AI Platform Engineer
Tasks
- Build AI agent portfolio for business workflows
- Build durable state management and run logging
- Build platform tooling and repository integrations
- Create data pipelines and AI adoption reporting
- Create golden test suites and safety checks
- Design and build AI execution platform
- Design responsible notification and communication systems
- Develop AI evaluation layer
- Enable audit logging and human approval workflows
- Enforce least privilege access controls and tool access controls
- Implement CI gates for AI quality assurance
- Implement governance mechanisms and risk tiers
- Implement human review workflows and rollback mechanisms
- Instrument AI workflows for usage efficiency costs and ROI
- Monitor agent performance and identify improvements
- Own production architecture for AI agents
- Restrict high risk AI actions through system design
Perks/Benefits
- Annual offsite gatherings
- Coworking allowance
- Dependent coverage support
- Employee equity
- Flexible, asynchronous work
- Fully remote
- Health insurance
- Open source opportunities
- Professional development budget
- Remote-first culture
- Technology allowance
Skills/Tech-stack
APIs | Access Control | Agentic AI | Audit Logging | CI/CD | Cloud Computing | Cloud Data | Cloud data warehousing | Cloud platform | Cost Tracking | Data Pipelines | Data Warehousing | Durable State | Evaluation datasets | Event Driven | Event-driven architecture | Generative AI | Golden tests | Google Cloud | Google Cloud Platform | Infrastructure as Code | LLM Observability | LLM tracing | Language Models | Large Language Models | Least Privilege | Monitoring | Python | Role-Based Access | Role-Based Access Control | Safety testing | “as-code”
Education
N/A
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