AI Engineer
Tasks
- Add observability with logging and error tracking
- Audit existing automations for agent opportunities
- Build Anthropic Claude based agents
- Build MCP Connectors
- Build unit tests
- Create reviewer interfaces for one click approval
- Create test harnesses for agent behavior
- Design AI agent systems end to end
- Design event driven pipelines with retries and idempotency
- Develop audit logging in Airtable
- Develop integration tests for external APIs
- Develop prompts and rubrics with eval sets
- Document systems with README architecture notes and runbooks
- Implement AI upgrades to existing workflows
- Implement webhook receivers
- Maintain systems with documentation and runbooks
- Present proposals to tech lead
- Quantify workflow opportunity and write build proposals
- Upgrade Make Zapier GHL workflows with AI
- Write production code in JavaScript
- Write production code in Python
Perks/Benefits
- Autonomous time management
- Exclusive event access
- Flexible work hours
- Global community
- Networking opportunities
- Professional development
- Remote work flexibility
Skills/Tech-stack
API | Agent SDK | Airtable | Anthropic API | Anthropic Claude | Claude Code | ClickUp | Dead Letter Queue | Error Tracking | Git | Go High Level | Google Cloud | Google Workspace | Idempotency | Integration Testing | JavaScript | LLM Evaluation | Logging | MCP | Make | Model Context Protocol | Monitoring | Next.js | Node.js | Observability | Prompt engineering | Python | Retry logic | Slack | Test Harness | TypeScript | Unit Testing | Webhooks | Zapier
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Software Engineer
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