**Job overview**

We are hiring a Senior AI Product Owner to turn messy internal needs around LLMs, agents, data, and AI operations into requirements that engineering teams can actually build.

You should have owned product work end to end before. You do not need to be an AI engineer, but you should be comfortable discussing data\-heavy products, asking AI engineers the right questions, and keeping trade\-offs visible when the answer is not obvious.

This is a senior individual contributor role reporting to the Evaluation Platform Team Lead. Experience with LLMs, prompt workflows, RAG, agents, model providers, telemetry, or data quality is important. Experience with AI evaluation, golden datasets, regression gates, or production feedback loops is a strong plus.

**Key Responsibilities:**

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Define requirements for AI product and platform areas such as model setup, prompt and agent configuration, RAG workflows, telemetry, and reliability controls.

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Write clear PRDs, user stories, acceptance criteria, process flows, and backlog items for engineering discussion.

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Shape platform features with AI engineers, data analysts, platform engineers, and business teams, with a bias toward reusable solutions instead of one\-off demos.

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Define success metrics for platform features, including adoption, workflow completion, output quality, cost visibility, latency, and reliability.

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Use evaluation results, production feedback, error patterns, and regression risks to make AI quality visible in product decisions.

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Help design operating workflows for AI products, including human review, approvals, audit trails, privacy checks, rollout rules, and production monitoring.

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Nice to have: use AI coding or prototyping tools such as Cursor, Claude, ChatGPT, v0, Retool, or similar tools to test ideas before asking engineering to build them.

**Requirements:**

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5\+ years of experience in Product Owner, Product Manager, Business Analyst, Product Analyst, or similar product roles.

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Has owned product work for complex software, data\-heavy products, internal platforms, or technical B2B systems.

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Comfortable working with engineering and data teams without needing every technical detail translated.

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Can make trade\-offs across user needs, engineering feasibility, data constraints, and delivery timelines.

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Familiar with practical AI product concepts such as LLMs, prompts, RAG, agents, telemetry, and data quality.

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Nice to have: experience with AI evaluation, golden datasets, regression gates, annotation workflows, or AI observability.

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Nice to have: hands\-on use of AI tools such as ChatGPT, Claude, Cursor, v0, or Retool for research, prototyping, or requirement validation.

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Good written and spoken English, with the ability to explain product decisions clearly to both business and technical stakeholders.

**Contact:**

Ms. Nguyệt Zalo/Call: 0769 288 088Email: [email protected]

Office: Hanoi: Technopark, Gia Lam