Applied AI Engineer
Tasks
- Build AI agents end to end
- Build evaluation harnesses
- Communicate with stakeholders on status and issues
- Deploy AI tools to production
- Detect regressions in deployed agents
- Handle logging and monitoring
- Integrate LLM APIs into workflows
- Integrate systems via APIs
- Maintain reusable components and documentation
- Manage authentication and rate limits
- Monitor quality metrics in production
- Run human reinforcement workflows
- Triage agent failures
- Tune agent behavior using feedback signals
Perks/Benefits
Skills/Tech-stack
API Integration | Authentication | Error Handling | Evaluation | HubSpot API | Jira API | LLM APIs | Language Models | Large Language Models | Logging | Monitoring | Prompt engineering | Python | Quality metrics | Rate Limiting | Regression testing | Slack API | Snowflake | Testing
Education
N/A
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Software Engineer
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