Lead Software Engineer, Quality Assurance / Test Automation / Agentic Systems

What you'll do

• Build and operate an agentic, human-gated testing ecosystem to accelerate test authoring, execution, and triage.
• Design and implement partner-facing integration validation using contract tests, stubs, and automated simulators.
• Develop deterministic test data, stable test environments, and integration simulations for the IAM stack.
• Set and run journey quality strategies to convert product intent into risk-based acceptance criteria and measurable outcomes.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
• Own the defect prevention loop by feeding failure patterns back into coverage, data strategies, and automation improvements.
• Report journey health and release posture to executives using evidence-based readiness reporting.
• Maintain a living journey map to continuously tune regression and performance testing scope based on production learnings.

What we're looking for

• Formal training or certification in software/quality engineering and software development in testing automation concepts.
• 5+ years of applied experience in software engineering and testing automation.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in one or more programming languages and frameworks such as Java, BDD suites, SQL, and Rest API.
• Proficiency in UI automation (Playwright/Selenium) and API testing with a track record of building stable, deterministic test suites.
• Experience building and operating MCP Servers/clients to connect LLM agents to tools like APIs, databases, and internal services.
• Demonstrated experience leading the use of approved AI-assisted software development tools for coding, code review, and troubleshooting.
• Proficiency in software applications and technical processes within a technical discipline such as cloud, AI, or machine learning (preferred).