AI/ML Platform Engineer — Bank-Grade DevOps for AI

Luxoft Singapore; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Luxoft Singapore is seeking an AI DevOps Engineer / MLOps Engineer to design, automate, and operate CI/CD pipelines for AI/ML deployments within a regulated banking environment. You will deploy LLMs from Hugging Face, containerise apps with Docker, and manage Kubernetes/OpenShift clusters across development, UAT, and production stages.

You will collaborate with AI engineers, data scientists, and security teams to implement IaC with Terraform/Ansible, monitor health with Prometheus/Grafana, and

Qualifications

• 6–10 years of experience in DevOps, Platform Engineering, or Cloud Engineering.
• Strong hands-on experience with Jenkins.
• Strong knowledge of GitHub, GitHub Actions, GitLab, or Bitbucket.
• Experience deploying AI/ML models from Hugging Face or similar model repositories.
• Strong Docker and Kubernetes/OpenShift experience.
• Experience with Linux system administration.
• Hands-on scripting experience using Bash, Python, or Shell scripting.
• Experience with CI/CD pipeline automation.
• Experience with Infrastructure as Code using Terraform or Ansible.
• Knowledge of container registries such as Artifactory, Nexus, or Docker Registry.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Understanding of GPU-enabled environments and NVIDIA CUDA ecosystem.
• Experience configuring model serving platforms and REST APIs / microservices.
• Experience with monitoring and logging tools including Prometheus, Grafana, ELK, Splunk, or Dynatrace.
• Strong troubleshooting and production support skills.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design, build, and maintain CI/CD pipelines for AI/ML model deployment.
• Deploy Large Language Models (LLMs) from Hugging Face and other model repositories into development, UAT, and production environments.
• Automate model packaging, versioning, testing, and release using DevOps best practices.
• Manage Kubernetes/OpenShift based AI platforms for model hosting and inference.
• Build deployment pipelines using Jenkins, GitHub Actions, GitLab CI, or similar CI/CD tools.
• Containerise AI applications using Docker and deploy them into Kubernetes clusters.
• Integrate AI solutions with enterprise applications using REST APIs and microservices.
• Manage model lifecycle, rollback strategies, monitoring, and production support.
• Implement Infrastructure as Code (Terraform/Ansible) for AI platform provisioning.
• Configure model serving platforms such as vLLM, Ollama, Triton Inference Server, or similar.
• Monitor application and model health using Prometheus, Grafana, ELK, Dynatrace, or Splunk.
• Optimise GPU resource utilisation and troubleshoot model performance issues.
• Collaborate with AI Engineers to productionise new models and inference pipelines.
• Ensure security, governance, and compliance requirements are met within the banking environment.
• Participate in production releases, incident management, and continuous platform improvements.

Skills

Jenkins

GitHub Actions

GitLab CI

Bitbucket

Hugging Face

Docker

Kubernetes/OpenShift

Linux system administration

Bash / Python scripting

CI/CD automation

Terraform / Ansible

Container registries

AWS / Azure / GCP

NVIDIA CUDA / GPU acceleration

REST APIs / microservices

Prometheus / Grafana / ELK / Splunk /

Dynatrace

Troubleshooting / production support

Communication with stakeholders

Tools

GitHub

Jenkins

Docker

Kubernetes

Terraform

Ansible

Artifactory / Nexus

AWS / Azure / GCP

Job description

Luxoft Singapore is seeking an AI DevOps Engineer / MLOps Engineer to design, automate, and operate CI/CD pipelines for AI/ML deployments within a regulated banking environment. You will deploy LLMs from Hugging Face, containerise apps with Docker, and manage Kubernetes/OpenShift clusters across development, UAT, and production stages.

You will collaborate with AI engineers, data scientists, and security teams to implement IaC with Terraform/Ansible, monitor health with Prometheus/Grafana, and