NFC Internal Careers

1. AI Strategy & Governance

• Define NFC's AI roadmap in alignment with the D&T digital foundation strategy and business priorities

• Establish AI governance frameworks covering ethics, data privacy, model risk, and responsible use

• Advise the CDTO and business units on AI opportunities, feasibility, and build vs. buy decisions

• Stay current on the latest LLM developments, AI platforms, and industry trends relevant to education and operations

2. AI Use Case Delivery

• Lead end-to-end delivery of AI Minimum Viable Products (MVPs) in collaboration with business units across NFC brands

• Design, build, and integrate AI solutions using LLMs (e.g. Claude, GPT-4), RAG architectures, and agentic workflows

• Ensure AI solutions are integrated into NFC's key operational platforms and upcoming Low-Code and iPaaS platforms

3. Platform & Technology Leadership

• Drive adoption of NFC's three digital foundation platform types: Work Automation, Integration/iPaaS, and Low-Code Application Development

• Collaborate with Solution, Data, Application architecture teams to provide solution and architecture design for AI, automation, and integration initiatives in collaboration with the Solution Architecture and Data functions within the CoE

• Evaluate and recommend AI tooling, APIs, and cloud services appropriate for NFC's scale and budget

4. Team Building & CoE Development

• Upskill the CoE team as platforms and capabilities mature

• Foster a culture of experimentation, learning, and digital fluency within D&T and across NFC business teams

• Mentor junior team members and act as an internal AI champion

5. Stakeholder Collaboration

• Partner with Tech Business Partners to identify and shape AI demand from business units across NFC's brands

• Work cross-functionally with Application Services and Infrastructure & Cybersecurity teams to ensure AI solutions are secure, scalable, and well-integrated

• Communicate progress, risks, and outcomes clearly to senior leadership including the CDTO

Education

• Degree in Engineering or related field

Experience

• 5–8 years of experience in technology roles, with at least 3 years in AI/ML, data, or digital innovation

• Proven track record of delivering AI or automation solutions from concept to production

• Experience working in or with enterprise environments; education, social services, or consumer-facing sectors are a bonus

• Experience managing or mentoring a small technical team

• Exposure to application development lifecycle (Understanding how software is built, tested, and maintained)

Skills and Attributes

• Hands-on experience with Large Language Models (LLMs) such as Claude (Anthropic), GPT-4 (OpenAI), or equivalent

• Familiarity with AI application patterns: RAG (Retrieval-Augmented Generation), prompt engineering, agentic workflows, and fine-tuning

• Comfortable working with cloud environments (AWS, GCP, or Azure) and APIs

• Hands-on experience deploying ML models to production using containerisation tools (Docker, Kubernetes)

• Experience with CI/CD pipelines for ML using tools such as GitHub Actions, GitLab CI, or Jenkins

• Experience setting up model monitoring in production — covering data drift, model performance degradation, and inference latency using tools such as Arize, or Prometheus/Grafana

• Familiarity with LLM evaluation frameworks such as PromptFoo, DeepEval, or Ragas to assess output quality, relevance, and factual accuracy across generative AI pipelines

• Experience designing test cases for LLM applications that probe for hallucination, prompt regression, and unsafe outputs, with the ability to implement automated evaluation workflows in a CI/CD context

• Working knowledge of Python or equivalent for scripting and prototyping AI solutions

• Understanding of data pipelines, vector databases, and AI infrastructure

• Strong communicator — able to translate complex AI concepts into plain language for non-technical stakeholders

• Entrepreneurial and pragmatic to find ways to deliver value within constraints

• Comfortable with ambiguity and building from scratch as this is a greenfield role

• Genuine passion for using technology to improve education and community outcomes

• Working experience with Low Code development platforms, iPaaS, Atlassian products will be an added advantage

• Experience in early childhood education, social services, or regulated sectors

• Familiarity with Singapore's AI governance landscape and PDPA requirements

• Experience with Claude API (Anthropic), LangChain, LlamaIndex, or similar AI frameworks

• Knowledge of school management, CRM, HR, or finance enterprise systems

• Prior experience contributing to a Centre of Excellence or innovation function