Lead Research Engineer, ARTC

Key Responsibilities • Define manufacturing system workflows, data flows, and API contracts across platform components so the system scales cleanly from prototype to live manufacturing deployment. • Architect the end-to-end agentic AI platform on cloud-native infrastructure (e.g. AKS, Azure OpenAI, Foundry LLM models, API Management), shaped to manufacturing enterprise and shopfloor needs. • Design integration patterns between LLMs, knowledge graphs, vector databases, and reasoning engines within the agentic AI framework for manufacturing use cases. • Recommend technology stacks for on-premise and cloud deployments based on scalability, cost, security, and maintainability. • Lead architecture and system design reviews, set engineering standards, and mentor junior engineers on building and deploying agentic AI systems. • Identify high-value use cases and deliver agentic AI solutions across manufacturing operations (e.g. maintenance, quality, planning, scheduling, knowledge assistants). • Partner with AI scientists, engineers, domain experts, and industry stakeholders to turn manufacturing requirements into production-ready systems deployed on the shopfloor. Required Skills • Hands-on experience with digital manufacturing systems (MES, SCADA, historians, or equivalent shopfloor/enterprise platforms). • Experience designing distributed systems/cloud-native platforms (Azure, AWS, GCP). • Familiarity with AI/ML system integration: LLMs, agentic AI frameworks, APIs, vector search, and knowledge graphs. • Strong systems thinking; able to connect the dots across data, AI models, and manufacturing applications. • Good communicator who can align technical and non-technical stakeholders across R&D and industry. • Experience with software development, deployment, containerisation and orchestration tools (Docker, Kubernetes, AKS) with industrial systems. • Demonstrated passion for advancing agentic AI and knowledge-driven architectures in manufacturing. Qualifications • B. Eng/B. Sc/M. Sc in Computer Science, Software Engineering, or related field. • 6–10 years of experience, with at least 3 years in a systems or solution architecture role. The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.