Principal AI Engineer
Tasks
- Apply linting typing formatting and reproducible builds
- Build production APIs and services
- Define AI platform patterns
- Design and build production systems in Python
- Design cloud-native, event-driven systems
- Develop unit, integration and end-to-end tests
- Implement RAG embeddings prompting and guardrails
- Implement authentication authorization secrets management and policy enforcement
- Implement data persistence and schema migrations
- Integrate agent tooling and coordination patterns
- Mentor engineers and raise technical bar
- Own reliability testing CI CD and operational standards
- Provide technical leadership and influence roadmap priorities
- Set technical direction across teams
Perks/Benefits
- Career advancement
- Employee recognition
- LinkedIn Learning Platform
- Open PTO
- Paid parental leave
- Professional development opportunities
- Remote work
Skills/Tech-stack
AWS | Agent Orchestration | Authentication | Authorization | CI/CD | Containerization | Data Modeling | Embeddings | End to End | End-to-End Testing | Formatting | Infrastructure as Code | Integration Testing | LLM guardrails | Linting | MCP | Observability | Orchestration | Policy enforcement | Prompting | Python | RAG | REST APIs | Reproducible Builds | Schema migration | Secrets management | Typing | Unit Testing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
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