Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
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.
Contribute to AI-enabled initiatives for content generation, experimentation, personalization, and workflow automation
Collaborate with product, marketing, and partners to translate requirements into well-designed technical solutions
Improve engineering excellence through code reviews, test automation, CI/CD, observability, performance tuning, and operational best practices
Ensure solutions meet security, privacy, and compliance expectations including consent management, data minimization, and access controls
Required Qualifications, Capabilities, and Skills
Proficiency in Java, Python, and React
Strong backend and frontend engineering fundamentals
Experience delivering customer-facing and internal platforms
Ability to build integrations with systems such as CMS, CDP, and CRM
Understanding of AI services and their integration into web applications
Knowledge of data flows, event-driven pipelines, and personalization techniques
Familiarity with security, privacy, and compliance requirements
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 practice
Commitment to engineering excellence and operational best practices
Effective collaboration and communication skills
Preferred Qualifications, Capabilities, and Skills
Experience with campaign management and attribution systems
Background in AI-enabled content generation, experimentation, or workflow automation
Skills in test automation, CI/CD, and observability tools
Experience optimizing performance and scalability
Familiarity with consent management and data minimization practices
Ability to drive innovation in personalization and measurement
Experience working in cross-functional teams
