Senior AI Data Solutions Engineer

Overview Job Summary The Senior AI Data Solutions Engineer is responsible for designing, building, and deploying internal AI applications and data products within the Company’s Snowflake ecosystem. This role establishes technical direction for the design, evaluation, governance, and ongoing improvement of AI solutions. Working across Operations, Human Resources, Finance, Patient Billing, and other business functions, the Senior AI Data Solutions Engineer translates business requirements, data, and processes into scalable data structures, semantic layers, analytics, and user-focused AI solutions. The role leads the development of retrieval-augmented generation pipelines, agentic workflows, chatbots, and related analytical tools while ensuring solution accuracy, performance, security, and appropriate governance. This position also provides technical guidance and mentorship to engineering team members. This is not a remote position. You must live or be willing to live in Denver, CO Essential Functions and 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; own the most complex and highest-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 on performance, scalability, and cost Own the strategy for semantic layers, semantic models, and metadata that give AI tools consistent business definitions, reduce hallucination, and exclude or restrict sensitive data such as PHI, billing and claims data, and employee personal information Build and deliver descriptive, prescriptive, and predictive analytics solutions, including machine learning and 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, and drive adoption through training, documentation, and enablement of business users Serve as a trusted advisor to senior business stakeholders; lead discovery with subject matter experts across departments to learn their business language and processes, and translate their metrics into data schemas, AI use cases, and prioritized roadmaps Define and own the AI evaluation, testing, and monitoring framework, including accuracy benchmarks, test question sets, prompt and version control, usage and cost monitoring, and report on 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, including keeping PHI and PII out of development tools not approved for that data 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 with business cases based on business value, risk, and cost Other duties as assigned Additional Job Requirements Regular Scheduled Attendance Percentage of time spent traveling: 0% Subject to applicable laws and Air Method’s policies, regular attendance is an essential function of the position. All employees must follow Air Methods’ employment practices and policies. Supervisory Responsibilities This position has no formal supervisory responsibilities. The Senior AI Solutions Engineer provides technical leadership, mentorship, and guidance to other team members and may lead project workstreams without direct reports. Qualifications To perform this job successfully, an individual must be able to perform each essential function satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. In accordance with applicable laws, Air Methods will provide reasonable accommodations that do not create an undue burden so disabled employees may perform the essential functions of the position. Education & Experience   Bachelor’s degree (BS/BA) from four-year college or university in Computer Science, Data Science, Engineering, or related field, and eight+ years’ related experience and/or training; or equivalent combination of education and experience 8+ years in data engineering, data science, machine learning engineering, or related field, including 3+ years building LLM or generative AI applications and 2+ 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, Cortex Analyst), and Streamlit Proven track record leading engagement with senior business stakeholders to translate metrics into data schemas and turn those schemas into user-friendly AI tools Experience designing semantic layers, metadata management, and data governance frameworks, ideally in a regulated environment (HIPAA experience strongly preferred) Familiarity with data visualization tools (Power BI and Sigma Computing preferred) Strong experience in an Agile Scrum environment, including leading work estimation and sequencing and providing input to managers on resource and risk planning Skills Expert prompt engineering and LLM evaluation skills, inc