Senior Product Manager

Risepoint

About The Position

Risepoint is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. We primarily work with regional universities, helping them develop and grow their high-ROI, workforce-focused online degree programs in critical areas such as nursing, teaching, business, and public service. Risepoint is dedicated to increasing access to affordable education so that more students, especially working adults, can improve their careers and meet employer and community needs. In this role, you will own a critical segment of the student journey—shaping how thousands of prospective students first engage with and navigate toward higher education. You will translate a compelling product vision into shipped features, working at the intersection of AI, data science, and human-centered design to deliver experiences that are personal, proactive, and genuinely useful. You will be one of the primary drivers of Risepoint’s technology-enabled student journey model, building the intelligent systems that help students find the right path, at the right time, with the right support. Your work will directly influence outcomes for regional universities and, by extension, expand access to education for working adults across the country. Risepoint’s mission to life by building the intelligent systems that make the student journey feel less like a transaction and more like a partnership. Through AI-powered personalization, proactive guidance, and data-driven decision support, you will help working adults navigate one of the most consequential decisions of their lives—returning to or continuing their education. Your work will directly enable Risepoint’s university partners to serve more students more effectively, expanding access to high-quality, workforce-aligned education at scale.

Requirements

5+ years of product management experience, with a track record of shipping impactful consumer or B2B SaaS products.
Experience partnering with engineering and data science to ship ML- or AI-enabled features: predictive models, ranking systems, automated workflows, or generative AI experiences.
Ability to frame AI/ML opportunities, define product requirements for intelligent systems, and guide teams through model evaluation, UX design, experiment setup, and iteration.
Strong analytical and problem-solving skills, with fluency in product analytics, A/B testing, and data-driven decision-making.
Exceptional communication skills, able to align engineering, design, operations, and leadership—especially when navigating ambiguity or explaining technical trade-offs.
A mission-driven, student-first mindset and deep interest in how AI can responsibly improve access, support, and outcomes in education.

Nice To Haves

Experience in higher education, edtech, or service-oriented journeys where AI augments expert human guidance.
Familiarity with human-in-the-loop workflows and the operational complexity of deploying AI in regulated or high-stakes contexts.
Background working with speech analytics, conversational AI, or student-facing digital products.

Responsibilities

Lead execution and evolution of a defined segment of the student journey, translating established strategies into scalable experiences using UX design and advanced analytics, including AI and ML where appropriate.
Identify opportunities to use predictive models, intelligent workflows, and generative AI to unlock proactive guidance, personalization, and operational efficiency.
Translate insights, research, and data into a roadmap with clear priorities and measurable student outcomes.
Partner with Engineering, Data Science, and Design to deliver personalization features that incorporate ML models, generative AI, and automated decision-support tools.
Define hypotheses and run experiments to validate value, accuracy, and user trust in AI-powered features.
Manage cross-functional workstreams, dependencies, risks, and stakeholder alignment for both traditional product initiatives and AI-enhanced solutions.
Establish success metrics for AI- and ML-driven features, including model performance, user experience impacts, and operational lift.
Lead the productization of manual and high-variance workflows into consistent, scalable, and increasingly intelligent experiences.
Introduce processes and frameworks to responsibly integrate AI—including transparency, bias mitigation, and user feedback loops.
Advocate for clarity, equity, and empowerment in every student interaction—especially in AI-led or AI-assisted experiences.
Ensure all solutions deliver real educational value, balancing automation with human support where needed.
Shape a POV on how AI should show up in the student journey now and in the future.