Director, AI & Data Product Management
New
P
phDataData & AI Consulting
US - RemoteFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 10+ years of product management experience, with at least 3 years in a consulting, professional services, or advisory environment.
- Required Skills
- Business IntelligenceProduct ManagementSnowflake
Requirements
- 10+ years of product management experience, with at least 3 years in a consulting, professional services, or advisory environment.
- Proven track record leading and managing product managers with accountability for utilization, performance, and client satisfaction.
- Experience owning a portfolio of client accounts with direct responsibility for delivery quality, scope, and financial performance.
- Demonstrated success building and scaling data or AI products from MVP to production.
- Deep understanding of the modern data and AI stack, including Snowflake, cloud platforms, BI tools, and agentic AI frameworks.
- Proficiency in product operating models, backlog management, specification quality, and KPI frameworks.
- Experience designing AI-assisted product workflows and embedding AI tools into delivery.
- Demonstrated pre-sales track record in SOW development, executive proposals, and closing consulting engagements.
- Strong executive communication skills for board-level and C-suite audiences.
- Ability to travel up to 50% of the time.
- Experience working in global or remote teams across the U.S., LATAM, and India.
Responsibilities
- Own the design, delivery, quality, scope, and financial performance of AI and data product engagements.
- Translate complex client requirements into scalable product strategies.
- Define and enforce backlog standards and adoption KPIs across all team engagements.
- Build relationships with executive client sponsors (CDO, CTO, CAO) to shape multi-phase roadmaps.
- Plan staffing and capacity across the practice to balance utilization and delivery.
- Lead pre-sales engagements including discovery, workshops, and SOW scoping.
- Develop and maintain product management standards, delivery frameworks, and reusable assets.
- Define AI productivity standards and evaluation models for team-wide implementation.
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