Engineer / Senior Engineer, AI Platform

At DSTA CIO Office, we drive the delivery of secure, scalable and enterprise-grade AI capabilities that empower the digital transformation of DSTA. As part of our team, you will play a key role in building, operating and optimising the enterprise AI platforms and services that enable AI adoption across the organisation.

You will work at the intersection of AI engineering, cloud and platform operations, GPU infrastructure, and enterprise technology strategy to deliver resilient and high-performance AI capabilities for the organisation. Join us in shaping the foundation for enterprise AI adoption, and achieve your potential in an environment that fosters growth, learning and innovation.

Opportunity

We are seeking an AI Engineer to join our CIO Office Data/AI Platform team, where you will work alongside engineers, architects and AI practitioners to build and sustain enterprise AI services and platforms. We are looking for forward-thinking individuals who are passionate about operationalising AI at scale and enabling impactful AI adoption across the enterprise.

Your work will directly contribute to the deployment, optimisation and management of enterprise AI platforms, including large language models (LLMs), retrieval-augmented generation (RAG) services, AI agent orchestration platforms and GPU-enabled AI infrastructure.

Key Responsibilities:

• AI Platform Engineering & Operations: Design, deploy and sustain enterprise-grade AI platforms and common AI services, including LLM hosting, inference services, embedding services and AI agent orchestration platforms.
• Model Deployment & Optimisation: Deploy, optimise and manage AI models across on-premise and cloud environments. Improve model inference performance, throughput and resource utilisation through continuous monitoring, observability and optimisation techniques such as quantization, vLLM, batching etc.
• GPU Infrastructure & Resource Management: Manage and optimise GPU infrastructure and compute resources to ensure efficient allocation, scalability and high utilisation across enterprise AI workloads. Support capacity planning, workload scheduling and performance monitoring for AI systems.
• AI Service Enablement: Enable enterprise-wide adoption of AI capabilities by developing reusable APIs, SDKs, templates and shared services that simplify AI integration and accelerate solution delivery across teams, while maintaining AI security and compliance within the organisation.
• Agentic AI & Orchestration: Deploy and manage AI orchestration platforms and frameworks that support agentic workflows, multi-agent systems, tool integration and enterprise AI automation capabilities.
• Continuous Innovation: Stay abreast of emerging developments in Generative AI, AI infrastructure, model optimisation and agentic AI technologies. Evaluate, prototype and introduce new technologies and approaches to enhance enterprise AI capabilities.

Requirements

• Driven with a strong foundation from, but not limited to, Computer Science, Computer Engineering, Information Systems, AI/ML or related disciplines.
• At least 2 years of practical experience in deploying, managing and optimising AI and agent orchestration platformsin regulated on-premise environments, including but not limited to GPU infrastructure, Kubernetes, vector databases, and common AI services (e.g. LLMs, agents, tools), with strong software engineering and infrastructure fundamentals.
• Strong interest and familiarity in enterprise AI platforms, LLM deployment, GPU infrastructure, AI operations and scalable AI service delivery.
• A resourceful and adaptable self-starter who thrives in a fast-evolving technology landscape and enjoys solving complex operational and engineering challenges.
• An eager learner who is committed to continuously upskilling in emerging AI technologies, infrastructure platforms and engineering best practices.
• Ability to influence and contribute to technical discussions, platform strategy and enterprise AI adoption initiatives through effective communication and technical expertise.