Senior AI Architect
Tasks
- Assess model risk and cybersecurity posture
- Conduct subsystem AI architecture reviews
- Create AI design review practices
- Define LLMOps requirements
- Define MLOps requirements
- Define enterprise AI reference architectures
- Define retraining governance
- Design deployment automation
- Develop reusable AI solution patterns
- Establish AI architecture standards
- Evaluate enterprise platform integration options
- Implement AI assisted workflows for validation
- Implement drift detection
- Implement model performance monitoring
- Integrate AI into engineering standard work and QMS
- Maintain architecture decision records
- Mentor embedded AI architects
- Provide technical escalation for complex AI initiatives
- Support AI governance technical assessments
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic Workflows | Amazon Web Services | Artificial Intelligence | Cloud Computing | Cloud platform | Computer Vision | Data Pipelines | Deep learning | Drift Detection | Generative AI | Google Cloud | Google Cloud Platform | LLMOps | Language Processing | MLOps | Machine Learning | Maintainability | Microsoft Azure | Model Deployment | Model Drift | Model Drift Detection | Model Monitoring | Model Serving | Natural Language | Natural Language Processing | Orchestration frameworks | RAG | Retraining Governance | Scalability | Security | Series forecasting | Time Series | Time Series Forecasting | Version control | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Architect | Architect | Learning Architect | Machine Learning Architect
Regions
Countries
States
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