Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Experience with Java development
Knowledge of cloud skills and/or hands-on experience with AWS or GCP
Understanding of Agile methodologies such as CI/CD, Applicant Resiliency, and Security
Familiar with Linux/UNIX environment
Experience working with AI agents for engineering
Preferred qualifications, capabilities, and skills
Experience with networking control points such as firewalls, security groups, ingress/egress controllers
Experience with automation testing
Experience leveraging Terraform to define, provision, and manage cloud infrastructure
Should be highly organized, detail-oriented, hands-on, motivated self-starter who can work independently
Eager to learn and experiment with cutting-edge technologies
AI enthusiast - focused on applying AI to drive meaningful impact for the team
