Principal Product Manager, AI
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LTKCreator commerce
Location: United StatesFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 8+ years of Product Management experience
- Required Skills
- Data AnalysisMachine LearningProduct ManagementPrototyping
Requirements
- 8+ years of Product Management experience, including ownership of complex technical products and multi-quarter strategy.
- Demonstrated experience shipping and improving AI/ML products in production, including LLM applications, AI agents, or model-backed workflows.
- Experience working directly with ML engineers and applied scientists to define model requirements, guide experiments, and translate results into product decisions.
- Concrete contributions involving model behavior, system architecture, data quality, reliability, latency, and cost.
- Deep expertise evaluating AI-powered products, including non-deterministic model and agent behavior.
- Experience building evaluation frameworks, investigating failure patterns, and improving evaluation practices.
- Hands-on experience using prototypes, evaluation tools, and data analysis to validate product ideas and improve product quality.
- Strong product judgment to identify AI opportunities and balance customer experience, business priorities, and technical constraints.
- Experience leading complex cross-functional initiatives and influencing senior leaders without direct authority.
- Understanding of responsible AI product development, including reliability, privacy, safety, transparency, and human oversight.
- Bachelor's degree or equivalent practical experience.
Responsibilities
- Define the long-term vision and multi-quarter AI product strategy for proprietary ML models, agent infrastructure, evaluation systems, and the knowledge graph.
- Translate customer problems into model capabilities and experiments with Machine Learning and Data Science teams.
- Partner with Engineering on model selection, retrieval, tool use, and build-versus-buy decisions.
- Define how agents understand customer goals, access tools and information, and obtain approval or customer oversight.
- Build representative evaluation datasets, investigate failures, and monitor production quality across task success, reliability, latency, and cost.
- Develop and evolve shared AI evaluation frameworks, tools, and quality standards across LTK.
- Partner with Product leads to identify AI opportunities and bring validated capabilities into customer-facing products.
- Champion responsible AI development, including reliability, privacy, transparency, and human oversight.
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