Snowflake AI Engineer

Key Responsibilities

Snowflake Cortex AIAgentic AI Development

Design and implement Cortex AI solutions including Cortex Analyst natural language to SQL Cortex Search hybrid semantickeyword search and Cortex Agents for multistep autonomous workflows grounded in Vulcans governed enterprise data

Build and deploy AISQL functions leveraging hosted LLMs Anthropic Claude Meta Llama Mistral OpenAI for indatabase AI transformationseg summarization of safety reports classification of supplier communications and extraction of insights from unstructured operational data

Develop RAG RetrievalAugmented Generation pipelines using Cortex Search and vector embeddings for document QA across regulatory filings environmental compliance records and operational SOPs

Architect and orchestrate Cortex Agents that autonomously plan retrieve and synthesize insights across structured ERP supply chain and unstructured sensor logs field reports data sources

Snowflake IntelligenceCortex Code

Configure and extend Snowflake Intelligence as a personal work agent for business usersenabling selfservice analytics automated reporting and workflow automation with Skills Artifacts and Deep Research capabilities

Leverage Cortex Code for AIpowered development workflowsaccelerating codetoproduction cycles building governed data pipelines and integrating with tools like dbt Airflow and enterprise systems via MCP Model Context Protocol connectors eg Salesforce Jira Google Workspace

Implement observability governance and guardrails for all AI workloadsensuring rolebased access control audit trails and compliance with Vulcans data governance policies

Data ScienceMachine Learning

Apply classical and modern machine learning techniquesregression classification clustering timeseries forecasting and anomaly detectionto solve business problems across

o Demand forecasting for aggregates across 400 facilities

o Predictive maintenance for crushing screening and hauling equipment

o Pricing optimization based on market conditions transportation costs and material availability

o Safety analyticspredicting and preventing workplace incidents

o Supply chain optimizationlogistics routing fleet utilization and inventory management

Build and deploy ML models using Python scikitlearn XGBoost PyTorch TensorFlow within Snowflakes native ML environment Snowpark ML Snowflake Model Registry

Implement MLOps best practicesmodel versioning AB testing drift monitoring and automated retraining pipelines

Data EngineeringIntegration

Collaborate with data engineers to design data pipelines that feed AIML workloadsincluding structured data from SAPERP systems IoTsensor data from quarry operations and unstructured data field reports images PDFs

Optimize Snowflake compute and storage for AI workloadsleveraging dynamic tables Snowpark Iceberg tables and streaming ingestion

Integrate AI outputs into downstream systemsdashboards Power BI Tableau operational applications and alerting frameworks