#SGunited Jobs AI Platform Engineer

Job SummarySupport the implementation and management of AI platform infrastructure using container technologies and automation tools to enable scalable, secure, and efficient AI/data platform operations.ResponsibilitiesSupport implementation of AIDA’s AI Platform on RE:AI’s IaaS using Red Hat OpenShift or equivalent container platforms to ensure stable and scalable deploymentIntegrate core platform components including API Gateway, RAG pipelines, agent orchestration, and observability stacks to enable seamless platform functionalityAssist in deployment and management of OpenShift clusters (CPU/GPU), including configuring operators, networking, and security settings to maintain cluster health and securityAutomate platform provisioning and operations using Infrastructure-as-Code (IaC), CI/CD pipelines, and standardized deployment patterns to improve deployment efficiency and consistencyIntegrate platform capabilities with enterprise infrastructure such as networking, storage, load balancers, and backup systems to ensure robust platform connectivity and data protectionImplement platform security controls including IAM/AD, SIEM, NGFW, and EDR aligned with enterprise security standards to safeguard platform integritySupport AI/ML workloads including GenAI, LLM serving, RAG pipelines, and agentic frameworks to optimize AI platform performanceContribute to platform monitoring, logging, performance tuning, and capacity planning to maintain operational excellence and scalabilityRequired competencies and certificationsBachelor’s degree in Computer Science, Engineering, or a related fieldMinimum 3 years of experience in platform engineering, cloud-native infrastructure, or AI/data platform rolesHands-on experience with Kubernetes/OpenShift including operators, networking, and security configurationFamiliarity with Infrastructure-as-Code (IaC) and DevOps/CI/CD practicesBasic understanding of cloud/IaaS networking and security principlesPreferred competencies and qualificationsExposure to AI/ML platform components such as LLMs, RAG, or similar frameworksRed Hat, Kubernetes, or OpenShift certifications