Manager - Product (AI for End-User Experience & Engagement)

This role exists to bring Moni to MoMo's end-users - defining what an AI assistant should do for a consumer inside a super-app, designing the experience that makes it worth opening, and building the engagement loop that turns a first conversation into a habit.What You Will DoUse Case Definition for End-Users: Decide what Moni should and should not do for consumers. Research where MoMo users are stuck or under-served today, size the opportunities, and make the case for a narrow, high-conviction set of use cases over a broad, shallow one.End-to-End Experience Design: Own the consumer experience of Moni from first exposure to task completion - conversation design, response format, UI surfaces, error and hand-off states. Hold the bar for how the product feels, not only for whether the answer is correct.Platform Discovery & Entry Points: Own where and when Moni appears in the MoMo user journey - home, search, and in-flow features. Design the targeting and distribution logic, and negotiate placement, instrumentation and dependencies with platform teams.Engagement & Retention Loop: Define and drive the activation → habit → retention funnel for end-users. Diagnose drop-off through funnel and cohort analysis, design lifecycle interventions, and own repeat-usage metrics, not just first-use.Experimentation: Build the experimentation practice for the end-user surface, with hypothesis, metric, sample size and decision rule agreed before launch. Run the tests, kill what doesn't work, and turn the results into the next set of bets.Cross-functional Delivery: Partner with AI engineering, design, data, operations and platform teams. Write clear requirements, drive sprint delivery, run UAT, and ship on schedule with quality accepted before release.What You Will NeedKnowledge / SkillsConsumer product sense: Has built for a large, non-expert user base. Can look at a screen or a conversation transcript, articulate precisely why it fails a user, and specify the fix.Zero-to-one execution: Comfortable setting an initial scope under uncertainty, shipping something narrow, and expanding from evidence rather than from a roadmap written in advance.Engagement and growth fundamentals: Fluent in activation, habit formation, cohort retention, funnel diagnosis and lifecycle design. Knows the difference between a vanity metric and one that predicts retention.Experimentation discipline: Can design a valid A/B test, size it, and read the result honestly - including when the result says the idea was wrong.Data-driven decision making: Comfortable with dashboards, funnels and cohort data. Defines the success metric before proposing the solution.Platform collaboration: Able to work within the constraints of a shared platform - placement rules, targeting variables, tracking gaps - and drive long-cycle dependencies to resolution rather than reporting them as blockers.AI literacy: Understands conceptually how an LLM assistant works - prompting, knowledge base / RAG, evaluation - and how that shapes what the experience can and cannot promise.Clear communication: Can explain a design decision to an engineer, a trade-off to a business stakeholder, and a user's problem to both.Working Style & PersonalityUser-obsessed: Talks to real users, watches them use the product, reads real conversations, and is uncomfortable with an experience that is merely acceptable.Evidence over opinion: Brings data to disagreements about design, and changes their mind when the data says so.Ownership in ambiguity: Comfortable building the process where none exists, and following through past launch to the outcome.Fast learner in a moving field: The AI product stack changes every few months; actively tracks and tests what is new rather than waiting to be taught.Education & ExperienceBachelor's degree in Business, Economics, Engineering, Design or a related field.5+ years in product management, including demonstrable ownership of a consumer-facing product and its engagement or retention metrics.A track record of taking at least one product or major feature from zero to launch, and measuring what happened afterwards.Experience with agile delivery.Experience with AI or B2C products is a plus.Company Culture:Our company culture is built on Customer Centricity, Innovation, Teamwork, Excellence in Execution, Constant Learning. We value diversity and inclusivity and strive to create an environment where everyone are inspired to grow and succeed fast together.