Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Rapidly prototype and iterate on automation and integration approaches using AI-assisted workflows (e.g., scaffolding services, generating tests, drafting technical documentation) to shorten delivery timelines and increase throughput.
Implement and support AuthE-based login for non-workforce users accessing internally built web reporting applications (human interactive authentication)
Configure and troubleshoot AuthE-supported authentication patterns and flows used by the application (e.g., OAuth 2.0 / OIDC and/or SAML federation, depending on the chosen pattern)
Support access and entitlement management workflows and user access issue resolution tied to external reporting access
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 3+ years applied experience
Hands-on practical experience in system design, application development, testing, and operational stability
Experience in developing, debugging, and maintaining code in a large corporate environment with Python and Django and database querying languages
Experience building REST APIs using Django REST Framework
Cloud experience (AWS, Cloud Foundry, or similar)
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Overall knowledge of the Software Development Life Cycle
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Familiarity with AuthE capabilities used for external login (e.g., username/password + OTP, federated SSO via SAML, OAuth 2.0 authorization code flow)
Experience automating BI platforms (Tableau, ThoughtSpot, Cognos, Qlik)
Experience building internal enterprise tools
Familiarity with MySQL
Experience integrating with infrastructure automation tools (e.g., Gaia, Jenkins)
