Senior Associate - QA Test Engineering Lead
Listed on 2026-05-14
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IT/Tech
IT QA Tester / Automation -
Quality Assurance - QA/QC
IT QA Tester / Automation
Location Designation
Hybrid - 3 days per week
We are seeking an experienced QA Test Engineering Lead to lead quality assurance for the Claims & Money Movement train within the Service Experience value stream. This role is responsible for defining and driving the end‑to‑end quality strategy across complex, highly integrated servicing platforms that support claims processing, payments, disbursements, and financial transactions.
As a QA lead, you will operate as a train‑level quality leader, partnering closely with Product Owners, Development Managers, Solution Leads, and Architects to ensure the delivery of high‑quality, compliant, and scalable solutions. You will set testing direction, advance automation and AI‑enabled quality capabilities, mentor QA engineers, and ensure consistent adoption of quality standards across multiple Agile teams.
What You’ll Do QA Leadership & Strategy- Own and lead the train‑level QA strategy for the Claims & Money Movement portfolio, ensuring alignment with Service Experience and enterprise quality standards.
- Serve as the primary QA lead for the CAMM train, influencing solution design, delivery approach, and release readiness from a quality and risk perspective.
- Define, implement, and evolve the test automation and quality engineering strategy, including regression, integration, API, and data validation testing.
- Champion AI‑assisted testing capabilities, such as intelligent test generation, predictive defect analysis, self‑healing automation, and test optimization.
- Establish and enforce quality governance, standards, and best practices across multiple Agile delivery teams.
- Partner with Tech and Solution Leads to plan capacity, manage dependencies, and mitigate quality and delivery risks.
- Provide technical, delivery, and career mentorship to QA engineers and leads across the train.
- Lead the creation and execution of train‑level test strategies and plans, including environment readiness and automation coverage.
- Lead API and integration testing using tools such as Postman, SOAP UI, or equivalent.
- Oversee end‑to‑end testing, including functional, regression, system integration, performance, and release testing.
- Review and approve team‑level test plans and automation approaches to ensure coverage of business, regulatory, and non‑functional requirements.
- Introduce and scale AI‑driven QA capabilities, including:
- Intelligent test case generation and prioritization
- Defect trend analysis and predictive quality insights
- Test optimization to reduce execution time and manual effort
- Self‑healing or adaptive test automation where applicable
- Partner with engineering and architecture teams to embed quality signals into CI/CD pipelines.
- Continuously evaluate emerging tools and techniques to improve test effectiveness, speed, and confidence.
- Own the defect management lifecycle at the train level, ensuring clear prioritization, root cause analysis, and timely resolution.
- Lead cross‑team defect triage and troubleshooting for complex, multi‑system issues.
- Ensure quality practices support financial accuracy, auditability, and regulatory compliance for claims and money movement.
- Proactively identify quality risks and define mitigation strategies ahead of releases.
- Act as a key quality partner to Product, Business, and Technology stakeholders.
- Provide clear, data‑driven quality reporting, including defect trends, automation coverage, risk posture, and release readiness.
- Participate in ART / train ceremonies, PI planning, retrospectives, and release reviews.
- Track and communicate quality metrics to drive continuous improvement.
- Identify and implement opportunities to reduce cycle time and manual testing through automation and AI.
- Support and guide User Acceptance Testing (UAT) in partnership with business stakeholders.
- Share best practices, tools, and techniques across the Service Experience QA community.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
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