Product marketing manager manager

AI Product Manager Location: Remote, Nationwide Our client is building the next generation of intelligent digital experiences, with a focus on making advanced AI genuinely useful, dependable, and intuitive in everyday life. They are seeking an AI Product Manager who can operate comfortably at the intersection of product strategy, machine learning, and software engineering. This is an opportunity to influence sophisticated AI products from the inside out, shaping not only what gets built, but how models, systems, and user experiences work together at scale. This is a highly technical product role for someone who enjoys ambiguity, understands the realities of production AI, and can partner deeply with engineering teams. The right candidate will bring strong technical judgment, hands-on familiarity with AI and LLM products, and the independence to turn complex technical challenges into focused product priorities. Opportunity to shape sophisticated AI products with meaningful, large-scale user applications. High ownership across product direction, technical decisions, quality standards, and execution. Direct collaboration with experienced machine learning and software engineering teams. Exposure to challenging problems involving AI reliability, evaluation, system performance, and user experience. Remote flexibility for candidates located across the United States. Lead product direction for technically complex AI capabilities, connecting user needs with model behavior, engineering constraints, and measurable outcomes. Turn emerging AI capabilities into practical product experiences that perform consistently in real-world environments. Partner with machine learning and software engineering leaders to shape architecture decisions, technical requirements, release priorities, and product behavior. Establish quality standards and evaluation approaches that combine quantitative testing, production performance signals, experimentation, and human review. Guide prompt, model, and workflow improvements through structured testing, while identifying issues such as inaccurate outputs, bias, behavioral drift, and unpredictable responses. Evaluate difficult product decisions across model quality, responsiveness, infrastructure expense, system dependability, and overall user experience. Bring structure to open-ended technical challenges, establish clear priorities, and use production signals and user feedback to continuously improve product performance. Strong computer science foundation with practical knowledge of algorithms, data structures, software architecture, and system design. Ability to confidently read technical specifications, challenge assumptions, and discuss implementation approaches with senior engineers. Solid understanding of machine learning concepts and the operational realities of deploying modern AI systems into production. Experience building or managing products powered by machine learning, generative AI, or large language models. Hands-on experience with AI evaluation, including testing model behavior, refining prompts or pipelines, developing feedback mechanisms, and recognizing common AI failure modes. Track record of owning complex technical products end-to-end while partnering closely with senior software engineering and machine learning stakeholders.