Senior AI Data Solutions Engineer
Air Methods Corporation · Greenwood Village, CO, US
About this role
## Senior AI Data Solutions Engineer ### Overview Design, build, and deploy internal AI applications and data products within the Company’s **Snowflake** ecosystem. You’ll establish technical direction for the design, evaluation, governance, and continuous improvement of AI solutions—translating business requirements, data, and processes into scalable data structures, semantic layers, analytics, and user-focused AI experiences. ### Key Responsibilities - Architect, design, build, and deploy **agentic AI architectures** and **LLM-powered applications** (chatbots and assistants) on **Snowflake** that deliver accurate, governed answers over enterprise data. - Lead the most complex, highest-visibility solutions from concept through production. - Own and operate **RAG pipelines**, including data preparation, embeddings, search indexing, semantic routing, and retrieval tuning (using **Snowflake Cortex AI** and Python orchestration frameworks). - Make architecture decisions for **performance, scalability, and cost**. - Own the strategy for **semantic layers**, semantic models, and metadata to ensure consistent business definitions, reduce hallucinations, and restrict sensitive data (e.g., **PHI**, billing/claims data, employee personal information). - Build descriptive, prescriptive, and predictive analytics solutions, including ML/statistical models exposed as endpoints that AI tools and dashboards can query. - Develop user-facing AI experiences using **Streamlit in Snowflake**, **Snowpark**, and existing analytics tools; drive adoption via training, documentation, and enablement. - Serve as a trusted advisor to senior stakeholders; lead discovery with subject matter experts to translate business language and metrics into data schemas, AI use cases, and roadmaps. - Define and own AI **evaluation, testing, and monitoring** (accuracy benchmarks, test sets, prompt/version control, usage and cost monitoring, and quality reporting). - Partner with Data Engineering, Information Security, and Compliance to define and enforce **access controls, data privacy, and responsible AI standards** in a **HIPAA-regulated** environment (including ensuring PHI/PII are not used in unapproved development tools). - Establish and evolve standards, reference architectures, and reusable patterns for AI solution design, prompt engineering, deployment, and maintenance. - Mentor and provide technical guidance to AI Solutions Engineers, data engineers, and analysts. - Evaluate emerging AI/LLM capabilities, lead pilots, and recommend adoption based on business value, risk, and cost. ### Qualifications (Summary) - **8+ years** in data engineering, data science, machine learning engineering, or related work; **3+ years** building LLM/generative AI applications; **2+ years** as a technical lead/architect on production data or AI solutions. - Deep hands-on experience designing and operating production **RAG** pipelines and **agentic workflows** (e.g., **LangChain**, **LlamaIndex**). - Expert experience building on **Snowflake**: **Snowpark**, **Cortex AI** (Cortex Search, Cortex Analyst), and **Streamlit**. - Strong experience with **semantic layers**, metadata management, and data governance (HIPAA experience strongly preferred). - Strong prompt engineering and **LLM evaluation** skills (accuracy, hallucination reduction, evaluation frameworks). - Deep knowledge of semantic routing, embeddings, vector search, and retrieval tuning. - Proven ability to build predictive/presc
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