Internal Product Manager 5

Adobe•San Jose, CA

17h

About The Position

Adobe is seeking an innovative, AI-first Product Manager to partner with Marketing, Sales, and operations teams. This role involves identifying business challenges, building solutions, and guiding project teams to successful completion, achieving business goals and KPIs. The ideal candidate will have deep, hands-on experience with Agentic/generative AI, machine learning, and AI-powered Sales & Marketing tools. Responsibilities include co-leading the planning, testing, and rollout of marketing and sales accelerators using agentic AI workflows, third-party sales tools, and Microsoft Dynamics CRM solutions. The role also requires close collaboration with data science, engineering, and UX teams to develop and deploy AI-powered technology solutions for hyper-personalized, next-best-action customer experiences at scale. This specific role will focus on the MSFT Dynamics ecosystem, with a primary emphasis on Marketing Operations and intelligent Sales experiences. Hands-on technical knowledge of Dynamics and Sales AI is preferred.

Requirements

6+ years of product management experience required, with a demonstrated focus on Sales AI/ML-powered products/solutions, intelligent automation, or data-driven platforms within large-scale global technology environments.
Deep technical understanding of AI/ML capabilities within Marketing and Sales platforms, including generative AI, predictive analytics, natural language processing (NLP), and real-time decisioning on sales tools.
Hands-on experience implementing MSFT Dynamics Sales Hub with AI-powered features including Copilot for Sales, predictive lead and opportunity scoring, and relationship intelligence at enterprise scale.
Self-starter with intellectual curiosity about emerging AI technologies, who thrives in ambiguous, fast-moving environments and proactively identifies new AI use cases that drive competitive advantage.
Outstanding skills in verbal and written communication. Capable of making complex AI concepts—model outputs, confidence scores, bias tradeoffs—clear for technical and non-technical audiences, including executive leadership.
Experience promoting AI product capabilities and supporting AI-based programs to customers, business partners, and internal users to encourage adoption and advance organizational AI literacy.
Strong people skills, with a distinctive ability to align data scientists, ML engineers, business analysts, and go-to-market teams around a shared AI product vision — influencing without authority.
Excellent conflict-resolution and facilitation skills, with the ability to navigate tensions between model accuracy, business timelines, data privacy requirements, and responsible AI standards.
Bachelor’s degree in Computer Science, Data Science, or a related technical field strongly preferred; equivalent work experience in AI/ML product management will be considered.

Nice To Haves

Individuals with hands on technical knowledge around Dynamics and Sales AI will be preferred.

Responsibilities

Partner with various end users and business teams to map current-state processes.
Architect AI-powered future-state solutions on MSFT Dynamics or other third-party sales tools.
Focus on automation and predictive intelligence to define the next best actions.
Lead and facilitate AI adoption workshops and process re-engineering sessions with internal customers, translating AI capabilities into tangible business value and measurable outcomes.
Define and champion an AI-first product vision.
Collaborate with teams in analytics, architecture, development, and engineering.
Deliver a roadmap anchored in machine learning models, generative AI features, and intelligent automation.
Communicate and align internal customers and technical teams on the strategic direction for AI products.
Outline the roadmap for delivering intelligent promotional and sales strategic experiences.
Strategically align with other Product Managers on the delivery of interdependent solutions, shared data pipelines, and cross-platform model integrations.
Lead the planning, documentation, and delivery of AI feature initiatives, including engineering standards that ensure timely responses, model evaluation frameworks, and ethical AI governance for Marketing and Sales use cases.
Lead User Acceptance Testing (UAT) for AI features with business testers, and partner with Quality Engineers to define acceptance criteria that validate model outputs, AI accuracy thresholds, and bias/fairness requirements.