Lead AI Engineer, GenAI Platform & Cloud

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

Job summary

SATS Ltd, headquartered in Singapore, is hiring a Lead AI Engineer to design, build, and operate an enterprise GenAI platform. You will architect production-grade AI/ML systems, develop scalable pipelines, and manage cloud infrastructure across AWS/Azure/GCP.

Mentorship and architecture reviews form a meaningful part of the role as you lead a high-caliber team. Expected to deliver end-to-end AI capabilities, including RAG, vector storage, class-leading latency, and reliable tooling.

Qualifications

• Proven hands-on software engineering (10–12 years) in GenAI Platform Engineering or equivalent.
• Deep, hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
• Strong Python experience and hands-on expertise with Docker, Kubernetes, Terraform/IaC, CI/CD pipelines, MLflow.
• Hands-on experience building/running Agentic AI applications and tool-calling agents in production.
• Commitment to ongoing AI/ML training and familiarity with aviation-related cargo, ground handling, or food solutions.

Responsibilities

• Design and build scalable ML/GenAI pipelines (batch & real-time).
• Build and operate model-serving infrastructure and optimize inference latency.
• Develop RAG pipelines, LLM orchestration, multi-agent workflows, and vector DB infrastructure.
• Create and maintain the knowledge base and core AI platform components (API gateway, auth, tracing).
• Architect cloud infrastructure (AWS/Azure/GCP), write IaC, and craft end-to-end CI/CD for ML/GenAI workloads.
• Collaborate with data scientists to productionize models and guide cloud/vendor choices.

Skills

Python

Docker

Kubernetes

CI/CD pipelines

MLflow

Education

Bachelor/Master/PhD in CS or Math

Tools

AWS

Azure

GCP

Terraform/IaC

Job description

SATS Ltd, headquartered in Singapore, is hiring a Lead AI Engineer to design, build, and operate an enterprise GenAI platform. You will architect production-grade AI/ML systems, develop scalable pipelines, and manage cloud infrastructure across AWS/Azure/GCP.

Mentorship and architecture reviews form a meaningful part of the role as you lead a high-caliber team. Expected to deliver end-to-end AI capabilities, including RAG, vector storage, class-leading latency, and reliable tooling.