Lead Research Engineer, Artc

Key Responsibilities Architect and lead development of enterprise-scale agentic AI systems and platforms Design AI orchestration workflows involving LLMs, tools, agents, and enterprise integrations Define scalable, secure, and reliable system architectures and engineering practices Collaborate with stakeholders to translate operational needs into AI-enabled solutions Evaluate and adopt emerging technologies related to agentic AI and enterprise AI systems Provide technical leadership and mentorship to engineering teams Requirements Degree in Computer Science, Software Engineering, or related fields Strong experience in software architecture, backend systems, or enterprise platform development Experience designing scalable cloud-native or distributed systems Familiarity with LLMs, AI application architectures, and orchestration frameworks Interest or experience in agentic AI systems, automation workflows, or multi-agent applications Strong communication, problem-solving, and stakeholder management skills Good to have Experience with cloud platforms such as Azure, AWS, or GCP Familiarity with Docker, Kubernetes, CI/CD pipelines, or MLOps practices Experience building AI-enabled enterprise applications, copilots, or intelligent automation solutions Exposure to AI governance, observability, or security considerations for AI systems Experience working with manufacturing, industrial systems, or enterprise digital transformation initiatives 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.