Senior AI Infrastructure Architect & MLOps Lead

A*STAR - Agency for Science, Technology and Research; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

A*STAR, Singapore’s leading public sector R&D agency, seeks a Senior AI Scientist to lead design, implementation and scaling of AI infrastructure. You will bridge data science and software engineering by building robust pipelines and lifecycle practices.

You will architect multi-agent workflows, define the tech stack, design collaboration frameworks, and partner with the AI Safety team to ensure secure, private systems while measuring effectiveness.

Qualifications

• 6+ years in Software Engineering, Platform Engineering, or DevOps, with 3+ years in MLOps/AI infrastructure in production.
• Architected end-to-end ML platforms beyond single-model deployments.
• Proficient in Python and one high-performance backend language (Go, C++, Rust, or Java).
• Hands-on with cloud-native architectures (AWS, GCP, or Azure) and containerization/orchestration (Docker, Kubernetes, Helm).

Responsibilities

• Architect scalable, autonomous multi-step agentic workflows delivering real-world value.
• Own the stack by defining the tech stack and integrating tools for diverse, high-impact use cases.
• Design advanced multi-agent communication frameworks, memory management, and context pipelines.
• Partner with AI Safety to build secure, private, robust systems and mitigate semantic drift.
• Set up rigorous evaluation and benchmarking to prove effectiveness of autonomous systems.

Skills

Software engineering

Platform engineering

DevOps

MLOps

AI infrastructure

Python

Go

C++

Rust

Java

Cloud platforms

Docker

Kubernetes

Helm

Tools

Docker

Kubernetes

Helm

AWS

GCP

Azure

Job description

A*STAR, Singapore’s leading public sector R&D agency, seeks a Senior AI Scientist to lead design, implementation and scaling of AI infrastructure. You will bridge data science and software engineering by building robust pipelines and lifecycle practices.

You will architect multi-agent workflows, define the tech stack, design collaboration frameworks, and partner with the AI Safety team to ensure secure, private systems while measuring effectiveness.