Principal AI Engineer — AI Solutions (Enabling Functions)
Tasks
- Build data pipelines feature stores and data quality lineage controls
- Build governed RAG pipelines with hallucination guards
- Build reusable multi agent components and governance instrumentation
- Define model strategy and integration patterns
- Design and ship governed multi agent LLM systems
- Develop governance as code workflows and monitoring
- Embed operational resilience with failover and circuit breakers
- Engineer multi jurisdiction compliance controls
- Implement audit logging and immutable data trails
- Implement fairness and explainability pipelines
- Implement sovereignty aware model routing and data residency
- Lead end-to-end AI solution design
- Manage AI lifecycle decommissioning and model registration
- Monitor model drift and bias and run AI red teaming
- Set up CI CD automated testing observability and incident response automation
Perks/Benefits
Skills/Tech-stack
AI red teaming | Agent systems | Artificial Intelligence | Audit Logging | Automated testing | Bias monitoring | CI/CD | Chaos Engineering | Circuit Breakers | Classification Tiering | Continuous Delivery | Continuous integration | Data Governance | Data Lineage | Data Quality | Data Residency | Data Sovereignty | Drift monitoring | Explainability | Failover | Fairness testing | Feature Store | Governance-as-code | Graceful Degradation | Human-in-the-loop | Incident Response | Language Models | Large Language Models | MLOps | Machine Learning | Model Drift | Model drift monitoring | Model routing | Monitoring pipelines | Multi-Agent | Multi-Agent Systems | Observability | Performance Monitoring | RAG | Red Teaming | Retrieval-Augmented Generation | The Loop | Workflow automation | “as-code”
Education
Roles
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