AI Platform Engineer

About the role

The AI Platform Engineer supports the implementation and lifecycle management of assigned agent services on Central AI Kitchen. The role contributes to secure, governed connectivity between AI agents, enterprise tools, APIs and data services, working across AI, infrastructure, cybersecurity, architecture and application teams. It supports the Lead AI Platform Engineer and development teams in delivering trusted agent identities, secure interactions and enterprise agent registry capabilities.

Key responsibilities

• Support implementation and lifecycle management of assigned agent services on Central AI Kitchen
• Implement and operate MCP servers and MCP gateway capabilities
• Support implementation of agent identity and authentication capabilities
• Implement and operate components of the enterprise agent registry
• Implement security controls for authentication, authorisation, secrets management, tool access and least-privilege execution by AI agents
• Perform testing, troubleshooting, defect resolution, deployment and operational support for assigned platform services
• Maintain technical documentation, deployment configurations, test cases, operating procedures and knowledge articles
• Work with internal staff, offshore engineers, vendors and other platform teams to support delivery and operation

Required profile

• Bachelor's degree in Computer Science, Engineering or a related field
• 2-4 years of experience in software engineering, platform engineering, cloud-native infrastructure, DevOps or data and AI platform roles
• Experience developing, deploying or integrating APIs, microservices or distributed application services
• Experience with source control, CI/CD and structured software delivery practices
• Ability to work independently on assigned tasks with guidance from senior engineers, and willingness to document work and share knowledge

Required skills

• Hands-on experience with Red Hat OpenShift, Kubernetes or equivalent container platforms
• REST APIs, API gateways, service-to-service communication and distributed system integration
• Enterprise identity and security concepts: OAuth2, OIDC, RBAC, service identities and secrets management
• GenAI and AI agent architectures, including agents, tools, models and APIs
• Git, GitOps, CI/CD and Infrastructure-as-Code practices
• Observability: logging, metrics, tracing and operational monitoring
• Cybersecurity principles: least privilege, credential management, authentication and authorisation

The position is on-site in Singapore; interested candidates should apply through the recruiter with an updated CV.