Principal AI Engineer — AI Solutions (Enabling Functions)
Tasks
- Build data pipelines feature stores data lineage and controls
- Build governed RAG pipelines
- Build multi-agent LLM systems
- Create model registration and approval workflows
- Design operational resilience patterns
- Develop decommissioning and human in the loop oversight
- Develop governance as code
- Engineer multi jurisdictional compliance controls
- Implement CI/CD and automated testing
- Implement drift and bias monitoring
- Implement hallucination guards and audit logging
- Implement sovereignty aware model routing
- Lead AI red teaming and fairness testing
- Lead end-to-end AI solution architecture
- Make and document model strategy decisions
- Measure adoption and impact using KPIs KRIs
- Own MLOps delivery and lifecycle management
- Set up monitoring and incident response automation
Perks/Benefits
- N/A
Skills/Tech-stack
AI red teaming | Agent systems | Artificial Intelligence | Audit Logging | Automated testing | Bias monitoring | CI/CD | Capacity Management | Chaos Engineering | Circuit Breakers | Classification and Tiering | Data Lineage | Data Quality | Data Residency | Data Sovereignty | Decommissioning Controls | Drift monitoring | Explainability | Failover Testing | Fairness testing | Feature Store | Governance-as-code | Graceful Degradation | Human-in-the-loop | Incident Response | Incident response automation | KPI design | KRI Design | Language Models | Large Language Models | MLOps | Machine Learning | Model registration | Model routing | Monitoring pipelines | Multi-Agent | Multi-Agent Systems | Observability | Performance Monitoring | RAG | Red Teaming | Response Automation | Retrieval-Augmented Generation | The Loop | “as-code”
Education
N/A
Roles
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