Software QA Specialist

Marsh McLennan•Louisville, KY

1d•Hybrid

About The Position

We are seeking a talented individual to join our team at Marsh. This role will be based in Louisville. This is a hybrid role that has a requirement of working at least three days a week in the office. We are seeking a Specialist - IT Quality Assurance to join our IT Quality Assurance team. This role will be an experienced individual contributor focused on functional, automation, data testing, and modern AI-assisted testing practices to ensure product and data quality across enterprise applications, APIs and data pipelines. The Specialist will work closely with development, product, and data teams to design and execute test strategies that validate both application behavior and data integrity.

Requirements

Experience of testing software across a variety of languages, technologies, and platforms.
Hands-on experience using Generative AI for testing and validating AI/ML models, including automation for AI-powered applications.
Skilled in collecting, processing, and assessing data quality; validating and provisioning test data for AI frameworks and pipelines.
Strong communicator and team leader who collaborates effectively with technical and non-technical stakeholders across cross-functional teams.
Experience with Agile-at-scale, Lean and continuous delivery practices (CI, TDD, Infrastructure as Code) and proven ability to design and implement automation frameworks.

Nice To Haves

Strong understanding of Test Engineering and Quality Assurance best practices, tools and policies.
Experience in automation tools and configuring test frameworks (Ex: VS Code IDE, Java, TypeScript, WebDriverIO, Playwright, etc…).
Involvement in test environment setup.
Understanding of CI/CD and DevOps practices
Experience in Salesforce or Informatica testing
Experience as a Scrum Lead or similar capacity

Responsibilities

Own and implement the Pod-wide test automation strategy (CI/CD, automation pyramid/shift-left, frameworks and tooling) and ensure consistent adoption across all squads for functional and non‑functional testing (performance, security, compatibility, accessibility).
Lead testing of AI/GenAI business applications and embed GenAI capabilities into test tooling and utilities (AI-driven insights, optimization, code refactoring, comparisons, migrations).
Define, federate, and continuously improve built‑in quality practices, standards, and methods (RCA, stage containment, code quality) so squads deliver consistent, high‑value outcomes aligned to Pod and global approaches.
Collaborate with Pod and squad leads, Product Owners, and operations to align quality objectives with PI/resourcing plans, skills profiles, supplier training needs, and global KPIs.
Drive process improvement and innovation to increase quality, velocity, and efficiency (closer alignment to business acceptance, automation enhancements, tooling upgrades).
Provide timely, actionable QA reporting and dashboards (test coverage, defect trends, leakage, metrics) enabling Pod leads and stakeholders to monitor quality and make data‑driven course corrections.