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ZEED TALENT TECHNOLOGY SDN.BHD is seeking an experienced New Product Introduction Engineer to drive NPI programs from concept to production in Penang. You will coordinate cross‑functional teams, manage timelines, and ensure first articles meet quality and cost targets.
The role requires a Diploma or Degree in Engineering and at least 5 years in NPI or manufacturing engineering, with strong knowledge of PPAP, DFM, FMEA, and DOE.
Formulate, coordinate, and execute project timelines for assigned NPI tracks.
Track project progress, mitigate bottleneck risks, and coordinate cross-functional teams to deliver flawless first articles on time, within budget, and to required standards.
Conduct comprehensive engineering reviews covering customer 3D data, bills of materials, design for manufacturability, failure mode and effects analysis, tolerance stack-ups, and process flows.
Develop production-ready packaging standards and clear technical standard operating work instructions.
Oversee the deployment of PPAP, FAIR, IQC, IPQC, and OQC matrices.
Drive structured corrective engineering loops using 8D and RCCA protocols to resolve pre-production abnormalities.
Lead post-project lessons-learned programmes and apply findings to future NPI activities.
Integrate Lean Manufacturing, Kaizen, and advanced automation frameworks to optimise line design, reduce tooling setup overhead, and lower operational unit costs.
Mentor, coach, and develop junior NPI engineers while building internal technical capability and professional accountability.
Diploma or Bachelor's Degree in Engineering or a closely related technical discipline.
At least 5 years of experience in NPI, manufacturing engineering, or technical product development environments.
Strong knowledge of project management frameworks, PPAP, DFM, FMEA, and DOE.
Proven understanding of precision manufacturing, high-tolerance machining, CEJ replication, and complex sheet metal manufacturing workflows.
Professional proficiency with engineering modelling systems.
Basic scripting capabilities or familiarity with AI productivity engineering tools is advantageous.
Experience with electromechanical assembly lines, structural dynamics, product quality testing, hydraulic or pneumatic infrastructure, or plastics manufacturing is advantageous.