Principal AI Engineer
Tasks
- Add safety guardrails and access control
- Build and operate MCP servers
- Create embedding and vector retrieval pipelines
- Define orchestration and retrieval evaluation
- Define tool surface strategy
- Design AI orchestration layers
- Design multi agent patterns
- Develop abstraction layers and platform APIs
- Establish observability and tracing
- Implement RAG retrieval systems
- Implement memory strategies for agent workflows
- Manage routing and context windows
- Mentor engineers
- Onboard product team tools and agents
Perks/Benefits
- N/A
Skills/Tech-stack
Access Control | Agentic Workflows | Authentication | Chunking | Context Assembly | Context window | Context window management | Embeddings | Evaluation | Function Calling | Hybrid search | Keyword search | LLM orchestration | Langgraph | Llamaindex | Model Context Protocol | Observability | Prompt engineering | Python | Re-ranking | Retrieval-Augmented Generation | Routing | Semantic Kernel | Tracing | Vector Databases | Window management
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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