Engineering Manager – AI Engineering & LLM Systems

ASUS; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

ASUS’ AICS unit is seeking an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.

You will drive design, development, and deployment of AI systems, establish MLOps practices, and advance agentic AI capabilities, memory, and tool integration while collaborating with AI Research, Product, and Software Engineering teams. This role requires 8+ years in software/ML and 3+ years leading teams.

Qualifications

• 8+ years of software/ML/AI engineering experience.
• 3+ years leading technical engineering teams.

Responsibilities

• Lead and grow a high-performing Machine Learning Engineering team.
• Drive 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

ML engineering

Team leadership

LLMs

RAG retrieval

PyTorch

Hugging Face

MLOps

Tools

PyTorch ecosystem

Hugging Face

MLOps tools

Job description

AICS builds Healthcare AI solutions that improve clinical workflows through large language models, agentic AI, and modern AI engineering.

We are looking for an Engineering Manager to lead a team of Machine Learning Engineers building production-ready LLM applications, AI infrastructure, and clinical AI systems.

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.

Qualifications

Required Experience

• 8+ years of software engineering, machine learning engineering, or AI engineering experience.
• 3+ years leading technical engineering teams.

Technical Expertise

Candidates should have practical, hands-on experience with most of the following:

• Large Language Models (LLMs) and Generative AI application development
• Model fine-tuning or adaptation for domain-specific use cases
• LLM evaluation and benchmarking
• RAG and knowledge retrieval systems
• Agentic AI frameworks and workflow orchestration
• Prompt engineering and structured tool calling
• PyTorch and Hugging Face ecosystem
• AI deployment, inference optimization, and MLOps