Principal AI Engineer — AI Solutions (Enabling Functions)
Tasks
- Build data pipelines and feature stores
- Build governed RAG pipelines
- Build shared reusable agent patterns
- Deliver production intent prototypes
- Design and ship multi agent LLM systems
- Engineer multi jurisdictional compliance
- Implement Governance as Code
- Implement circuit breakers and provider fallbacks
- Implement classification tiering logic
- Implement data governance for regulated data
- Implement data quality and lineage controls
- Implement deterministic routing layers
- Implement drift and bias monitoring
- Implement fairness and explainability pipelines
- Implement governance instrumentation
- Implement graceful degradation and fail safe defaults
- Implement hallucination guards
- Implement human in the loop oversight
- Implement immutable audit logging
- Implement model registration and approval workflows
- Implement model routing and data residency
- Implement monitoring pipelines and decommissioning controls
- Implement performance monitoring and incident response automation
- Integrate enterprise platforms and external partners
- Lead AI red-teaming
- Lead end-to-end AI solution design
- Make and document model strategy decisions
- Manage capacity and lifecycle operations
- Measure adoption impact with KPIs KRIs
- Own MLOps delivery to production
- Produce assurance reporting for oversight
- Run failover tests and chaos testing
- Run technical discovery and UX iteration
- Select AI patterns and component boundaries
- Set up CI/CD and automated testing
- Translate sovereignty policy into infrastructure
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 | Data Governance | Data Lineage | Data Quality | Data Residency | Data Sovereignty | Drift monitoring | Explainability | Fail Safe | Fail Safe Defaults | Failover Testing | Fairness testing | Feature Stores | Governance-as-code | Graceful Degradation | Human-in-the-loop | Incident Response | Language Models | Large Language Models | MLOps | Machine Learning | Model registration | Model routing | Monitoring pipelines | Multi-Agent | Multi-Agent Systems | Observability | Performance Monitoring | Provider Fallbacks | RAG | Red Teaming | Retrieval-Augmented Generation | The Loop | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
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