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AI Technical Project Manager – GenAI & Agentic Applications (內湖瑞光)

Advantech · Taipei_Neihu

  • Manufacturing & Industrial
  • 5,001–10,000 employees
  • Neihu District, Taipei 114

Weak hiring record · median 108 days open

7272

Hiring signal

Open

Still listed on the employer's own board · How we score

All reasons
  • Open 46 days
  • 70% of this employer's openings are over 60 days old

In its favour

  • Still listed on the employer's own board

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AI Technical Project Manager – GenAI & Agentic Applications (內湖瑞光) at Advantech. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Advantech is looking for an AI Technical Project Manager to lead the delivery of generative AI and agentic AI applications from concept through deployment and adoption.

In this role, you will work closely with business stakeholders, AI engineers, and cross-functional teams to identify business needs, define project scope and requirements, and drive projects through planning, development, testing, rollout, and continuous improvement.

This is a hands-on delivery role for someone who can connect business objectives with technical execution. Beyond managing timelines, you will help teams apply AI to improve workflows, knowledge access, and operational efficiency while ensuring that solutions are practical, secure, and scalable.

Key Responsibilities

  • Define project scope, requirements, priorities, deliverables, and success criteria.
  • Translate business needs into clear and actionable requirements for technical teams.
  • Develop project plans and manage schedules, milestones, dependencies, risks, and scope changes.
  • Work closely with AI engineers and application teams to clarify requirements, resolve issues, and support delivery decisions.
  • Coordinate testing, launch readiness, user onboarding, deployment, and post-launch improvement.
  • Partner with stakeholders to identify opportunities for applying generative AI and autonomous agents to business workflows.
  • Establish appropriate guardrails, approval points, and human oversight for AI-enabled processes.
  • Communicate project progress, risks, decisions, and outcomes to stakeholders and leadership.
  • Maintain practical project documentation and promote continuous improvement in AI project delivery.
  • Support other enterprise application and system-integration projects when required.

Required Qualifications

  • 3–5 years of experience in technical project management, technical program management, product delivery, or a comparable role.
  • Experience managing software, data, cloud, or AI-related projects from requirements definition through production launch.
  • Strong project planning, scope management, problem-solving, and organizational skills.
  • Strong stakeholder-management and communication skills.
  • Ability to work closely with engineers and translate between business and technical teams.
  • Basic understanding of software development, system integrations, APIs, cloud services, or data flows.
  • Experience coordinating testing, deployment, rollout, and user adoption.
  • Bachelor’s degree in a relevant field or equivalent practical experience.
  • Professional working proficiency in English and Mandarin Chinese.

Preferred Qualifications

  • Experience with generative AI, machine learning, LLM-based applications, or autonomous AI agents.
  • Familiarity with retrieval-augmented generation (RAG), enterprise knowledge management, or AI-enabled workflow solutions.
  • Experience with Azure, AWS, or other cloud and AI platforms.
  • Understanding of AI governance, security controls, monitoring, and human-in-the-loop design.
  • Familiarity with Agile or Scrum practices and tools such as Jira or Azure DevOps.
  • Experience with enterprise applications, API integrations, or CI/CD processes is a plus.
  • PMP, Scrum, Agile, or another relevant certification is a plus but not required.

What Success Looks Like

Success in this role means delivering AI solutions with well-managed scope and timelines, maintaining strong alignment between business and technical teams, and ensuring that solutions are successfully deployed, adopted, and able to deliver measurable business value.

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