AI Engineer
Tasks
- Architect LLM and tool combinations
- Build AI evaluation frameworks
- Collaborate with cross-functional teams
- Design RAG pipelines
- Develop CI/CD and containerization
- Establish semantic data layers
- Extend AI architecture
- Implement secure data access and filtering
- Integrate vector databases
- Mentor engineering staff
- Model enterprise data with ontologies
- Review technical designs and code
- Troubleshoot and improve AI systems
Perks/Benefits
- 401k
- Discretionary bonus
- Family & fertility benefits
- Medical/Dental/Vision
- Paid time off
- Parental leave
- Profit sharing
Skills/Tech-stack
A/B | A/B Testing | AI/ML | AI/ML Platforms | Azure | B testing | Cloud services | Data Pipelines | Data Privacy | Data Standards | Delta Lake | DevOps | Docker | Drift monitoring | ELT | ETL | Event Driven | Event-driven architecture | Feature Flags | Financial Data | Financial data standards | GraphQL | Knowledge graphs | Linguistics | ML Platforms | Microservices | Microsoft Fabric | Model Drift | Model Governance | Model drift monitoring | Ontology Modeling | Prompt engineering | Python | REST | Retrieval-Augmented Generation | Security practices | Semantic Modeling | Spark | Telemetry | Terraform | Tracing | Unity Catalog | Vector Databases | Versioned Data
Education
Roles
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