Senior DevOps Engineer

About the Position

We are seeking a Senior DevOps Engineer for a leading Singapore-based financial institution to build, automate, and manage AI model deployment pipelines.

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.

Requirements

Must have

• 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 such as:
  • Ollama
  • NVIDIA Triton Inference Server
  • Text Generation Inference (TGI)
• Knowledge of REST APIs and microservices architecture.
• 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.

Nice to have

• Experience with LangChain, LangGraph, or AI Agent frameworks.
• Experience with Vector Databases (Pinecone, Milvus, Weaviate, OpenSearch, pgvector).
• Knowledge of Retrieval-Augmented Generation (RAG) architecture.
• Experience deploying Llama, Mistral, DeepSeek, Qwen, or other open-source LLMs.
• Experience with MLflow, Kubeflow, or other MLOps platforms.
• Familiarity with Kafka or RabbitMQ.
• Experience with API Gateway and service mesh technologies.
• Knowledge of security scanning tools such as Trivy, SonarQube, Checkmarx, or Snyk.
• Experience implementing DevSecOps practices.
• Agile/Scrum delivery experience.
• Previous experience within Banking, Capital Markets, or Financial Services.
• Experience supporting AI platforms in production environments.

We Offer

• Competitive salary
• Opportunity to work with cutting-edge AI technologies
• Collaborative and innovative work environment
• Professional development opportunities

About the Company

Our client is a leading Singapore-based financial institution embarking on an enterprise-wide AI transformation programme to accelerate the adoption of Generative AI across business and technology functions.

Application

Apply for Senior DevOps Engineer in Singapore.