COMPANY DESCRIPTION
Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together – building a strong collegiality and morale within the university.
Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities – all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.
RESPONSIBILITIES
- Enhance and support SMU's enterprise AI platforms, including customisations, infrastructure, monitoring, and day-to-day operations.
- Maintain and govern AI access for approved applications and third-party tools, including API key issuance, model access management, usage monitoring, cost tracking, and governance controls.
- Build production-ready AI-enabled applications, APIs, backend services, and integrations using LLMs, agents, workflow automation, and enterprise data sources.
- Integrate AI platforms with Microsoft Azure, Entra ID, Microsoft 365, SharePoint, and Microsoft Graph; manage model deployments, endpoints, quotas, and access controls.
- Manage the full lifecycle of AI-enabled applications, including CI/CD, controlled releases, evaluation, and production support.
- Implement logging, monitoring, audit trails, content filtering, and other responsible AI safeguards aligned with institutional policies.
- Partner with AI governance, security, infrastructure, application, and business teams to ensure AI platforms and applications are reliable, secure, scalable, and fit for operational use.
- Contribute to AI literacy and enablement across the SMU community, including knowledge sharing, documentation, internal demos, and helping users adopt AI tools effectively.
- Other duties as assigned.
QUALIFICATIONS
- Degree in Computer Science, Information Systems, Software Engineering, Artificial Intelligence, Data Science, or a related discipline with 5 to 6 years of relevant work experience.
- Equivalent professional experience in software engineering, cloud engineering, platform engineering, or AI application development may also be considered.
- Relevant certifications in Azure, cloud engineering, DevOps, AI engineering, or Microsoft ecosystem technologies would be advantageous.
- Experience developing, maintaining, and supporting AI platforms used by multiple users, teams, or applications, with attention to reliability, scalability, monitoring, and ongoing enhancement.
- Able to design and build production-ready applications, APIs, and backend services that integrate LLMs, agents, and workflow automation.
- Understands Azure, Microsoft Entra ID, Microsoft 365, SharePoint, and Microsoft Graph. Able to configure SSO, user groups, role-based access control, and secure authentication patterns for enterprise applications.
- Able to work with Azure AI Foundry, model deployments, model endpoints, quotas, usage patterns, and access patterns.
- Able to support governed AI access layers for approved applications and tools, including API key issuance, model access, usage monitoring, and cost tracking.
- Understands data residency requirements, privacy controls, audit logging, and responsible AI practices. Able to implement safeguards aligned with institutional policies, including content filtering, usage governance, and compliance reporting.
- Able to manage the full lifecycle of AI-enabled applications, from development and CI/CD to environment promotion, controlled releases, deployment, monitoring, evaluation, maintenance, and ongoing production support.
- Comfortable with containers, cloud hosting, environment separation, logging, monitoring, and production support.
- Uses AI tools creatively and critically to accelerate coding, debugging, research, prototyping, and problem solving.
- Keeps up to date with emerging AI tools, models, and practices, and can translate relevant developments into practical applications, platform improvements, and adoption opportunities for SMU.