Software Principal Engineer AI Empowered

Dell Global BV Singapore Branch (7032); Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

A leading technology company in Singapore is seeking a Software Principal Engineer (AI Empowered) to lead the design and development of AI platforms. The role requires a Master's degree in Computer Science and 5+ years in software engineering. Key responsibilities include architecting AI solutions, developing automation frameworks, and mentoring other engineers. Strong programming skills in Python, Go, or Java, and hands-on experience with containerization technologies like Kubernetes and Docker are essential in this innovative role.

Qualifications

• 5+ years in software engineering or platform development.
• Hands-on experience with containerization and orchestration.
• Familiarity with LLM ecosystems and ML infrastructure.

Responsibilities

• Design, develop, and operate core AI platform components.
• Implement and manage LLM tooling and prompt engineering frameworks.
• Troubleshoot complex issues across infrastructure and application layers.

Skills

Python

Go

Java

CI/CD

DevOps practices

AI-assisted development tools

Education

Master’s degree in Computer Science or related field

Tools

Kubernetes

Docker

OpenShift

Ansible

Terraform

Helm

Job description

Software Principal Engineer (AI Empowered)

The Software Engineering team delivers next‑generation application enhancements and innovative products for a rapidly evolving world. Working at the cutting edge, we design and develop software for platforms, peripherals, applications, and diagnostics—leveraging advanced technologies, modern engineering methodologies, and close collaboration with internal and external partners.

Join us to do the best work of your career and make a profound social impact as a Software Principal Engineer (AI Empowered) on our Software Engineering team in Singapore.

What You’ll Achieve

As a Software Principal Engineer (AI Empowered), you will be a key hands‑on leader who architects, builds, and operationalizes AI platforms and accelerates engineering through AI‑assisted development. You’ll develop core infrastructure for AI workloads (LLMs, agentic systems, data/ML pipelines) and embed AI tools across the engineering lifecycle to uplift speed, quality, and innovation across Dell’s solution platforms.

You will:

Design, develop, and operate core AI platform components: MLOps pipelines, data handling, model serving, and observability.

Implement and manage LLM tooling and prompt engineering frameworks; define reusable patterns for agents and retrieval workflows (e.g., vector databases).

Deploy and maintain scalable compute environments on Kubernetes/OpenShift, VxRail, ensuring high availability, performance, and cost efficiency for AI workloads.

Troubleshoot complex issues across the stack—from infrastructure and networking to runtime and application layers; contribute to technical documentation and platform best practices.

Optimize GPU scheduling, resource management, and model runtime performance in containerized environments.

AI‑Assisted Application Engineering

Drive adoption of AI‑assisted development tools (e.g., code generation, intelligent testing, automated documentation) and integrate LLM‑based services into engineering workflows.

Build and maintain automation frameworks and CI/CD pipelines that leverage AI for code quality, security scanning, and performance optimization.

Collaborate with platform engineers and product teams to embed AI capabilities into solution platforms (e.g., OpenShift, VxRail, VMware ecosystem).

Develop reference implementations, guardrails, and best practices for AI‑assisted engineering across multiple product teams.

Mentor engineers in effective use of AI tools to improve productivity while maintaining high‑quality standards; evaluate emerging AI technologies and recommend adoption strategies.

Qualifications

Master’s degree in Computer Science or related field, with 5+ years in software engineering or platform development.

Strong programming skills in Python, Go, or Java; solid CS fundamentals and hands‑on experience with containerization and orchestration (Docker, Kubernetes, OpenShift).

Experience building/managing ML or high‑performance computing infrastructure; familiarity with LLM ecosystems (e.g., LangChain, vector databases).

Proficiency with CI/CD, DevOps practices, and enterprise software delivery.

Experience with AI‑assisted development tools (e.g., GitHub Copilot, CodeWhisperer) or integrating LLM services into engineering workflows.

Experience with VMware technologies (vSphere, Tanzu) and Dell platforms (VxRail, PowerStore) and knowledge of GPU resource management in containerized environments.

Familiarity with hyper‑converged infrastructure (HCI), enterprise storage, and network virtualization (e.g., VMware NSX) and hands‑on experience with infrastructure automation tools (Ansible, Terraform, Helm).