JOB DESCRIPTION

• End-to-end project leadership (industry deployment): Plan, execute, monitor and close concurrent AI deployment projects across manufacturing partners, ensuring delivery on scope, schedule, cost, quality and deployment readiness.
• Industry problem scoping & requirements translation: Deep-dive with technical/research teams and industry stakeholders to convert operational pain points into clear requirements, milestones, and acceptance criteria for deployment.
• Cross-functional orchestration: Act as the execution integrator across AI researchers, manufacturing domain experts, AI engineering/productisation teams, Business Development, Ops/Finance/Legal to ensure smooth delivery and fast issue resolution.
• Governance, compliance & reporting: Ensure compliance to programme governance and grantor requirements; drive disciplined reporting to internal and external stakeholders using programme rhythms (e.g., project dashboards / cadence reviews).
• Risk, issue & change management: Proactively manage delivery risks (data readiness, integration constraints, scope creep, partner dependencies) and execute change control to protect outcomes.
• Impact realisation & outcome measurement: Define and track project outcome indicators (e.g., time savings, productivity, defect reduction, planning efficiency), coordinate post-project data capture where required, and package evidence for programme impact reporting.
• Stakeholder management: Manage stakeholder environments spanning industry, public agencies, and  leadership and prepare decision-led updates 

JOB REQUIREMENTS

• Bachelor's degree in Engineering / Industrial Systems / Manufacturing-related discipline
• More than 5 years of project management experience delivering technology projects in manufacturing / production environments (e.g., automation, inspection, planning/scheduling, digital manufacturing, industrial 4.0).
• Demonstrated experience delivering cross-functional, multi-party projects, preferably involving AI/analytics, digitalisation, or industrial software deployments.
• Working understanding of manufacturing operations and production technologies (e.g., MES/ERP, shopfloor data, process flows, quality systems, maintenance workflows, automation contexts).
• PMP / Agile certification is advantageous.
• Strong project execution discipline: scope/schedule/cost control, risk management, and governance compliance.
• Strong stakeholder management and communication skills; confident interfacing with industry leaders and cross-functional internal teams.
• High adaptability and structured problem solving; able to navigate ambiguity typical of R&D-to-deployment work.

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.