#Sgunited Jobs AI Platform Engineer

Job Summary Support the implementation and management of AI platform infrastructure using container technologies and automation tools to enable scalable, secure, and efficient AI/data platform operations. Responsibilities Support implementation of AIDA’s AI Platform on RE:AI’s IaaS using Red Hat OpenShift or equivalent container platforms to ensure stable and scalable deployment Integrate core platform components including API Gateway, RAG pipelines, agent orchestration, and observability stacks to enable seamless platform functionality Assist in deployment and management of OpenShift clusters (CPU/GPU), including configuring operators, networking, and security settings to maintain cluster health and security Automate platform provisioning and operations using Infrastructure-as-Code (IaC), CI/CD pipelines, and standardized deployment patterns to improve deployment efficiency and consistency Integrate platform capabilities with enterprise infrastructure such as networking, storage, load balancers, and backup systems to ensure robust platform connectivity and data protection Implement platform security controls including IAM/AD, SIEM, NGFW, and EDR aligned with enterprise security standards to safeguard platform integrity Support AI/ML workloads including GenAI, LLM serving, RAG pipelines, and agentic frameworks to optimize AI platform performance Contribute to platform monitoring, logging, performance tuning, and capacity planning to maintain operational excellence and scalability Required competencies and certifications Bachelor’s degree in Computer Science, Engineering, or a related field Minimum 3 years of experience in platform engineering, cloud-native infrastructure, or AI/data platform roles Hands-on experience with Kubernetes/OpenShift including operators, networking, and security configuration Familiarity with Infrastructure-as-Code (IaC) and DevOps/CI/CD practices Basic understanding of cloud/IaaS networking and security principles Preferred competencies and qualifications Exposure to AI/ML platform components such as LLMs, RAG, or similar frameworks Red Hat, Kubernetes, or OpenShift certifications