VP AI Engineering
Tasks
- Architect and operate AI platform at scale
- Build CI CD pipelines for ML development
- Define career frameworks and growth paths
- Deploy and monitor machine learning models
- Detect model drift
- Develop AI governance policies and audit frameworks
- Ensure HIPAA CMS and state compliance
- Ensure model evaluation and continuous improvement
- Establish responsible AI standards
- Implement MLOps best practices
- Implement bias detection and model explainability
- Integrate AI models with health plan systems
- Manage model registry and versioning
- Mitigate technical and ethical AI risks
- Optimize AI infrastructure cost
- Own AI engineering platform architecture
- Recruit and develop AI engineering teams
- Report AI engineering progress to executives
- Run A B testing for AI models
- Set engineering KPIs and SLOs SLAs
Perks/Benefits
- Comprehensive wellness program
- Global travel health insurance
- Life and disability insurance
- Medical/dental/vision/life insurance
- Paid Holidays
- Paid time off
- Retirement savings plan
- Volunteer time off
- Well-being days
Skills/Tech-stack
AWS | Apache Airflow | Azure | Azure ML | CI/CD | CPT | Data Lakes | Drift Detection | FHIR | Flink | Google Cloud | HL7 | Hugging Face | ICD-10 | Java | Kafka | Kubeflow | Kubernetes | Langchain | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Monitoring | Model Registry | Prompt engineering | PyTorch | Python | RAG | SQL | SageMaker | Scala | TensorFlow | Vector Databases | Vertex AI
Education
Roles
AI | AI Engineering | AI Engineering Director | Director | Engineering | Engineering Director | Head | Head of AI | Head of AI Engineering | VP | VP, AI Engineering
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