Principal AI Engineer
Tasks
- Architect AI infrastructure on GCP and AWS
- Architect retrieval pipelines with unstructured and structured data
- Build answer generation and grounding strategies
- Create question routing and data classification logic
- Define MLOps standards with versioning and deployment gates
- Design and build RAG pipelines
- Develop model quality frameworks
- Ensure HIPAA compliance for PHI handling and audit logging
- Establish confidence scoring and auto acceptance thresholds
- Implement citation backed answer validation
- Implement drift monitoring and audit trails
- Implement human-in-the-loop workflows
- Integrate large language models
- Mentor engineers on RAG and responsible AI
- Own end to end AI technical vision
- Run evals for accuracy and regression detection
- Set hallucination detection and factual grounding guardrails
Perks/Benefits
Skills/Tech-stack
AWS Bedrock | Artificial Intelligence | Audit Logging | BigQuery | CI/CD | Code review | Continuous integration | Data Deidentification | Dataflow | Deployment gates | Drift monitoring | Embedding Models | FHIR | HIPAA | HL7 | Human-in-the-loop | Hybrid search | Langchain | Language Models | Language Processing | Large Language Models | Llamaindex | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | PGVector | PHI handling | Pinecone | Prompt Revision | Prompt engineering | Python | Retrieval-Augmented Generation | Rollback procedures | Testing | The Loop | Vector Databases | Vertex AI | Weaviate
Education
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
Regions
Countries
States
Cities
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