Senior RAG Engineer
Tasks
- Build retrieval evaluation methodologies
- Design scalable retrieval augmented generation architectures
- Develop knowledge ingestion and indexing frameworks
- Develop scalable APIs and retrieval services
- Establish retrieval standards and best practices
- Evaluate emerging retrieval technologies
- Implement retrieval integration with LLMs
- Implement security controls and data governance
- Lead RAG platform design
- Maintain technical documentation
- Mentor engineers
- Monitor platform performance and availability
- Optimize retrieval quality and performance
- Perform root cause analysis
- Recommend platform architecture enhancements
Perks/Benefits
- N/A
Skills/Tech-stack
AI Deployment | AI Deployment Pipelines | APIs | Backend Development | Cause analysis | Cloud infrastructure | Data Governance | Deployment Pipelines | Distributed Computing | Embeddings | Indexing | Information Retrieval | Knowledge Management | Knowledge ingestion | LLM integration | Language Models | Large Language Models | MLOps | Performance optimization | Python | Retrieval-Augmented Generation | Root Cause Analysis | Root cause | Security controls | Semantic Search | Vector Databases | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Engineer | RAG Engineer | Senior RAG Engineer | Software Engineer
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