Top AWS Jobs in Singapore

Serve as a Technical Account Manager Architect supporting strategic enterprise customers: provide architectural and migration guidance, lead onboarding and escalations, own L3 support cases, coordinate projects and roadmap with Product/Engineering/Sales, mentor teammates, produce docs and reference architectures, and perform onsite regional customer visits (up to ~35%).

The Senior AI Engineer will develop a retrieval layer for enterprise AI agents, ensuring relevant, permission-aware responses by integrating multiple data sources and designing hybrid retrieval systems. Responsibilities include mentoring, designing pipelines, and building evaluation systems, with a strong focus on retrieval quality and permission management.

Lead design and delivery of Generative AI solutions using Amazon Bedrock and orchestration frameworks. Build CI/CD pipelines, manage full-stack AWS infrastructure, ensure observability and AI governance, collaborate with stakeholders, apply Agile practices, mentor engineers, and integrate new AI innovations into production systems.

Lead the development of AI tools that optimize the software development lifecycle, mentor teams, and implement scalable ML systems.

The Senior Data Scientist will develop AI/ML models for dynamic pricing, automate model processes, build monitoring dashboards, and present findings.

The Principal Software Engineer will develop AI tools to enhance developer productivity and manage AI project execution across teams.

Collaborate with teams to develop AI tools for enhancing software development efficiency, mentor engineers, and manage AI projects across Grab.

As a Senior Software Engineer, you will design and implement backend components, improve service reliability, mentor colleagues, and integrate AI solutions in collaboration with other teams.

Lead the development of AI-driven software solutions, enhance engineering productivity, manage AI project execution, and mentor junior engineers.

Design and maintain scalable data platforms on AWS and Databricks, focusing on efficient data processing, analytics, and orchestration of pipelines.