Engineering Manager, AI & LLM Systems (Production)

asus global pte. ltd.

Singapore

On-site

SGD 180,000 - 280,000

Full time

3 days ago
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Job summary

AICS is seeking an Engineering Manager in Singapore to lead a skilled team of ML engineers building production-ready LLM applications and AI infrastructure. You will shape engineering workflows, ensure high-quality AI systems, and drive adoption of agentic AI capabilities.

Experience delivering AI products to production and strong leadership are essential to drive collaboration across AI Research, Product, and Software teams.

Qualifications

  • 8+ years of software engineering, machine learning engineering, or AI engineering experience.
  • 3+ years leading technical engineering teams.
  • Proven experience delivering AI products into production.

Responsibilities

  • Lead and grow a high-performing Machine Learning Engineering team.
  • Drive the design, development, and deployment of production LLM applications and AI systems.
  • Build scalable AI engineering workflows covering model evaluation, experimentation, deployment, and continuous improvement.
  • Lead the development of agentic AI capabilities, including multi-agent workflows, tool integration, memory, and orchestration.
  • Establish engineering best practices for AI development, software quality, testing, and MLOps.
  • Work closely with AI Research, Product, and Software Engineering teams to translate research into production products.
  • Continuously evaluate emerging AI technologies and adopt new techniques that improve product quality and engineering productivity.

Skills

LLMs & GenAI
Team leadership
Production AI deployment
MLOps practices

Tools

PyTorch
Hugging Face
Docker
Kubernetes
Azure or GCP

Job description

AICS is seeking an Engineering Manager in Singapore to lead a skilled team of ML engineers building production-ready LLM applications and AI infrastructure. You will shape engineering workflows, ensure high-quality AI systems, and drive adoption of agentic AI capabilities.

Experience delivering AI products to production and strong leadership are essential to drive collaboration across AI Research, Product, and Software teams.

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