AI Platform Engineer (Cloud)
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Summary
Build and operate a secure, multi-cloud AI platform using Kubernetes, model-serving, and zero-trust controls while ensuring data residency and cost efficiency.
- Apply data loss prevention controls
- Build AI gateway configurations
- Build cost reporting dashboards
- Configure authentication and authorization
- Configure model-serving environments
- Deploy and operate AI platform services
- Design multi cloud AI infrastructure
- Enable agentic AI infrastructure
- Ensure data residency and sovereignty compliance
- Implement Kubernetes based AI workloads
- Implement infrastructure-as-code
- Implement platform observability and alerting
- Implement prompt injection prevention and output filtering
- Implement zero-trust security controls
- Maintain operational runbooks and procedures
- Manage AI workload portability
- Monitor and optimize AI platform costs
- Support incident response and root cause analysis