Platform & Modelling Engineer for AI Infrastructure

A*STAR - Agency for Science, Technology and Research

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Job summary

A*STAR seeks a Platform Engineer or Modelling & Simulation Engineer to help build and support the digital infrastructure for its modelling, simulation and agentic AI projects in Singapore. The role welcomes candidates with strong fundamentals in either platform/infrastructure engineering or modelling and simulation, and an interest in advancing researchers' workflows.

You will design and maintain hybrid infrastructure, automate workflows, collaborate with researchers and cybersecurity teams,

Qualifications

Degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
Experience in platform engineering, DevOps, cloud infrastructure, Linux administration, SRE, or research computing.
For platform-focused candidates: good working knowledge of Linux systems, basic networking, and at least one cloud platform.
Some experience with automation or scripting (Bash, Python, Terraform, Ansible), containers, CI/CD, or infrastructure-as-code, or with modelling and simulation software such as MATLAB/Simulink or Python-based scientific computing.
Awareness of security good practices, such as access control, encryption, patching, logging, and secure remote access.
Ability to communicate clearly with technical and non-technical stakeholders, and an interest in learning AI/ML infrastructure concepts such as local model deployment or agentic AI systems (no expertise required).

Responsibilities

Design, build, and maintain hybrid infrastructure (on-premise, cloud, and containers) for modelling, simulation, and scientific computing workloads.
Develop, build, and validate modelling and simulation models and computational workflows (e.g., discrete-event, agent-based, physics-based, or systems simulation).
Automate infrastructure, operational, and simulation workflows (execution, calibration, results analysis) using scripting, infrastructure-as-code, and DevOps practices.
Work with researchers, engineers, cybersecurity teams, and stakeholders to translate requirements into practical technical solutions.
Contribute to CI/CD pipelines, deployment automation, and documentation, and help enable secure, federated modelling and simulation workflows across systems and teams.
Deploy and maintain local AI infrastructure, including GPU-based compute resources, and support the integration and reliability of agentic AI systems and tooling.