AI Engineer, DevOps

About the role

This position is hosted at Nanyang Technological University (NTU) under the office of the Vice President (Artificial Intelligence & Digital Economy). It is a hands-on DevOps role focused on running the university's data platform and central data management infrastructure, with a strong emphasis on using AI tools to make operations faster and more reliable.

Key responsibilities

• Run day-to-day operations of the Data Platform across GCP and AWS, covering environment health, capacity, performance, cost, security and SLOs, alerting policies and on-call practices.
• Lead incident response: triage, mitigation, blameless post-mortems and preventive actions.
• Operate the central data management infrastructure (pipelines, storage, catalogues, access control, lineage) and partner with engineers on reliability, throughput, cost and data quality.
• Maintain backup, retention, disaster recovery and data residency controls aligned to programme and funder requirements.
• Manage infrastructure-as-code (e.g. Terraform), CI/CD pipelines, container build/registry workflows and deployment automation.
• Strengthen observability with logs, metrics, traces and dashboards, and automate repetitive tasks.
• Deliberately use AI tools (e.g. Claude, Copilot, Cursor) for incident triage, log and metric analysis, runbook drafting, IaC generation and review, and on-call support, and build lightweight internal tools that leverage AI.
• Contribute to security, compliance and access reviews (secrets management, IAM hygiene, vulnerability patching, audit readiness).

Required profile

• Degree in Computer Science, Information Technology or equivalent.
• At least 3-5 years of DevOps, SRE or platform engineering experience operating production systems at non-trivial scale.
• Hands-on experience with GCP and AWS, including IaC, containers and orchestration and managed services.
• Strong cybersecurity knowledge, including IAM, least privilege, secrets management, network security, vulnerability and patch management, and familiarity with standards such as ISO 27001, NIST, OWASP and data protection requirements such as Singapore PDPA and GDPR.
• Working knowledge of data engineering and central data management, CI/CD, observability and incident response.
• Demonstrated use of AI tools in daily engineering work, solid scripting skills (e.g. Python, Bash, Go) and strong communication skills across cultures and time zones.
• Bonus: experience with multimodal data systems, open-source AI/data tooling, or Singapore public sector or research programmes.