Senior AI Data Solutions Engineer

Air Methods • Greenwood Village, CO

20h • $137,000 - $174,000

About The Position

The Senior AI Data Solutions Engineer designs, builds, and deploys internal AI applications and data products within the Company’s Snowflake ecosystem, establishing technical direction for solution design, evaluation, governance, and continuous improvement. Working across Operations, Human Resources, Finance, Patient Billing, and other business functions, the role translates business requirements, data, and processes into scalable data structures, semantic layers, analytics, and user-focused AI solutions. It leads development of retrieval-augmented generation pipelines, agentic workflows, chatbots, and related analytical tools, ensuring accuracy, performance, security, and appropriate governance. The position also provides technical guidance and mentorship to engineering team members.

The role owns complex, high-visibility AI solutions from concept through production, including RAG pipelines, semantic models, analytics, and user-facing AI experiences. It defines evaluation and monitoring practices, establishes reusable architecture and engineering standards, and partners with Data Engineering, Information Security, Compliance, business stakeholders, data scientists, and product owners. Work takes place in a HIPAA-regulated environment, with particular attention to protecting PHI, PII, billing, claims, and employee personal information.

This position has no formal supervisory responsibilities, though it provides technical leadership and mentorship and may lead project workstreams without direct reports. Regular scheduled attendance is required. Travel is 0%.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, and eight or more years of related experience and/or training; or an equivalent combination of education and experience.
• Eight or more years in data engineering, data science, machine learning engineering, or a related field, including three or more years building LLM or generative AI applications and two or more years as a technical lead or architect on production data or AI solutions.
• Deep hands-on experience designing and operating production RAG pipelines and agentic workflows, including orchestration frameworks such as LangChain or LlamaIndex.
• Expert-level experience building on Snowflake, including Snowpark, Cortex AI (Cortex Search and Cortex Analyst), and Streamlit.
• Demonstrated success leading engagement with senior business stakeholders to translate metrics into data schemas and develop user-friendly AI tools.
• Experience designing semantic layers, metadata management, and data governance frameworks.
• Expert prompt engineering and LLM evaluation skills, including designing evaluation frameworks, reducing hallucinations, and measuring answer accuracy.
• Deep experience with semantic routing, embeddings, vector search, and retrieval strategy tuning.
• Experience building predictive and prescriptive statistical and machine learning models and deploying them as callable endpoints.
• Ability to independently translate ambiguous business questions into well-defined data products and AI use cases.
• Strong experience with complex data modeling, ELT design, and performance and cost optimization on large databases in a business environment.
• Rigor in data quality, lineage, access control, and sensitive-data handling, and ability to set that expectation for others.
• Ability to learn modern AI technologies and quickly prototype and validate new approaches.
• Ability to develop unconventional solutions, identify opportunities to innovate, and lead innovation.
• Strong critical thinking, reasoning, and attention to detail; ability to prioritize and multitask in a fast-paced environment.
• Excellent written and verbal communication, including explaining AI behavior and limitations to non-technical audiences and presenting to executive leadership.
• Advanced experience with Microsoft Word, Excel, PowerPoint, and Outlook.
• Expert proficiency in Python and SQL, including manipulation of large structured and semi-structured datasets.
• Extensive experience with Snowflake, Snowpark, Cortex AI, and Streamlit in Snowflake.
• Extensive experience with LLM provider APIs and orchestration frameworks such as LangChain or LlamaIndex.
• Experience with cloud warehouse ELT tools and DAG schedulers such as dbt or Estuary.
• Experience using AI-assisted development tools such as Claude Code within company governance guidelines.
• Experience with version control and CI/CD tools such as Git or Azure DevOps.
• Strong experience in an Agile Scrum environment, including leading work estimation and sequencing and providing input to managers on resource and risk planning.

Nice To Haves

• HIPAA experience is strongly preferred.
• Familiarity with data visualization tools; Power BI and Sigma Computing are preferred.
• Snowflake SnowPro certification at the Advanced level is preferred.

Responsibilities

• Architect, design, build, and deploy agentic AI architectures and LLM-powered applications, including chatbots and assistants, on Snowflake; own complex, high-visibility solutions from concept through production.
• Lead the design and operation of RAG pipelines, including data preparation, embedding, search indexing, semantic routing, and retrieval tuning using Snowflake Cortex AI and Python-based orchestration frameworks.
• Make architecture decisions concerning solution performance, scalability, and cost.
• Own the strategy for semantic layers, semantic models, and metadata that provide consistent business definitions, reduce hallucinations, and exclude or restrict sensitive data.
• Build descriptive, prescriptive, and predictive analytics solutions, including machine learning and statistical models exposed as endpoints for AI tools and dashboards.
• Develop user-facing AI experiences using Streamlit in Snowflake, Snowpark, and existing analytics tools; support adoption through training, documentation, and business-user enablement.
• Lead discovery with subject matter experts and advise senior business stakeholders, translating business language, processes, and metrics into data schemas, AI use cases, and prioritized roadmaps.
• Define and own AI evaluation, testing, and monitoring frameworks, including accuracy benchmarks, test question sets, prompt and version control, usage and cost monitoring, and reporting solution quality to leadership.
• 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.
• Establish and evolve standards, reference architectures, and reusable patterns for AI solution design, prompt engineering, deployment, and maintenance; lead code and design reviews.
• Mentor and provide technical guidance to AI Solutions Engineers, data engineers, and analysts.
• Collaborate with data scientists and product owners to integrate AI solutions with ELT pipelines, data models, and analytics tools.
• Evaluate emerging AI and LLM capabilities, lead pilots, and recommend adoption based on business value, risk, and cost.
• Perform other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior