Lead Consultant - Snowflake and Cortex AI Engineer
Tasks
- Apply governance security and compliance with audit trails
- Build model pipelines from experimentation to production
- Design Snowflake native ML platform architecture
- Design and deliver agentic AI systems on Cortex AI
- Design feature stores and enable feature reuse
- Develop prompt architectures and prompt engineering
- Engineer batch and streaming data workflows
- Establish testing validation and release processes
- Implement CI/CD for ML model deployment
- Implement RBAC dynamic data masking and secrets management
- Implement token usage and cost optimization for LLM workflows
- Mentor engineers and lead design reviews
- Monitor model performance drift and bias
- Optimize Snowflake warehouses queries and compute costs
- Set up logging tracing alerting and health monitoring
Perks/Benefits
- N/A
Skills/Tech-stack
Alerting | Audit Logging | Azure DevOps | CI/CD | Contract testing | Cortex AI | Data Governance | Data Privacy | Data masking | Docker | Dynamic Tables | Dynamic data | Dynamic data masking | Event Tables | External functions | Feature Store | GitHub Actions | Go | Healthcare Data | Healthcare data privacy | Integration APIs | Integration Testing | JavaScript | Language Models | Large Language Models | Logging | MLOps | Machine Learning | Model Deployment | Model Registry | Multifaceted Tables | Observability | Prompt engineering | Python | RBAC | Row Level Security | Rust | SQL | Secrets management | Snowflake | Snowflake Model Registry | Snowpark | Snowpark Containers | Snowpipe | Stored Procedures | Streams | TDD | Tasks | Terraform | Testing | Token optimization | Tracing | TypeScript | UDF | UDTF | Uptime monitoring
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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