W2 candidatesLocalsSkills required - Java, AWS preferred, Kubernetes, some streaming/Kafka, NOSQL, CI/CD, testing, alerts, and monitoring(Splunk/dynatrace). Must know AI for code optimization to accelerate development.Develops secure and high-quality production code, and reviews and debugs code written by othersDrives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.Drives decisions that influence the product design, application functionality, and technical operations and processesServes as a function-wide subject matter expert in one or more areas of focusActively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life CycleDrives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
Not specified in the original listing.
Not specified in the original listing.
