Applied AI Engineer
Tasks
- Add observability logging monitoring error tracking
- Build LLM-powered applications
- Containerize services with Docker
- Create RESTful APIs and webhooks
- Deploy applications to Google Cloud
- Design AI automation solution
- Develop autonomous agent workflows
- Implement rag pipelines
- Implement secure authentication patterns
- Integrate LLM APIs
- Research business workflow friction
- Set up CI/CD pipelines
- Ship production improvements with measurable impact
- Validate and evaluate agent outputs
Perks/Benefits
- Employee stock option plan
- Flexible working options
- Health insurance
- Home-office allowance
- Parental leave
- Peer recognition program
- Professional development stipend
- Unlimited vacation
Skills/Tech-stack
AI Agents | Agentic Architectures | Authentication | CI/CD | Cloud Run | Cloud platform | Docker | Error Tracking | Firebase | Firestore | Git | GitHub | Google Cloud | Google Cloud Platform | IAM | JavaScript | LLM APIs | Logging | MCP | Model Context Protocol | Monitoring | Multimodal LLMs | Next.js | Observability | Prompt engineering | Pub/Sub | Python | RAG | REST APIs | TypeScript | Webhooks
Education
N/A
Roles
AI Engineer | Applied AI Engineer | Engineer | Software Engineer
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