Head of Product, AI Business Intelligence
New
J
JobgetherPropTech, AI
Based in the United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 9+ years
- Required Skills
- Business IntelligenceProduct ManagementProduct DevelopmentPrototypingMarket Research
Requirements
- 9+ years of product management experience within a high-growth startup or technology company.
- Ownership of at least one product from 0-to-1 through launch and adoption.
- Demonstrated ability to build and ship products that customers actively use.
- Strong product judgment, design sensibility, and ability to turn ambiguous needs into compelling product experiences.
- Proven experience leading customer discovery and synthesizing qualitative feedback into strategy.
- Experience defining quality metrics, evaluation frameworks, testing processes, or feedback loops.
- Hands-on experience with LLMs, AI-powered products, or modern AI development tools.
- Strong understanding of AI product development, including model behavior, evaluation, and user trust.
- Builder mentality with a bias toward action, rapid prototyping, and iterative delivery.
- Experience with business intelligence, analytics, or data platforms.
- Experience in PropTech, multifamily housing, or real estate is a plus.
- Ability to work autonomously and manage cross-functional stakeholders.
Responsibilities
- Own the AI Business Intelligence product line from discovery, positioning, and roadmap development through launch, adoption, and ongoing optimization.
- Define where AI and language models create meaningful customer value, ensuring the platform is genuinely AI-native.
- Conduct customer discovery, market research, and regular feedback sessions with key customers to identify needs and prioritize product opportunities.
- Translate customer insights into clear product direction, specifications, workflows, prototypes, user stories, and actionable roadmaps.
- Partner closely with engineering, design, data science, and product leadership to rapidly build, test, and ship new AI-powered functionality.
- Develop evaluation frameworks, quality metrics, test suites, and feedback loops to measure AI output quality and improve performance.
- Establish and validate guardrails that ensure AI-generated outputs are reliable, explainable, and safe.
- Shape the underlying data foundation, including data requirements, normalization, and architecture.
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