- Executes creative software solutions, design, development, and technical
troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- 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.
- Set and run journey quality strategy to convert product intent into
risk-based acceptance criteria, measurable quality outcomes, and clear entry/exit standards for key IAM journeys
- Design coverages that stays current with maintaining a living journey map
(personas → flows → tests) and continuously tune regression & performance testing scope based on change impact and production learnings
- Engineer partner-facing integration validation by implementing contract
tests, stubs/simulators, and automated integration/acceptance suites that emulate partner behaviors and isolate dependency risk
- Identifies opportunities to eliminate or automate remediation of recurring
issues to improve overall operational stability of software applications and systems
- Improve reliability of the testing system in reducing flakiness and
time-to-diagnosis through stability patterns (selectors/fixtures, determinism, parallelism strategy), and clear quarantine/triage rules
- Own defect prevention loop to lead reproduction → triage → fix validation →
prevention, feeding failure patterns back into coverage, data strategies, and automation improvements
- Report “journey health” with clarity by providing executive-ready readiness
reporting that explains risk, coverage, and release posture in plain language—backed by evidence, not volume metrics
- Leads communities of practice across Software Engineering to drive awareness
and use of new and leading-edge technologies and must add to team culture of diversity, opportunity, inclusion, and respect