AI Platform Engineer
Tasks
- Add tool access controls
- Build AI governance mechanisms
- Build data pipelines for AI reporting
- Build event triggered workflows
- Build golden test suites
- Build platform tooling
- Create audit logging
- Create behavioral evaluations
- Create context distribution systems
- Create human review processes
- Design AI execution platform
- Design responsible communication systems
- Develop AI evaluation layer
- Develop validators and compilers
- Enable human approval workflows
- Implement least privilege permissions
- Implement model agnostic runtimes
- Implement rollback mechanisms
- Implement safety checks
- Instrument AI workflow observability
- Integrate across repositories
- Manage durable state
- Own production AI agent architecture
- Restrict high risk AI actions by design
- Set up continuous integration gates
- Set up run logging
- Track usage efficiency and costs
Perks/Benefits
- Annual offsite gatherings
- Coworking support
- Dependent coverage support
- Employee equity ownership
- Flexible asynchronous work environment
- Fully remote
- Globally distributed team
- Health insurance
- Open source contributions
- Professional development budget
- Remote-first culture
- Technology allowance
Skills/Tech-stack
API Integration | Access Control | Audit Logging | Automation | CI Gates | Cloud Data | Cloud Data Warehouses | Continuous integration | Cost Tracking | Data Warehouses | Durable State | Evaluation | Event Driven | Event-driven architecture | GCP | Golden Dataset | Human-in-the-loop | Infrastructure as Code | LLM Observability | Language Models | Large Language Models | Least Privilege | Open Source | Python | Safety testing | Security | The Loop | Tracing | “as-code”
Education
N/A
Roles
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