Seeking a hands-on AI Engineer to enhance intelligent, data-driven capabilities on our cloud data platform, utilizing deep expertise in Amazon Bedrock, Kiro, and Snowflake Cortex. This role is integral to our Enterprise Data Architecture and Data Platform team, which sets enterprise-wide data and AI standards, develops scalable platform capabilities, and governs solutions across the firm.

Beyond solution development, you will contribute to defining reusable standards, patterns, and documentation for adoption by engineering teams. This is a practical, execution-focused position demanding proven experience in delivering AI use cases end-to-end into production.

Design, build, and deploy AI solutions using Snowflake Cortex (LLM Functions, Analyst, Search, Fine-Tuning). Develop and operationalize agent-based workflows and skills with Amazon Bedrock and Kiro, integrating enterprise data. Build AI-enabled pipelines and retrieval capabilities over enterprise data assets using Snowflake and AWS services.

Implement Snowflake ML features for forecasting, anomaly detection, and classification. Design and author enterprise-wide AI standards and reusable patterns, ensuring clear documentation. Write and maintain evaluation frameworks to assess AI output quality, including LLM-as-judge patterns and regression testing. Collaborate with data engineers on AI solution integration with Medallion architecture. Integrate AI capabilities with enterprise applications and APIs.

Apply best practices for AI governance, observability, and lifecycle management. Contribute to reusable frameworks and best practice guides. Leverage AI-assisted development tools like Amazon Q and Kiro to expedite solution delivery.

Expert, hands-on experience with Snowflake Cortex (LLM Functions, Analyst, Search, Fine-Tuning). Strong experience with Amazon Bedrock and building AI solutions using foundation models, orchestration patterns, and agent capabilities. Familiarity with Kiro for accelerating AI solution development.

Proven experience delivering at least one end-to-end AI use case into production using Snowflake Cortex, Amazon Bedrock, or similar platforms. Strong Python development skills for modular, testable, production-grade code. Experience building and integrating agent-based workflows and skills. Demonstrated ability to write and implement AI evaluation frameworks.

Excellent technical documentation skills for clear, structured standards and guides. Proficiency in SQL and Snowflake platform fundamentals (Snowpark, Streamlit, stages, UDFs). Familiarity with AI governance and observability practices. Comfortable with GitOps/CI/CD workflows. Familiarity with AI-assisted development tools (Amazon Q, Kiro).