AI Data Innovation Engineer

What you'll do

• Prototype, validate, and operationalize AI capabilities using governed enterprise data products and standardized semantic models.
• Develop reusable AI enablement patterns for Snowpark workloads, RAG, and agent orchestration aligned with platform standards.
• Design and validate conversational data and agent-enabled experiences using Snowflake Cortex and Databricks Genie.
• Translate successful experiments into reference architectures, implementation playbooks, and adoption guidance for other teams.
• Partner with risk and security teams to implement responsible AI guardrails, policy enforcement, and auditability.
• Evaluate emerging AI tools and frameworks through proofs of concept to ensure interoperability and avoid technology sprawl.
• Establish AI observability practices covering agent traces, prompt quality, latency, cost, and safety signals.
• Serve as a technical mentor to guide teams through architectural choices and reduce duplicated experimentation.

What we're looking for

• Bachelor's degree in a related field or equivalent work experience.
• Eight or more years of statistical and/or data analytics experience.
• Hands-on experience with modern data and AI platforms such as Snowflake and Databricks.
• Experience developing AI-enabled solutions using Python and SQL.
• Experience implementing AI guardrails, evaluations, observability, security, governance, and operational controls for production-oriented solutions.
• Experience with agent integration and orchestration frameworks such as LangGraph, LangChain, or Semantic Kernel.
• Experience with CI/CD, automated testing, and deployment patterns using platforms like Harness, GitHub Actions, or Azure DevOps.
• 7-10 years of experience across AI engineering, data engineering, or related roles (preferred).