全职 AI Product Manager 工作, 薪水, Digile Federal Territory 公司招聘中 - Ricebowl

Digile’s AI Practice is currently looking for an AI Product Manager to join our Forward Deployed Engineer (FDE) Pods, customer‐embedded, cross‐functional AI delivery units that turn AI capabilities into production‐grade workflows with measurable business impact. The ideal candidate brings a blend of strong skillsets as requested in the section below and a strong passion for using AI to transform how businesses operate.

The main job responsibility of the AI Product Manager is to own business value, roadmap and prioritisation for the pod. As the AI Product Manager, you hold decision rights on use case prioritisation and will work closely with the Senior FDE (Pod Lead), Junior FDEs, Domain SMEs and customer stakeholders to define use cases, set success metrics, manage delivery cadence and drive adoption, ensuring every use case shows quantifiable operational improvement. You must be capable of working independently, thinking strategically and having fun along the way!

• Defining AI use cases with customer stakeholders, including success metrics, business case and expected impact.
• Leading discovery and workflow mapping with Domain SMEs to identify bottlenecks and map current versus AI‐augmented workflows.
• Owning the product backlog, prioritisation and delivery cadence, including bi‐weekly demos, feedback sessions and backlog refinement.
• Aligning stakeholders across business and technology and jointly owning customer alignment with the Senior FDE.
• Owning UAT and validation sign‐off together with Domain SMEs and customer users.
• Driving adoption and change management, including user training, communications and workflow redesign.
• Tracking and reporting pod KPIs such as time‐to‐prototype, time‐to‐production, workflow adoption rate, reduction in manual effort and business impact (hours saved, cost avoided, throughput improved).
• Leading the monthly impact review and contributing to weekly delivery reports and quarterly roadmap alignment and scaling plans.
• Identifying and shaping additional use cases to scale successful solutions across the customer’s organisation.
• Ensuring responsible AI, data privacy and compliance considerations are captured in requirements from the start.
• Willing to travel and be stationed at customer sites, within and outside of Kuala Lumpur, Malaysia.
  
  

Experience

• 5+ years of experience in product management, digital transformation or technology consulting, with at least 2 years working on AI/ML, data or automation products.
• Proven track record of taking solutions from discovery to production adoption with measurable business outcomes.
• Experience in customer‐facing, enterprise B2B delivery or consulting engagements.
• Experience leading change management and user adoption programmes.
• Relevant certifications such as CSPO, PMP or Prosci will be a plus point.
  
  

Skills

• Solid understanding of generative AI and LLM capabilities, limitations and cost drivers, sufficient to assess feasibility and engage credibly with engineers.
• Good knowledge of EPC / PMC project delivery across the engineering, procurement, construction and commissioning (E/P/C/Cx) lifecycle, including project controls (L2/L3 schedules, cost plans, plan vs actual progress) and PMC deliverables and reporting.
• Familiarity with construction digital platforms such as Autodesk Construction Cloud (ACC) / Autodesk Forma, CxAlloy and Primavera P6, and procurement, sufficient to define use cases and data requirements.
• Strong ability to define measurable KPIs, business cases and dashboard requirements across progress, deliverables, HSE, OFCI/procurement, construction, quality & turnover and claims.
• Experience running phased delivery from POC to foundation to production, using Agile/Scrum and tools such as Jira or Azure DevOps.
• Strong process mapping skills to identify automation opportunities in PMC deliverables, QA/QC, NCR/punch closure and commissioning workflows.
• Understanding of responsible AI governance, including defining human‐in‐the‐loop approval points where qualified engineers validate AI outputs, and preparing AI deployment plans covering use cases, data flows and access rights.
• Change management skills, including designing role‐based training for project leadership, project controls, engineering, construction, QA/QC and commissioning teams.
• Stakeholder management skills up to C‐level, including client project leadership and IT/security teams.
• Data literacy; working knowledge of SQL or dashboarding tools such as Power BI will be a plus point.
• Strong ability to present information to customers and our leadership team in a manner that is clear, concise and open, with excellent written and verbal communication skills.