Principal AI Engineer
Tasks
- Architect graph based agent workflows
- Build FastAPI applications
- Build and deploy autonomous agent systems
- Build evaluation frameworks for agents
- Build hybrid intelligence patterns
- Design RESTful API architectures
- Design event driven API architectures
- Design multi-agent workflows
- Develop response transformation pipelines
- Develop reusable agent node libraries
- Ensure data governance compliance
- Implement LDAP and SSO integration
- Implement Responsible AI standards
- Implement SSE streaming
- Implement WebSocket communication
- Implement access control
- Implement conversation state persistence
- Implement function calling
- Implement observability tracing telemetry
- Implement prompt management with versioning templating
- Implement tool calling protocols
- Implement unit, integration, and end-to-end testing
- Integrate Model Context Protocol
- Integrate PostgreSQL
- Integrate Redis
- Integrate cloud LLM providers
- Mentor junior engineers
- Optimize token usage and LLM costs
- Participate in architecture reviews
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Bedrock | Access Control | Anthropic Claude | Asyncio | Autogen | Azure | Azure OpenAI | CI/CD | CrewAI | Docker | End to End | End-to-End Testing | Event Driven | Event-driven architecture | FastAPI | Function Calling | GPT-4 | Git | Google Cloud | Integration Testing | LDAP | LLMOps | Langchain | Langfuse | Langgraph | Langsmith | Model Context Protocol | OpenAI GPT | OpenAI GPT-4 | Plan-and-Execute | PostgreSQL | Prompt engineering | Prompt templating | Python | REST | ReAct framework | React | Redis | SSE | SSO | Server Side | Server Side Events | Server-Sent Events | Token optimization | Unit Testing | WebSocket
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
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