Software Test Engineering Manager (IGEN)

IGEN is seeking a Software Test Engineering Manager to lead and evolve our Quality Engineering function across all software products and platforms. This role is responsible for defining and executing a modern, automation-first, and AI-enabled quality strategy that ensures scalable, reliable, and high-performing SaaS solutions.

This individual will operate within a Microsoft-based technology ecosystem and Scrum-driven Agile model, partnering closely with Engineering, Product, Platform, and domain experts (tax advisors / logic experts) to ensure both technical quality and business logic accuracy.

The ideal candidate is passionate about driving continuous improvement, intelligent automation, and agentic testing capabilities, while ensuring logic fidelity, regulatory compliance, and customer trust in all product outputs.

The ideal location for this role is on-site in Appleton, WI for 4 days per week (Monday - Thursday). We may consider candidates in other areas of Wisconsin with a hybrid schedule of 1-2 days per week on-site in Appleton., Quality Strategy, Vision & Governance

• Define and execute a portfolio-wide Quality Engineering strategy across all IGEN software products
• Establish a quality-first culture where quality is embedded in design, development, and delivery
• Translate product risk, customer impact, and system complexity into measurable quality KPIs and release criteria
• Define and govern:
• Defect escape rate
• Test coverage across layers
• Release confidence scoring
• MTTR / MTTD

Microsoft & Platform Quality Engineering

• Lead quality engineering within a Microsoft-centric ecosystem, including:
• Azure-based SaaS platforms
• Azure DevOps / GitHub CI/CD pipelines
• .NET-based services and APIs
• Define best practices for testing in:
• Distributed cloud environments
• Identity-enabled systems (Entra / IAM)
• Ensure QA is deeply integrated into platform engineering practices

Scrum & Product Team Quality Ownership

• Embed QA into Scrum teams, ensuring quality ownership throughout the sprint lifecycle
• Define and enforce Definition of Done, including automation coverage and quality gates
• Influence:
• Sprint planning (test strategy and risk)
• Backlog refinement (testability and acceptance criteria clarity)
• Ensure product teams deliver with clear accountability for quality outcomes

Logic Validation & Domain Quality (Critical for IGEN)

• Partner closely with logic experts (tax advisors and domain specialists) to validate:

• Business rules
• Regulatory logic
• Calculation accuracy and scenario coverage

• Establish structured processes for:

• Logic validation testing (rule-based and scenario-driven testing)
• Domain test case design tied to real-world client scenarios
• Business acceptance validation beyond functional correctness
• Ensure software quality includes confidence in both technical performance and domain correctness
• Drive traceability between:
• Requirements * rules * test coverage * expected outcomes

AI & Agentic Quality Engineering

• Lead adoption of AI-driven and agentic QA capabilities, including:
• Autonomous test generation from requirements and user stories
• AI-assisted test maintenance and self-healing automation
• Intelligent identification of coverage gaps
• Establish governance for AI-generated testing and validation outputs
• Drive evolution toward autonomous QA systems capable of adaptive testing at scale

Test Architecture & Automation Strategy

• Define and own the enterprise test architecture, including:
• UI, API, integration, contract, and end-to-end testing
• Build and scale modular, reusable automation frameworks
• Integrate automated testing into CI/CD pipelines with:

• Automated quality gates
• Real-time feedback loops
• Drive best practices:
• API-first testing
• Test data management
• Service virtualization
• Test stability and flakiness reduction

DevOps, CI/CD & TestOps Integration

• Embed quality engineering into CI/CD pipelines (Azure DevOps / GitHub Actions)
• Implement TestOps practices with continuous quality monitoring
• Drive shift-left and shift-right quality strategies:
• Early validation within development
• Production validation via telemetry

Observability & Production Quality

• Leverage logs, metrics, and traces for production quality validation
• Implement:
• Synthetic monitoring
• Release validation strategies
• Establish feedback loops from production insights into:

• Defect analysis
• Risk prioritization
• Backlog improvements

Leadership & Team Development

• Lead, mentor, and develop QA Engineers, SDETs, and automation specialists
• Act as a player-coach, contributing to design and technical implementation
• Build organizational capability in:

• Automation engineering
• AI-enabled QA
• Cloud-native testing
• Foster a culture of shared ownership of quality across engineering teams

• Strategic thinker with ability to balance speed, risk, and quality
• Strong communication skills across technical and business stakeholders
• Ability to lead in a fast-paced, Agile environment
• Excellent problem-solving and decision-making skills
• Passion for innovation and continuous improvement
• Lives IGEN values:

• High Performance
• Caring Relationships
• Strategic Foresight
• Entrepreneurial Spirit
• Champions efforts to Find a Better Way through innovation and optimization, Required:

• Bachelor's degree in Computer Science, Engineering, or equivalent experience
• 5+ years of experience in QA, automation, or SDET roles
• 3+ years in a leadership role
• Strong experience with:

• Test automation frameworks (Selenium, Playwright, Cypress, etc.)
• API and integration testing
• CI/CD pipelines (Azure DevOps, GitHub Actions)

• Experience working in Scrum-based Agile environments
• Programming experience (C#, JavaScript, Python, or Java)
• Experience with cloud-native SaaS architectures (Azure preferred)

Preferred:

• Experience with AI-driven or agentic QA approaches

• Experience with:

• Performance testing tools

• Observability platforms

• Experience integrating security testing and SCA tools

• Experience working with domain-heavy systems requiring logic validation (e.g., tax, regulatory, or rules-based platforms)