Automation Engineer, Financial Systems AI

Key Responsibilities

• Designs, builds, and deploys AI-powered tools and automated workflows to enhance Finance organization efficiency and decision-making.
• Applies modern data engineering and AI development practices to deliver scalable, governed solutions for Finance.
• Collaborates with Finance stakeholders and cross-functional teams to translate business problems into working software, ensuring compliance with Centene data security, compliance, and applicable regulatory requirements.
• Develops and supports end-to-end AI and automated solutions for Finance operations, including data pipelines, reporting applications, workflow automation, and AI-assisted analysis tools.
• Works with Finance analysts, data engineers, and business stakeholders to identify manual or inefficient processes and design technology-enabled solutions that reduce effort and improve data quality.
• Assists in establishing and maintaining development standards, including version control practices, code review workflows, and continuous integration and delivery pipelines.
• Contributes to the team's AI governance framework by registering tools, participating in design and review processes, and ensuring adherence to Centene data classification and compliance requirements.
• Builds and maintains data transformation and integration workflows that serve as the foundation for Finance AI applications, ensuring data quality, consistency, and reliability.
• Develops interactive Finance applications that surface AI-generated insights, automate reporting tasks, and provide self-service capabilities to Finance staff.
• Provides ongoing support, troubleshooting, and incremental enhancements for deployed solutions.
• Performs other duties as assigned.
• Complies with all policies and standards.

Requirements & Tech Stack

• Foundational knowledge of software development principles and data engineering concepts.
• Familiarity with automation tools, scripting languages, or analytics platforms used in enterprise environments.
• Basic understanding of Artificial Intelligence or machine learning concepts, with emphasis on applied use rather than model research.
• Ability to translate defined business requirements into technical solutions with guidance.
• Strong attention to detail and commitment to data accuracy and quality.
• Effective written and verbal communication skills, with the ability to collaborate across technical and non-technical teams.

Qualifications

• A Bachelor's degree in Computer Science, Data Engineering, or Information Systems required.
• 0 – 2 years of related experience in software development, data engineering, or AI/Machine Learning systems required.