AI Engineer, Dev Ops
SGD 18K-27K (estimate) Mid-level Full Time
Tasks
- Align backup retention disaster recovery and data residency
- Analyze logs and metrics for root cause
- Automate deployment processes
- Build and maintain CI/CD pipelines
- Conduct blameless post-mortems
- Conduct vulnerability patching and audit logging
- Draft infrastructure as code
- Generate change reports and documentation using AI
- Generate runbooks using AI tools
- Implement observability with logs metrics traces and dashboards
- Implement preventive actions
- Maintain SLOs alerting policies and on call
- Maintain data lineage tooling
- Manage container build and registry workflows
- Manage data pipelines storage catalogues and access control
- Operate central data management infrastructure
- Operate data platform on GCP and AWS
- Perform incident triage and mitigation
- Perform secrets management and IAM hygiene
- Support security compliance and access reviews
- Use AI tools for incident triage and remediation
Perks/Benefits
- N/A
Skills/Tech-stack
AI tools | AI/ML | AI/ML evaluation | Access Control | Alerting | Amazon Web Services | Audit Logging | Backup and Retention | Bash | Benchmarking | CI/CD | Cloud platform | Cybersecurity | Data Annotation | Data Catalog | Data Lineage | Data Pipelines | Data Residency | Data Storage | Disaster Recovery | Distributed tracing | Docker | GDPR | Go | Google Cloud | Google Cloud Platform | IAM | ISO 27001 | Incident Response | Infrastructure as Code | Kubernetes | Least Privilege | Logging | ML evaluation | Monitoring | NIST | Network Security | OWASP | Observability | PDPA | Python | SLO | Secrets management | Terraform | Vulnerability Management | Web Services | “as-code”
Education
Roles
AI | AI Engineer | DevOps | DevOps Engineer | Engineer | Reliability Engineer | Site Reliability Engineer
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