Test Lead with Wealth Management exp.

Role: Test Lead with Wealth Management exp.

Location: New York, NY/Windsor, CT/Boston, MA (Hybrid 3 days onsite a week)

Position Summary:

·         We are seeking a highly experienced Test Lead - Wealth Management to establish and lead an enterprise-wide Quality Engineering and Testing Practice for large-scale Wealth Management transformation program. This role requires a strategic leader who can define end-to-end testing methodologies, implement AI-powered test automation frameworks, and drive collaboration across Business, Product, Engineering, Architecture, and Operations teams.

·         The ideal candidate will bring deep expertise in Wealth Management platforms and business processes, while creating a modern, scalable, AI-enabled testing ecosystem that accelerates delivery, improves quality, and reduces production risk across complex programs.

Responsibilities:

·         Quality Engineering & Test Practice Leadership

·         Build and lead an enterprise-wide testing and quality engineering practice for Wealth Management initiatives.

·         Define testing governance, operating models, standards, tools, KPIs, and best practices across multiple programs and portfolios.

·         Develop a long-term quality engineering roadmap aligned with business and technology transformation objectives.

·         Establish test management processes covering requirement validation, test planning, execution, defect management, reporting, and release readiness.

·         End-to-End & UAT Strategy

·         Design and execute comprehensive End-to-End (E2E), System Integration Testing (SIT), and User Acceptance Testing (UAT) strategies.

Define testing approaches across Wealth Management business capabilities including:

o            Client onboarding

o            Advisor platforms

o            Portfolio management

o            Asset allocation

o            Financial planning

o            Trading and execution

o            Performance reporting

o            Regulatory and compliance functions

·         Ensure complete business process validation across integrated applications and vendor platforms.

·         Establish business-led UAT frameworks and governance processes that improve stakeholder engagement and acceptance outcomes.

·         AI-Powered Test Automation Leadership

·         Define and implement an AI-driven automation testing framework that supports functional, regression, integration, API, and data validation testing.

Leverage Generative AI and intelligent automation tools for:

o            Automated test case generation

o            Requirement-to-test traceability

o            Test data creation

o            Defect prediction and analysis

o            Automated script maintenance

o            Test optimization and coverage analysis

·         Create a shift-left testing strategy by integrating AI-based testing capabilities into CI/CD pipelines.

·         Drive automation adoption across all testing phases to improve speed, coverage, and quality.

·         Program & Stakeholder Leadership

·         Act as the primary quality leader for large-scale transformation programs.

·         Facilitate strategic discussions between Business, Product Owners, Engineering, Program Management, and Executive stakeholders.

·         Translate business requirements into enterprise testing strategies and measurable quality outcomes.

·         Drive alignment between business expectations and technical implementation through structured test planning and validation activities.

·         Lead quality governance forums, steering committee discussions, and executive quality reviews.

·         Test Delivery & Execution Management

·         Manage multiple testing workstreams across geographically distributed teams.

·         Oversee test planning, resource management, environment readiness, execution tracking, and defect triage activities.

·         Implement risk-based testing models and quality gates across releases.

·         Drive release readiness assessments and go-live recommendations.

·         Monitor quality metrics and proactively identify program risks and mitigation plans.

·         Data, Integration & Non-Functional Testing

Establish strategies for:

o            Data validation and reconciliation

o            API and integration testing

o            Performance and scalability testing

o            Security and compliance testing

o            Production validation testing

·         Ensure data integrity across Wealth Management ecosystems and downstream reporting platforms.

·         Team Building & Capability Development

·         Build and mentor a high-performing Quality Engineering organization.

·         Define role-based competencies, career paths, and skill development plans.

·         Promote adoption of AI, automation, and modern testing practices across engineering teams.

·         Foster a quality-first engineering culture across delivery organizations.

Required Skills:

·         Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.

·         12+ years of experience in Quality Engineering, Software Testing, or Test Management.

·         5+ years leading enterprise-scale testing programs within Wealth Management, Asset Management, Investment Management, Brokerage, or Financial Services.

·         Proven experience establishing testing centers of excellence or quality engineering practices.

·         Extensive experience leading End-to-End, UAT, SIT, and Release Validation programs.

·         Strong stakeholder management experience with senior business and technology leaders.

·         Experience managing large distributed testing teams and vendor partners.

Required Wealth Management Domain Expertise

Strong understanding of:

·         Advisory and Wealth Management platforms

·         Investment products and portfolios

·         Managed accounts

·         Trading and investment operations

·         Financial planning solutions

·         Client servicing workflows

·         Regulatory and compliance controls

·         Performance measurement and reporting

·         Market data and investment analytics

Technical Skills:

·         AI-enabled Test Automation Platforms

·         Selenium, Playwright, Cypress, Tosca, or equivalent

·         API Testing (Postman, Rest Assured)

·         CI/CD Tools (Azure DevOps, GitHub Actions, Jenkins)

·         Test Management Platforms (Jira, Xray, Zephyr, ALM)

·         Cloud Platforms (Azure, AWS, Google Cloud Platform)

·         SQL and Data Validation Frameworks

·         Performance Testing Tools

·         GenAI applications for Quality Engineering and Test Automation

Success Metrics:

·         Increased automated test coverage across enterprise applications

·         Reduced regression testing cycle times through AI automation

·         Improved defect detection in earlier phases of delivery

·         Improved UAT success rates and business satisfaction

·         Faster release cycles with reduced production incidents

·         Establishment of scalable enterprise quality engineering operating model

·         Enhanced collaboration between Business and Engineering organizations