
Tuyển dụng AI Product Owner (Education & Research) tại Hà Nội
Việc này đang có 2 tin đăng trên VietnamWorks
| Nền tảng | Tiêu đề tin | Lương ghi trong tin | Hạn nộp | CV Work thấy từ |
|---|---|---|---|---|
| VietnamWorks | AI Product Owner (Education & Research) | không ghi | 28/11/2026 | 29/10/2026 |
| VietnamWorks | AI Product Owner (Education & Research) | không ghi | 28/10/2026 (đã qua) | 28/09/2026 |
Các tin ghi khác nhau về hạn nộp — ô tô đậm.
Lịch sử tuyển vị trí này: CV Work ghi nhận tin đầu tiên ngày 28/09/2026, đến nay đã có 2 tin đăng; lần gần nhất 29/10/2026.
Mô tả công việc AI Product Owner (Education & Research)
ABOUT THE POSITION
The AI Product Owner (Education & Research) turns initiatives set by the AI Product Manager into AI features that work reliably and are used by learners, instructors and researchers at VinUniversity. The role is responsible for an assigned product area, from clarifying use cases and maintaining a prioritized backlog to shaping the user experience and coordinating delivery with AI engineers and researchers. It evaluates released features through product analytics and AI evaluation, and manages pilot operations until the product is ready for operational handover. This is a hands-on role in a small team that uses AI tools throughout product work: the Product Owner builds prototypes, analyzes data directly and defines AI quality requirements. The Product Owner defines user requirements and acceptance criteria; engineers own the technical solution.
KEY RESPONSIBILITIES
1. Use Case Discovery & Requirements
Use Case Clarification
• Work with users and stakeholders in the assigned area — learners, instructors, coaches and research staff — to understand current practice and turn high-level use cases into clear goals, scope and success criteria before development starts.
• Benchmark leading learning and research products that address the same problems, and apply those insights to the definition of each feature.
Requirements & Backlog
• Write user flows, user stories and acceptance criteria that engineers can build from directly, specifying what the AI should do, what it must not do, and the quality level required.
• Own a single prioritized backlog for the area; resolve open questions before work starts and accept completed stories against their acceptance criteria.
2. UX, Prototyping & AI Tools
UX & Rapid Prototyping
• Design the user experience of each feature, including the conversational experience, through user flows and simple wireframes within the University's design system.
• Build prototypes with AI and no-code tools and test them with real users before committing engineering resources; refine the prototypes based on test results.
Using AI in Product Work
• Use AI tools as the standard toolkit to synthesize research, write specifications, support design, generate test data and prepare reports.
• Stay current with AI tools, proactively test new approaches in product work, and share effective practices with the team.
3. Delivery & Project Management
Planning & Timeline
• Plan delivery for the area against the roadmap milestones: break initiatives into releases, manage dependencies and risks, and report potential delays early.
• Coordinate shared resources such as quality assurance (QA) staff, contracted engineers and subject-matter experts.
Release Management & Approvals
• Coordinate regular planning, reviews and demos with the development team, and define the scope of each release.
• Prepare the product documentation required for Vingroup's approval checkpoints, and track findings from security reviews and user testing until they are resolved.
4. Product Analytics & AI Evaluation
Product Analytics & Experiments
• Define the metrics and data each feature must capture from the start; build and analyze dashboards of usage, engagement and outcomes.
• Design and run feature-level experiments and pilots with real users; use the evidence to decide whether to retain, revise or discontinue each feature.
AI Evaluation & User Acceptance
• Assess AI quality and readiness for release: agree evaluation criteria and benchmarks with the AI Product Manager, coordinate subject-matter experts' contributions to data labeling and evaluation, and assess accuracy, groundedness (support from provided sources), safety and cost.
• Plan and run user acceptance testing for each release, with scenarios per user group and clear pass/fail conditions.
5. Product Operations & Continuous Improvement
Pilot Operations
• During build and pilot, run day-to-day operations directly with the engineers: onboard users, provide initial user support, and assess and prioritize reported issues.
• Keep the product usable while it is still changing; track usage, AI output quality and user satisfaction.
User Feedback & Handover
• Review user and operational feedback weekly, turning usability issues, unusual use cases and unmet needs into prioritized backlog items.
• Once the product is stable, hand over day-to-day operations to the designated team with documentation, clear support responsibilities and quality monitoring in place. Remain accountable for product usage and AI output quality, and prioritize further improvements.
Mentoring & Training
• Mentor and train fresh graduates and junior team members in product discovery, requirements, prototyping and AI-assisted workflows through hands-on guidance, work reviews and regular feedback.
1. Required Qualifications< 1. Required Qualifications • Bachelor's degree in Business Administration, Computer Science, Information Systems, Data Science, Education, Design or a related field. • Minimum 3 years' experience as a Product Owner, Product Manager, Business Analyst or Product Designer on software products used by real users, including at least 1 year on AI or machine learning products. • Experience planning software delivery and managing schedules, and coordinating user acceptance testing or releases. • Ability to write clear user stories, business flows and acceptance criteria covering expected AI behavior and quality thresholds, and assess actual outputs against those criteria before release. • Data-driven decision-making: ability to define metrics, build and analyze dashboards, and interpret A/B tests or pilot results to guide feature priorities and improvements; working familiarity with SQL or analytics tools. • UI/UX skills: ability to sketch user flows and simple wireframes, experience conducting usability tests, and familiarity with a prototyping tool. • Experience using AI tools daily for research, writing, design and prototyping, with the ability to build working prototypes independently using AI or no-code tools. • Strong written and verbal communication in Vietnamese and English. • Alignment with VinUni's core values (EXCEL): Empathy, Creativity, Leadership Mindset, Exceptional Capability, and Entrepreneurial Spirit. 2. Preferred Qualifications • Experience in education technology, learning platforms or learning management system (LMS) integration. • Background in teaching, instructional design or learning sciences. • Experience with AI evaluation: labeling rounds with subject-matter experts, evaluation datasets, benchmarks or LLM-as-judge results (using large language models to assess AI outputs). • Agile or PMP certification. • Experience in early-stage teams building products from the ground up. • Background in UI/UX design or conversational experience design. COMPENSATION & BENEFITS • The salary and benefits are competitive and commensurate with qualifications and experience. We thank all applicants for their interest. Please note that only those candidates selected for interviews will be contacted.Yêu cầu công việc
Quyền lợi
Nhà tuyển dụng Trường Đại học VinUni
Trường Đại học VinUni · Hà Nội

Trường Đại học VinUni là nhà tuyển dụng ngành Giáo dục, quy mô 25-99 nhân viên. Hiện đang tuyển 15 vị trí tại Hà Nội, mức lương trung bình khoảng 22 triệu/tháng.
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