Principal AI Engineer

Job Description:

Job Title: Principal AI Engineer

Location: Springfield, Missouri

Department: Information Technology

Employment Type: Full-time

Job Summary: Join a compassionate, collaborative team making a measurable difference by delivering AI-driven analytics that empower business decisions and improve outcomes for stakeholders.

This role offers the opportunity to lead high-impact AI initiatives, mentor cross-functional teams, shape enterprise AI strategy, work with cutting-edge LLM and Snowflake technologies, and build production-ready systems that increase data accessibility and drive faster insights. We seek a self-directed, systems-thinking engineer with strong communication skills and a passion for translating complex analytical needs into scalable technical solutions.

The Principal AI Engineer is the senior technical contributor within Analytics responsible for designing, developing, and implementing enterprise AI capabilities on the data platform with a focus on Snowflake integration. This hands-on role develops natural language-to-SQL solutions, semantic data models, and prototype applications that enable governed, conversational access to enterprise data, and guides their transition into scalable, production-ready solutions.

This position offers...
• Employee Assistance Program - 24/7 counseling services, legal assistance, & financial consultation for you and your household at no cost
• Mileage Reimbursement - Company paid for work functions requiring travel
• Employee Discounts - Hotels, Theme Parks & Attractions, College Tuition
• Workplace Culture - An environment cultivating employee wellbeing, valuing each individual's humanity, and actively promoting a healthy, joyful workforce
• Additional Perks & Benefits - Scroll down to bottom of this post to learn more

Key Responsibilities:

• Lead the design and implementation of LLM-enabled analytics capabilities leveraging Snowflake and Cortex AI features

• Develop natural language-to-SQL solutions and conversational interfaces that allow business users to query governed enterprise data

• Collaborate with Data Engineering to design and maintain semantic data models that support reliable AI-driven query generation

• Build prototype AI applications to validate high-value business use cases and demonstrate new capabilities

• Guide the transition of prototypes into scalable, production-ready solutions and establish architectural patterns and best practices for LLMs with structured data

• Assist Data Engineering with prompt design, query-generation frameworks, evaluation approaches, and integration tasks

• Identify high-impact opportunities for AI across analytics, reporting, and decision-support workflows

• Evaluate emerging AI technologies, tools, and Snowflake platform capabilities for potential adoption

• Support development of standards for responsible, secure AI usage aligned with enterprise data governance

• Document system architecture, design decisions, and implementation approaches

• Provide technical guidance and mentorship to analytics and data engineering team members

• Function in accordance with operational guidelines and professional ethics; participate in staff development activities; perform other duties as assigned

Education, Experience, and/or Credential

Qualifications:



• Bachelor's degree or equivalent experience in Computer Science, Data Engineering, Data Science, Information Systems, or related field

• 7+ years of experience in data, analytics, engineering, or applied AI roles

• Demonstrated experience building or prototyping AI/LLM-driven solutions in enterprise environments

• Experience with modern data warehouse platforms (Snowflake preferred)

• Proficiency in SQL and Python

• Experience with cloud platforms (AWS, Azure, or GCP) preferred

• Healthcare or regulated industry experience preferred but not required

Additional Qualifications:

• Strong understanding of modern data warehouse architecture and analytics data modeling practices

• Experience designing natural language query interfaces, prompt engineering, context management, and grounding techniques for LLM systems

• Knowledge of semantic data modeling and data governance principles

• Ability…