AI Product Manager

7 days ago


Hanoi Capital Region, Vietnam GSM - Xanh SM Full time

As a AI Product Manager, you will take ownership of one or more product areas strictly focused on
Artificial Intelligence (AI)
and
Machine Learning (ML)
. You will drive end-to-end product development, delivering impactful and innovative AI-driven solutions that align with business goals and user needs by
optimizing core operational and marketplace platform functions.

You'll work closely with cross-functional teams, including Data Scientists and ML Engineers, to build scalable, data-informed AI/ML products that specifically
leverage advanced algorithms to drive efficiency, enhance user experience, and maximize business performance
across all platform pillars. You will also lead the development of scalable AI APIs, orchestrate backend ML workflows, and ensure seamless collaboration between internal services and external partners.

Key Responsibilities:

Focus on AI Optimization:
Ensure AI products deliver
superior operational efficiency, scalability, and user experience
in core logistics and marketplace functions, specifically spanning:

Key Responsibilities:

  • Focus on AI Optimization:
    Ensure AI products deliver
    superior operational efficiency, scalability, and user experience
    in core logistics and marketplace functions, specifically spanning:
  • Marketplace Dynamics:
    Optimizing supply and demand balancing, and dynamic pricing strategies.
  • Logistics & Fulfillment:
    Enhancing order allocation, routing, and real-time dispatch systems.
  • User Experience & Personalization:
    Driving smart interactions, recommendations, and customer personalization.
  • Trust & Safety:
    Building models for fraud detection, risk management, and compliance assurance.
  • Own the lifecycle of AI/ML products across Platform domains:
    From design, model development, testing, release, and operations, ensuring global adaptability.
  • Lead the AI Strategy:
    Collaborate with business stakeholders, designers, Data Scientists, engineers, and analysts to define clear AI product roadmaps and translate them into actionable plans, with a focus on delivering high-impact models for
    dispatch, pricing, payment, customer, supply, and demand optimization
    .
  • Focus on AI Optimization:
    Ensure AI products deliver
    superior operational efficiency, scalability, and user experience
    in core logistics and marketplace functions, such as
    optimizing order allocation, predicting market demand, and setting dynamic prices
    .
  • Partner with business teams to deliver solutions tailored to specific needs and drive continuous innovation through the
    application of advanced machine learning models in various platform systems.
  • Manage cross-functional teams to ensure efficient AI product delivery and market alignment.
  • Analyze data, model results, and incorporate user feedback to improve model accuracy, product competitiveness, and user satisfaction.
  • Define and monitor key AI/ML product metrics (e.g., model accuracy, operational efficiency lift, impact on key business metrics like fill rate and utilization),
    identify trends, and implement optimization plans to enhance product capabilities.

Qualifications:

  • Strong product management experience with a solid foundation in AI/ML.
  • Excellent communication and collaboration skills, with experience managing cross-functional teams (including Data Scientists and ML Engineers).
  • Ability to coordinate with engineering, business, and external partners; excellent stakeholder management.
  • High ownership, proactive problem-solving, and a results-driven approach.
  • Strong business acumen, attention to detail, and user experience design expertise
    for AI-powered solutions
    .
  • Strong analytical and problem-solving skills; highly comfortable working with large datasets and collaborating with Data Scientists.
  • A logical thinker with excellent analytical skills and a customer-first mindset.
  • Adaptable in fast-paced environments, with strong stakeholder management abilities.
  • Strong experience in developing and executing product roadmaps from ideation to execution plan, writing Product Requirement Documents (PRD), including managing timelines and project milestones.

Qualifications:

  • Strong product management experience with a solid foundation in AI/ML.
  • Excellent communication and collaboration skills, with experience managing cross-functional teams (including Data Scientists and ML Engineers).
  • Ability to coordinate with engineering, business, and external partners; excellent stakeholder management.
  • High ownership, proactive problem-solving, and a results-driven approach.
  • Strong business acumen, attention to detail, and user experience design expertise
    for AI-powered solutions
    .
  • Strong analytical and problem-solving skills; highly comfortable working with large datasets and collaborating with Data Scientists.
  • A logical thinker with excellent analytical skills and a customer-first mindset.
  • Adaptable in fast-paced environments, with strong stakeholder management abilities.
  • Strong experience in developing and executing product roadmaps from ideation to execution plan, writing Product Requirement Documents (PRD), including managing timelines and project milestones.
  • Technical Understanding:
    Familiarity with AI/ML fundamentals, the model development lifecycle, and related technology platforms (e.g., data platforms, ML Ops, model serving APIs).

Preferred Skills:

  • 3–5+ years in AI/ML product management, or complex Platform/API product management focused on optimization.
    Experience with ride-hailing, logistics, payments, or marketplaces is a strong plus.
  • Ability to manage multiple workstreams simultaneously and adapt in a fast-changing environment.
  • Familiarity with the core operations of
    ride-hailing, logistics, e-commerce, food delivery
    , or complex backend/platform products,
    especially those supported by AI
    .
  • A technical background or
    familiarity with APIs, backend systems, and ML Ops architecture
    is a plus.

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