap and growth of Gitar, Sonar’s agentic code review product. Research customer and developer needs, prioritize opportunities, shape product vision and positioning, and coordinate integration with SonarQube. Partner with engineering, founders, sales, marketing, and customer success to deliver cross-product features, meet enterprise trust requirements, support go-to-market efforts, and evolve product management processes.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Own the Ascent AI enablement platform roadmap across engineering and enterprise programs. Prioritize shared infrastructure, define specifications, close capability gaps, measure maturity, and connect AI usage to business value. Partner with engineering teams without direct authority, communicate roadmap decisions to technical and nontechnical stakeholders, and stay hands-on with AI coding agents and developer tools.