AI Platform Engineer
Tasks
- Build AI agent portfolio
- Build data pipelines for AI adoption reporting
- Build event triggered workflows
- Build responsible notification systems
- Control tool access
- Create golden test suites
- Create human approval workflows
- Create human review workflows
- Create platform tooling validators compilers and context distribution
- Design AI execution platform
- Develop AI evaluation layer
- Develop repository integrations
- Develop rollback mechanisms
- Enforce least privilege permissions
- Implement audit logging
- Implement durable state management
- Implement platform governance mechanisms
- Implement safety checks
- Instrument AI workflows usage efficiency cost and value tracking
- Maintain run logging
- Monitor agent performance
- Own production architecture decisions
- Restrict high risk AI actions
- Set CI gates for quality
Perks/Benefits
- Annual offsite gathering
- Dependent coverage support
- Employee equity ownership
- Flexible asynchronous work environment
- Fully remote
- Global team collaboration
- Health insurance
- Open source contributions
- Professional development budget
- Remote-first culture
- Technology allowance
- WeWork coworking support
Skills/Tech-stack
AI Evaluation | API Integration | Access Control | Audit Logging | CI/CD | Cloud Data | Cloud Data Warehouses | Cost Tracking | Data Warehouses | Event Driven | Event-driven architecture | GCP | Golden datasets | Infrastructure as Code | LLM | LLM Observability | Language Models | Large Language Models | Least Privilege | Open Source | Permissions Management | Python | Role-Based Access | Role-Based Access Control | Safety testing | Security | Tracing | “as-code”
Education
N/A
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