Product Manager - AI

We are recruiting an experienced AI Product Manager to build core AI products for our trading platform. This role focuses on large model application and LLM generative recommendation system development, combining AI technology with financial trading scenarios to drive business growth and user transaction conversion. Benchmarking mature financial AI products from Tonghuashun, East Money and Ant Fortune, you will lead full-cycle AI product planning, design and iteration.

Responsibilities

1. Recommendation strategy: Own personalized presentation of product components and the strategy roadmap for "For You" recommendations; define problems, mechanisms and metrics together with ML engineers.
2. User features: Work with data engineers on user feature definitions, pipelines and launch; evaluate feature coverage, freshness and contribution to model performance, retiring weak features and adding new ones to keep improving the recommendation models.
3. AI products: Contribute to the planning, design and delivery of AI agents and AI products; design prompts, RAG knowledge bases and data-source integration; define agent task flows, capability boundaries and fallbacks, and use user profiles to personalize AI output.
4. AI evaluation & compliance guardrails: Build the evaluation loop of business metrics + model metrics + user feedback (accuracy, hallucination rate, adoption, badcase regression sets); set prompt standards and hard-rule guardrails so AI output is traceable and auditable.
5. Data & experimentation: Define north-star and process metrics (CTR, trading conversion, volume, retention, AI adoption); lead tracking design, A/B testing and attribution, driving iteration by measurable incremental impact.
6. Cross-functional collaboration: Work closely with ML, data, engineering, design, risk & compliance, operations and business lines (Spot / Futures / Copy Trading / Earn / Stocks) to take products from 0→1 and scale from 1→N.

Requirements

1. Bachelor's degree or above; CS, Statistics, Math or Financial Engineering preferred.
2. 5+ years of internet product management, including 3+ years in recommendation / growth strategy, with measurable incremental impact from strategy initiatives you owned.
3. Solid understanding of recommender systems (recall, ranking, re-ranking, features, cold start, explore–exploit); able to discuss strategy and trade-offs with ML engineers.
4. Strong data skills: hands-on SQL, event tracking design, rigorous A/B testing (sample size, significance, traffic splitting, guardrail metrics) and attribution.
5. Builder mindset: a heavy user of AI tools who prototypes, pulls data and writes eval sets — not just PRDs.
6. Clear structured thinking; able to drive alignment and execute under ambiguity.
7. Bilingual Skills English and Mandarin.