Staff Agentic AI Engineer
Tasks
- Add guardrails and escalation mechanisms
- Analyze prompt and retrieval quality
- Build RAG solutions
- Build production AI agent systems
- Create embedding based solutions
- Deploy scalable Python services to cloud
- Design AI agent platforms
- Develop LLM evaluation frameworks
- Develop knowledge modeling systems
- Diagnose latency and cost issues
- Implement retrieval systems
- Monitor production agent performance
- Optimize agent workflows
- Perform regression testing for LLMs
- Run LLM as judge workflows
Perks/Benefits
- Continuous learning opportunities
- Employee benefits
- Flexible work hours
- Inclusive workplace culture
- Professional growth
- Remote-friendly
Skills/Tech-stack
AWS | Cloud deployment | Embeddings | Guardrails | Information Retrieval | Knowledge graphs | LLM Evaluation | LLM orchestration | Langchain | Langgraph | Language Models | Language Processing | Large Language Models | Machine Learning | Memory systems | Natural Language | Natural Language Processing | Prompt engineering | Python | Regression testing | Retrieval-Augmented Generation | Tool use | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | Staff AI Engineer
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