Principal Applied AI Engineer
Tasks
- Build long horizon agents with human judgment
- Build stateful agentic systems beyond RAG
- Contribute reusable AI patterns to core systems
- Create context engineering and self improving feedback loops
- Design and ship agentic AI systems
- Develop agent tools custom harnesses and execution sandboxes
- Evaluate agent failure modes using evals and context
- Implement observability and self learning loops
- Publish and open source AI learnings
- Source assess and support healthcare technology founders
- Teach organization how to build in an AI native world
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Frameworks | Agent SDK | Anthropic Agent SDK | Context engineering | Evals | Knowledge graphs | Langchain | Language Models | Large Language Models | Machine Learning | Observability | Python | Retrieval-Augmented Generation | Sandboxing | Semantic Search | TypeScript
Education
N/A
Regions
Countries
States
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