- 12+yrs exp Only locals Chicago - Our client is seeking a Sr AI Data Engineer to join its Data Engineering team, building ingestion and transformation pipelines and GenAI-enabled workflows on Snowflake and AWS, and packaging them as Snowflake Native Apps.
- Responsibilities
- Design and build scalable data ingestion and transformation pipelines in Snowflake and AWS
- Develop GenAI-enabled workflows using Snowflake Cortex AI or an equivalent production LLM platform, including structured extraction from free text at scale
- Package solutions as Snowflake Native Apps using the Native App Framework and Snowpark
- Implement ML/LLM observability, evaluation design, and drift monitoring
- Define and track data quality and model quality KPIs
- Build CI/CD and infrastructure-as-code for pipeline deployment
- Support production rollout, documentation, and handoff to operations teams
- Required Qualifications
- Experience: 8+ years overall, including 5+ years in Data Engineering and 2+ years in hands-on GenAI development.
- Snowflake: Advanced SQL, Streams/Tasks, stored procedures, performance tuning, Snowpark, and Native App Framework.
- GenAI/LLMs: Hands-on experience with Snowflake Cortex AI or equivalent production LLM platforms, including large-scale structured data extraction from free text.
- AWS: Strong experience with S3, Lambda, Glue, Step Functions, DynamoDB, EC2, Kinesis, and CloudFormation.
- Python & Pipelines: Production-grade Python development and scalable data ingestion and transformation pipelines.
- ML/LLM Monitoring: Experience with LLM observability, model evaluation, drift monitoring, and data/model quality KPIs (Arize or similar).
- DevOps: Hands-on experience with CI/CD (GitHub Actions/Jenkins), Infrastructure as Code (Terraform/CloudFormation), and automated deployments.
- Preferred: Experience with customer data/personalization, human-in-the-loop classification, data privacy, Snowflake governance, and prompt regression testing.
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