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Lead Software/Data Infrastructure Engineer, Embodied AI Centre (EAIC)

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Summary

Lead the software and data infrastructure of Singapore's national Embodied AI Centre, setting technical direction and delivering platforms, APIs, data pipelines, storage and shared engineering systems for embodied AI research, evaluation and deployment, while managing a roadmap and mentoring engineers.

Singapore's Embodied AI Centre (EAIC) is a new national initiative under the RIE2030 Manufacturing, Trade and Connectivity domains to establish Singapore as a leading robotics and embodied AI hub. EAIC brings together research and industry partners to build engineering and R&D capabilities, advance trusted evaluation, benchmarking and validation of embodied AI models and robotics solutions, and promote an open and interoperable ecosystem that accelerates adoption in real-world applications.

As the Lead for Software/Data Infrastructure, you will set the technical direction and lead the delivery of EAIC's software platforms, data infrastructure and shared engineering systems. You will guide a multidisciplinary team in building reliable and scalable foundations for embodied AI research, experimentation, evaluation and deployment.

Job Description

Lead the architecture, development and delivery of EAIC software platforms, data infrastructure and shared engineering services.

Oversee full-stack applications, APIs, data pipelines, storage platforms, integrations and operational tooling.

Define engineering standards for software development, data quality, testing, security, deployment, observability and documentation.

Partner with AI/robotics and hardware teams to define system interfaces and enable reliable data flow across the embodied AI lifecycle.

Manage the technical roadmap, priorities, resources and delivery risks across software and data infrastructure workstreams.

Mentor software and data engineers and strengthen engineering capability within the team.

Job Requirements

Demonstrated experience designing, building and operating production-grade software platforms or data-intensive systems.

Strong software engineering foundation, with experience in scalable APIs, databases, data pipelines and system architecture.

Experience leading multidisciplinary engineering projects, technical workstreams or software/data infrastructure teams.

Ability to translate research, operational and stakeholder needs into practical technical roadmaps and integrated solutions.

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