AVP, Platform & AI Infrastructure Engineer, Group Infrastructure & Cloud, Group Technology

DBS · Singapore

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Business Function

Group Technology and Operations enables and empowers the Bank with an efficient, nimble, and resilient infrastructure through a focus on productivity, quality and control, technology, people capability, and innovation.

Responsibilities

• Develop, deploy, and support cloud-native applications, microservices, and APIs using Java and Spring Boot.
• Collaborate with engineering, security, operations, and AI teams to deliver scalable, secure, and reliable platform solutions.
• Build and maintain CI/CD pipelines, containerized workloads, and Kubernetes-based platforms.
• Support cloud environments across AWS, Azure, and/or GCP.
• Monitor platform health, troubleshoot production issues, and contribute to operational excellence initiatives.
• Assist in the deployment and operation of AI/ML infrastructure, GPU clusters, and model serving platforms.
• Implement observability and monitoring capabilities using tools such as Prometheus, Grafana, ELK, and OpenTelemetry.
• Participate in system integration, performance optimization, automation, and continuous improvement activities.
• Contribute to technical documentation, knowledge sharing, and agile delivery practices.

Requirements

• Strong experience in Software Engineering, Platform Engineering, DevOps, Cloud Infrastructure, or related disciplines.
• Proficiency in Java, Spring Boot, microservices architecture, and RESTful APIs.
• Understanding of event-driven architectures, system integration, and secure coding practices.
• Experience with relational databases such as PostgreSQL, MariaDB, or SQL Server.
• Hands-on experience with Docker, Kubernetes, and CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
• Familiarity with AWS, Azure, and/or GCP cloud platforms.
• Experience with monitoring and observability tools.
• Exposure to Site Reliability Engineering (SRE) principles and production support.

Preferred Skills

• Exposure to AI/ML platforms, GPU infrastructure, or NVIDIA technologies.
• Familiarity with Large Language Models (LLMs), Generative AI, MLOps, or RAG architectures.
• Experience with GPU-enabled environments, NVIDIA DGX, HPC, or hybrid-cloud deployments.
• Knowledge of Infrastructure-as-Code and automation tools.

What We're Looking For

• Strong individual contributor with a hands-on engineering mindset.
• Collaborative team player who works effectively across cross-functional teams.
• Self-driven, proactive, and eager to learn new technologies.
• Strong problem-solving and troubleshooting skills.
• Passion for cloud, platform engineering, AI infrastructure, and emerging technologies.

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