Lead Consultant - Snowflake and Cortex AI Engineer
Tasks
- Build autonomous detection and action agents
- Build model pipelines from experimentation to production
- Design Cortex AI agent architectures
- Design Snowflake native ML platform architecture
- Design feature stores and feature reuse
- Develop prompt engineering and instruction architecture
- Engineer batch and streaming data workflows
- Ensure reliability, performance, and cost optimization
- Establish testing validation and release processes
- Implement governance, security, and compliance controls
- Implement logging tracing alerting and monitoring
- Implement model lifecycle versioning and deployment
- Lead engineering standards and mentor engineers
- Monitor model performance drift and bias
- Optimize token economics and cost control
Perks/Benefits
- N/A
Skills/Tech-stack
Access policies | Audit controls | Azure DevOps | Bias monitoring | CI/CD | Caching | Chunking | Contract testing | Cortex AI | Cortex Analyst | Cortex Fine Tuning | Cortex LLM | Cortex Search | Data Lineage | Data Quality | Data masking | Docker | Dockerfile | Drift Detection | Dynamic Tables | Dynamic data | Dynamic data masking | Embeddings | Event Tables | Feature Stores | Fine Tuning | GitHub Actions | Integration Testing | Linting | MLflow | Model Registry | Network policies | Observability | Prompt engineering | Python | RBAC | Row Access | Row access policies | SQL | SageMaker | Scala | Secrets management | Snowflake | Snowpark | Snowpark Containers | Snowpipe | Stored Procedures | Streams | TDD | Tasks | Terraform | Tokenization | Type Checking | UDF | UDTF
Education
Roles
Consultant | Data Engineering | Data Engineering Manager | Engineer | Engineering Manager | Lead | Lead Consultant | MLOps Engineer | Manager
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