IT Application Engineer

ENTEGRIS ASIA PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ENTEGIS ASIA PTE. LTD. in Singapore seeks an IT Application Engineer - R&D Application Support with expertise in modeling and simulation software on Linux HPC clusters.

The role covers installation, deployment, and management of software on Linux-based cloud infrastructure, optimizing HPC configurations, and collaborating with data scientists to run scalable workloads. You will ensure security and reliability of HPC systems in the cloud, design network solutions for license servers, and deploy

Qualifications

• Experience supporting modeling and simulation software environments.
• Experience with Ansys, Schrodinger, AMS and other modeling tools.
• Experience with building, deploying, and sustaining SLURM Linux clusters.
• Experience with SaaS.
• Exposure to multi-cloud environments (Azure, GCP, AWS).
• Experience in an Agile development environment.
• Prior work with application and user support and training in a support role.
• Four or more years of experience in cloud computing and application development.
• Two or more years of hands-on experience with Google Cloud Platform (GCP).
• Demonstrated expertise in cloud computing and cloud architecture, preferably within GCP environments.
• Knowledge of containerization technologies, including Docker, and cloud-based HPC solutions.
• Knowledge of infrastructure-as-code tools such as Terraform, CloudFormation, Packer, or Ansible.
• Proficiency with job scheduling and resource management tools such as SLURM, PBS, or LSF.
• Knowledge of storage architectures and distributed file systems, including Lustre, GPFS, or Ceph.
• Strong understanding of network architecture and security best practices.
• Understanding of license-server technologies and requirements, including FlexLM and DSLS.
• Experience deploying AI-enabled engineering workflows that integrate large language models, simulation software, optimization frameworks, and HPC infrastructure.
• Exposure to OpenFOAM and Python-based scientific computing environments
• Familiarity with Google Vertex AI, MLOps, model deployment, or AI platform operations
• Familiarity with secure AI deployment practices and controlled access to engineering software environments
• Experience deploying custom software applications, collaborating with vendors, and supporting requirements capture and implementation

Responsibilities

• Install, and manage software packages that run on HPC and storage infrastructure.
• Optimize computing speeds of software by optimizing HPC configurations.
• Collaborate with data scientists and engineers to deploy scalable modeling and simulation workloads.
• Ensure the security, scalability, and reliability of HPC systems in the cloud.
• Deploy and maintain AI and simulation workflows on cloud.
• Monitor and automate SLURM cluster operations.
• Document system design and operational procedures.

Skills

Cloud computing experience

Agile development experience

Support and training experience

GCP platform tools

Tools

SLURM

Docker

Terraform

CloudFormation

Packer

Ansible

Lustre

GPFS

Ceph

OpenFOAM

Google Vertex AI

FlexLM

Ansys

Schrodinger

AMS

Job description

Job Summary

Our team is looking for a highly skilled IT Application Engineer - R&D Application Support with expertise in Modeling and Simulation software applications running on Linux hardware clusters. The selected individual has expertise in installing, configuring, deploying, updating, and managing software application packages running in Linux based Cloud infrastructure, understanding various application licensing models, understanding networking protocols, network architecture, and security best practices such as identity and access management, encryption, and secure network design to ensure projects align with business goals, while driving innovation and continuous improvement.

Key Responsibilities

• Install, and manage software packages that run on High-Performance Compute (HPC) and storage infrastructure that supports scientific workloads
• Optimize computing speeds of software by optimizing HPC configurations.
• Collaborate with data scientists and engineers to deploy scalable modeling and simulation workload in an HPC environment
• Ensure the security, scalability, and reliability of HPC systems in the cloud
• Work with infrastructure team to design networking solutions to various license servers based on FlexLM and other technologies
• Deploy and maintain AI and simulation workflows on cloud
• Maintain and allocate licenses for commercial software
• Optimize HPC cloud resources for cost-effective and efficient use
• Drive innovation and stay current with the latest in cloud services and industry standard processes
• Provide technical leadership and guidance in cloud and HPC systems management
• Monitor and automate slurm cluster operations
• Document system design and operational procedures

Requisite Criteria & Skills

• Experience supporting modeling and simulation software environments
• Experience with Ansys, Schrodinger, AMS and other modeling and simulation tools, FEA, CFD, DFT, and MD.
• Experience with building, deploying, and sustaining SLURM Linux based clusters
• Experience with SaaS.
• Exposure to multi-cloud environments (Azure, GCP, AWS)
• Experience in an Agile development environment
• Prior work with application and user support and training in a support role
• Four or more years of experience in cloud computing and application development.
• Two or more years of hands-on experience with Google Cloud Platform (GCP) and related platform tools.
• Demonstrated expertise in cloud computing and cloud architecture, preferably within GCP environments.
• Working knowledge of containerization technologies, including Docker, and cloud-based HPC solutions.
• Working knowledge of infrastructure-as-code tools such as Terraform, CloudFormation, Packer, or Ansible.
• Proficiency with job scheduling and resource management tools such as SLURM, PBS, or LSF.
• Knowledge of storage architectures and distributed file systems, including Lustre, GPFS, or Ceph.
• Strong understanding of network architecture and security best practices.
• Understanding of license-server technologies and requirements, including FlexLM and DSLS.
• Experience deploying AI-enabled engineering workflows that integrate large language models, simulation software, optimization frameworks, and HPC infrastructure.
• Exposure to OpenFOAM and Python-based scientific computing environments
• Familiarity with Google Vertex AI, MLOps, model deployment, or AI platform operations
• Familiarity with secure AI deployment practices and controlled access to engineering software environments
• Experience deploying custom software applications, collaborating with vendors, and supporting requirements capture and implementation