Automation Engineer, Financial Systems AI

Key Responsibilities

• Design, build, and deploy AI-powered tools and automated workflows to improve efficiency and decision-making within the Finance organization.
• Apply modern data engineering and AI development practices to create scalable, governed solutions for Finance.
• Collaborate 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.
• Develop and support end-to-end AI and automated solutions for Finance operations, including data pipelines, reporting applications, workflow automation, and AI-assisted analysis tools.
• Identify manual or inefficient processes and assist in designing technology-enabled solutions to reduce effort and improve data quality.
• Establish and maintain development standards, including version control practices, code review workflows, and CI/CD pipelines.
• Contribute 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.
• Build and maintain data transformation and integration workflows for Finance AI applications, ensuring data quality, consistency, and reliability.
• Develop interactive Finance applications to surface AI-generated insights, automate reporting tasks, and provide self-service capabilities.
• Provide ongoing support, troubleshooting, and incremental enhancements for deployed solutions.
• Perform other duties as assigned.
• Comply 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.
• 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, Information Systems required.
• 0 – 2 years of related experience in software development, data engineering, or AI/Machine Learning systems required.