Editorial summary

Nanyang Polytechnic is seeking a qualified Lecturer or Senior Lecturer in AI-Augmented Product Architecture to join the School of Engineering. The role involves delivering lectures, tutorials, and laboratory sessions, mentoring students across diploma and adult learning programs, and engaging in curriculum development, industry collaboration, and applied research. Candidates should possess relevant expertise in emerging technology domains and demonstrate strong pedagogical and industry engagement skills. Compensation details are not specified.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job https://singapore.job-q.com/jobs/detail/lecturer-snr-lecturer-ai-augmented-product-architect-sch-of-engineering-35469 first appeared in Job-Q.com on 02 Oct 2026]

[What the role is]

Nanyang Polytechnic is seeking a dynamic and experienced Lecturer/Senior Lecturer in AI-Augmented Product Architecture to contribute to our School of Engineering. This role involves teaching and mentoring students across both PET (Diploma) and CET (Adult Learning) programmes using modern pedagogical approaches, curriculum development in emerging technology domains, industry engagement, applied research, and academic administration.

[What you will be working on]

Instructional Delivery & Facilitation

• Deliver lectures, tutorials and laboratory sessions across full-time Diploma programs (PET) and adult workforce upskilling modules (CET).
• Adopt diversified pedagogical frameworks, including project-based learning, flipped classrooms, and blended e-learning spaces.
• Supervise and mentor students during final-year projects, multi-disciplinary capstone assignments, and professional internship placements, particularly in Edge AI, IoT systems, and distributed architectures.

Curriculum Design & Development

• Design, review, and revitalize instructional resources, module structures, and assessment rubrics aligned to emerging industry practices in Edge AI and distributed systems.
• Embed competencies such as AI model optimization and edge analytics into curriculum delivery.
• Develop hands-on lab modules involving embedded AI deployment, IoT telemetry pipelines, and hardware acceleration platforms.

Industry Engagement & Applied Research

• Establish partnerships with industry players in Edge AI, IoT, and smart infrastructure.
• Contribute to applied R&D and industry partnership in areas such as edge AI, digital twin systems can smart connected systems.
• Translate real-world deployments (e.g., edge inference, chiller optimisation, smart monitoring) into learning case studies.

Student Development & Administrative Duties

• Mentor students in technical and career development within Edge AI and embedded systems domains.
• Perform academic administration duties including assessment tracking and quality assurance.

#LI-Hybrid

[What we are looking for]

• Education: Degree or Postgraduate qualification in Computer Science, Computer Engineering, Information Systems, or related fields.

• Industry Experience: Minimum 3–5 years in software development, AI application development, or product engineering.

(Candidate should demonstrate strong proficiency in at least 2 of the following areas)

    i.    AI-Augmented Development & Low-Code/No-Code

• Experience with low-code/no-code and AI-assisted (“vibe coding”) tools to rapidly prototype web, mobile, and backend applications.

    ii.    Agentic AI & Workflow Orchestration

• Understanding of agentic AI concepts (reasoning, tool use, multi-step workflows) and ability to build agent-driven applications integrated with APIs or IoT systems.

    iii.   LLM Deployment (Cloud & Edge)

• Familiarity with deploying LLMs via cloud and/or edge (SLMs), including integration into applications and trade-offs (latency, cost, privacy).

    iv.   Cross-Platform Application Development

• Experience in building web and cross-OS mobile apps (iOS & Android) using frameworks such as Flutter or React Native, with simple, user-centric UI design.

    v.    AI Application Security & Risk Awareness

• Awareness of risks (e.g., prompt injection, data leakage, API vulnerabilities) and basic practices in secure AI application design and governance.

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