Build Quality Principal

PBM Build Quality Principal   In-Factory Quality Engineering, Automation & Release Evidence   Job Description   PBM Build Quality Principal will lead execution of the program’s quality strategy across platform and product engineering builds. Working within the standards established by the PBM Test Architect Principal, this role is accountable for unit, contract, regression, evaluation, and automation testing, as well as the evidence required to demonstrate that releases meet agreed entry and exit criteria. The Principal will establish a consistent quality bar across New PBM Platform engineering teams and drive quality earlier into design and development.   This role partners closely with Product and Platform Engineering, Delivery, DevSecOps, Architecture, Test Data Engineering, the PBM Test Lead, and the PBS test organization. The Principal provides deep quality-engineering expertise, leads contractors or matrixed contributors where required, identifies systemic risks, and advances automation and responsible AI-enabled testing practices to improve release confidence, speed, and reliability.   Core Responsibilities Include   Build Quality Strategy Execution   • Operationalize the program test strategy within the New PBM Platform software factory and ensure engineering teams consistently meet the defined quality standards.   • Define build-level test plans, coverage expectations, automation requirements, evidence packages, and quality checkpoints for platform and product releases.   • Lead unit, contract, component, regression, evaluation, and other in-factory testing required before integration and end-to-end stages.   • Ensure defects, risks, exceptions, and unresolved quality concerns are transparent and appropriately escalated.   • Partner with the PBM Test Architect Principal to evolve standards based on delivery experience, defects, incidents, and emerging risks.   Automation & Quality Engineering   • Drive automation across the development and release pipeline, prioritizing repeatability, coverage, speed, and reliable evidence.   • Embed quality engineering into design, coding, pull-request, build, and deployment practices rather than relying on downstream detection.   • Partner with DevSecOps and engineering teams to integrate automated quality controls into CI/CD pipelines.   • Use AI to accelerate the quality lifecycle, including generation of unit, contract, and regression tests, synthetic test data, defect triage, root-cause analysis, and evidence assembly, judged on measured gains in cycle time and escape rate rather than tool adoption.   • Set the review bar for AI-generated test assets, covering what must be human-reviewed before it is trusted, how coverage claims are verified, and how traceability back to requirements is preserved.   • Advance service virtualization, testability, observability, synthetic data, and other techniques that reduce testing constraints.   Release Quality & Evidence   • Own compilation and validation of build-quality evidence against agreed entry and exit criteria.   • Provide clear quality assessments and recommendations for releases moving to integration and end-to-end testing.   • Establish scorecards for coverage, defect trends, escape rates, automation, stability, and quality risk.   • Lead root-cause analysis and systemic corrective action for recurring defects and quality failures.   • Partner with engineering leaders to ensure technical debt and quality risks are understood, prioritized, and addressed.   Technical Leadership & Partnership   • Serve as the senior quality-engineering advisor to platform and product engineering leaders.   • Mentor quality engineers, developers, and technical contributors in modern testing and defect-prevention practices.   • Coordi