AI Engineer
Tasks
- Apply model risk management and auditability
- Build generative AI RAG and agent workflows
- Define evaluation and monitoring for GenAI outputs
- Deploy AI models as scalable services
- Design production AI services and pipelines
- Embed AI governance into engineering workflows
- Establish deployment rollback procedures
- Implement automated ML delivery pipelines
- Implement embeddings and semantic search
- Implement environment isolation and controlled releases
- Implement monitoring, alerting, and runbooks
- Implement security access controls and privacy controls
- Manage model versioning and reproducibility
- Resolve production incidents for AI systems
Perks/Benefits
Skills/Tech-stack
APIs | Agent workflows | Alerting | Audit Logging | Azure | Data Governance | Embeddings | GCP | LLMOps | MLOps | Machine Learning | Model Risk Management | Model risk | Model versioning | Monitoring | Observability | Privacy | Python | Retrieval-Augmented Generation | Risk Management | SQL | Security | Semantic Search
Education
N/A
Roles
AI | AI Engineer | Engineer
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