Sr. Software Engineer in Test (SET)

Ingram Micro•Greer, SC

About The Position

Accelerate your career. Join the organization that's driving the world's technology and shape the future. Ingram Micro is a leading technology company for the global information technology ecosystem. With the ability to reach nearly 90% of the global population, we play a vital role in the worldwide IT sales channel, bringing products and services from technology manufacturers and cloud providers to business-to-business technology experts. Our market reach, diverse solutions and services portfolio, and digital platform Ingram Micro Xvantage™ set us apart. Learn more at www.ingrammicro.com Come join our team where you’ll make technology happen in surprising ways. Let’s shape tomorrow - it’ll be a fun journey! We are seeking a highly motivated Sr. Software Engineer in Test (SET) to drive quality engineering excellence through modern test automation, AI-enabled testing practices, and continuous quality innovation across enterprise platforms and applications.

Requirements

Bachelor's degree in computer science, or relevant science and math disciplines with an IT emphasis is required.
5 + years functional experience including a minimum of 3 years position specific experience.
Ability to make significant contribution to processes and systems.
Strong experience in Quality Engineering and Test Automation within Supply Chain domains, including Order Management, Procurement, Inventory, Warehouse Management, Logistics, Transportation, Fulfillment, and Returns.
Expertise in designing and implementing scalable automation frameworks using Playwright, Selenium, Cucumber, REST Assured, Appium, and TestNG.
Hands-on experience testing enterprise platforms and integrations, including SAP, Oracle, Dynamics, WMS, TMS, OMS, and EDI/B2B solutions.
Proven ability to automate complex business processes such as Order-to-Cash (O2C) and Procure-to-Pay (P2P) and integrate testing into CI/CD pipelines.
Experience applying AI-driven testing capabilities, including test generation, intelligent test selection, self-healing automation, and quality engineering innovation.
Strong knowledge of Agile, Scrum, BDD, TDD, DevOps, and Continuous Testing practices.
Experience validating cloud-native applications on AWS, Azure, Kubernetes, Docker, and Cloud Foundry platforms.
Proficiency with observability and monitoring tools such as Grafana, Kibana, and Elasticsearch.
Demonstrated leadership in mentoring teams, conducting code reviews, driving quality best practices, and leading continuous improvement initiatives.

Responsibilities

Demonstrate understanding of end-to-end Supply Chain business processes including Order Management, Procurement, Inventory Management, Warehouse Management, Logistics, Transportation, Fulfillment, Returns Management, and Customer Delivery.
Design and execute automation strategies for mission-critical supply chain platforms supporting high-volume order processing, inventory visibility, shipment tracking, and fulfillment operations.
Ensure quality validation of integrations across enterprise supply chain systems including in depth in one of the following : ERP platforms (SAP, Oracle, Dynamics) Warehouse Management Systems (WMS) / Transportation Management Systems (TMS) Order Management Systems (OMS) EDI and B2B integration platforms
Develop automated test solutions for complex supply chain workflows including: Order-to-Cash (O2C) Procure-to-Pay (P2P)
Design and develop scalable automation frameworks using modern technologies including Playwright, Selenium, Cucumber, REST Assured, Appium, and TestNG.
Build reusable automation libraries, utilities, and accelerators for UI, API, integration, and end-to-end testing.
Develop test tools, mock services, test data generators, simulators, test beds, and other quality engineering infrastructure components.
Ensure automation solutions are maintainable, scalable, and integrated into CI/CD pipelines.
Champion adoption of AI-powered testing and automation capabilities across engineering teams.
Implement AI-assisted test generation, intelligent test selection, self-healing automation, test data generation, and defect prediction capabilities.
Leverage Generative AI and engineering copilots to improve test coverage, accelerate automation development, and increase engineering productivity.
Evaluate emerging AI-enabled quality engineering tools and drive innovation initiatives across the organization.
Collaborate closely with Product Owners, Architects, Business Analysts, and Development teams to define quality strategies and test approaches.
Participate in sprint planning, estimation, backlog refinement, and release planning activities.
Foster and maintain Behavior-Driven Development (BDD) and Test-Driven Development (TDD) practices.
Plan, execute, and manage sprint-based testing cycles in Agile and Scrum environments.
Integrate automated testing into CI/CD pipelines and release management processes.
Support Release Automation and Deployment Automation across multiple application environments.
Enable continuous quality measurement through continuous integration and continuous testing practices.
Partner with DevOps teams to improve deployment confidence and release quality.
Support testing and quality validation of cloud-native applications and distributed systems.
Implement testing strategies for applications deployed on AWS, Azure, Cloud Foundry, Kubernetes, and Docker platforms.
Utilize monitoring, logging, dashboarding, and analytics tools such as Grafana, Kibana, and Elasticsearch for quality analysis and operational insights.
Monitor quality metrics, test effectiveness, automation coverage, and production quality trends.
Conduct automation code reviews and ensure adherence to engineering standards and best practices.
Mentor and coach team members on automation technologies, domain knowledge, quality engineering principles, and emerging technologies.
Drive continuous improvement initiatives and quality transformation programs across teams.
Research new tools, frameworks, and technologies and recommend strategic adoption opportunities.
Refactor legacy applications to improve testability and support unit, integration, and end-to-end testing.