AI Platform Engineer
Tasks
- Add rollback mechanisms
- Add tool access controls
- Build AI evaluation layer
- Build and manage AI agent portfolio
- Build data pipelines
- Build platform tooling validators compilers and context distribution
- Build scalable AI agent runtime
- Create AI adoption reporting
- Create CI gates for AI quality
- Create golden test suites
- Create human approval workflows
- Create human review workflows
- Design AI execution platform
- Design responsible notification systems
- Develop run logging
- Enable audit logging
- Enforce least privilege permissions
- Enhance AI platform continuously
- Implement durable state management
- Implement platform governance
- Implement safety checks
- Instrument AI workflows usage efficiency costs and value
- Integrate across repositories
- Monitor agent performance
- Own AI production architecture
- Restrict high risk actions
Perks/Benefits
- Annual company offsite
- Annual professional development budget
- Coworking allowance
- Dependent coverage support
- Employee equity ownership
- Fully remote
- Health insurance
- Remote-first culture
- Technology allowance
Skills/Tech-stack
API Integration | Access Control | Audit Logging | Automated testing | CI/CD | Cloud Data | Cloud Data Warehouse | Cloud Dataflow | Cloud platform | Cost Tracking | Data Warehouse | Evaluation Methodologies | Event Driven | Event-driven architecture | GCP Cloud | GCP Cloud Dataflow | Golden datasets | Google Cloud | Google Cloud Platform | Human-in-the-loop | Infrastructure as Code | LLM Observability | Permissions Management | Python | Safety testing | Security | The Loop | Tracing | “as-code”
Education
N/A
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