What We Are Looking For: • 7+ years of product management experience, with significant experience building and shipping B2B software products. • Strong hands-on experience building AI-powered products, where AI is a core part of the product experience and customer outcome. • Deep practical understanding of AI evaluation and experience building evaluation frameworks for AI products. • Strong experience with AI monitoring and observability, including identifying, diagnosing, and addressing failures in production AI systems. • Strong data skills and experience working with large-scale data. You should be comfortable understanding data structures, exploring datasets, analyzing data, and using data to validate product hypotheses and AI behavior. • Experience designing and building grounding systems and evaluation systems, rather than simply consuming AI APIs. • Experience with modern AI application architectures, including LLMs, RAG, embeddings, prompting, model selection, agents/workflows, and orchestration. • Demonstrated ability to take an ambiguous problem, formulate hypotheses, validate them with data and experimentation, and turn the resulting insight into a production product. • Experience building products for B2B customers in heavily regulated industries, such as financial services, fintech, insurance, healthcare, or similar domains. • Strong understanding of enterprise AI considerations including accuracy, reliability, explainability, security, governance, data quality, and auditability. • Ability to work deeply with technical teams and engage in detailed discussions about AI system behavior without needing to be the engineer implementing the system. • Familiarity with the AWS ecosystem is preferred. • Strong product judgment and the ability to distinguish between an impressive AI demo and an AI system that is genuinely reliable enough for production use. What Will Set You Apart: • You have taken an AI product from hypothesis prototype evaluation production continuous monitoring and improvement. • You have personally designed or owned an AI evaluation framework and understand why evaluation is central to building reliable AI products. • You have worked through difficult AI failure modes and know how to investigate whether a problem originates in the model, data, retrieval, grounding, prompting, orchestration, or product workflow. • You have experience building AI products where incorrect outputs have meaningful business or customer consequences. • You are comfortable challenging an initial hypothesis when the data or evaluations do not support it. • You naturally think in terms of measurable customer outcomes rather than AI features. • You enjoy getting into the details and are equally comfortable discussing a customer workflow, analyzing an evaluation dataset, investigating AI output failures, and working with engineers on the product architecture.