IT Portfolio Architect Testing

Define and drive the enterprise strategy for testing and verifying cloud-native platforms and services, including infrastructure, Kubernetes workloads, APIs, microservices, and event-driven architectures, ensuring quality and reliability from local development through production.

Leverage deep AWS and Red Hat OpenShift (ROSA)/Kubernetes expertise to design testing and verification approaches for cloud-native architectures, including cluster and workload testing, infrastructure-as-code validation, service mesh and network policy testing, autoscaling and failover verification, and cloud configuration and compliance validation.

Evaluate and adopt appropriate third-party testing tools and platforms, including contract testing, chaos engineering, synthetic monitoring, security and compliance scanning, and test data management solutions, and architect or build internal services where suitable solutions do not exist.

Design reference architectures and enterprise standards for automated testing, including unit, integration, contract, end-to-end, performance, resilience, and security testing, that scale across multiple application teams and AWS environments.

Partner with the CCoE (Cloud Center of Excellence) and Enterprise Architecture teams to embed testing and verification standards into golden paths, DevOps pipelines, and platform engineering templates.

Architect and develop supporting services, APIs, and microservices to address gaps in the enterprise testing and verification toolchain, leveraging AWS and Kubernetes platforms.

Establish enterprise standards and guardrails for test coverage, quality gates, non-functional testing, and release-readiness criteria, and guide architects and delivery teams on adoption.

Serve as a key technical leader on cross-functional initiatives requiring the integration of testing and verification capabilities with CI/CD platforms, cloud infrastructure, container platforms, and observability solutions.

Architect solutions with a strong focus on non-functional requirements, including scalability, reliability, availability, observability, fault tolerance, security, and maintainability.

Champion a culture of software craftsmanship through Test-Driven Development (TDD), Behavior-Driven Development (BDD), Continuous Integration/Continuous Delivery (CI/CD), and shift-left quality practices across the enterprise.

Design AI-native testing and validation approaches, including per-change validation, isolated and ephemeral environments, and automated verification pipelines, that scale to the pace and volume of AI-generated code, not just human-authored changes.

Define enterprise architectures and standards for AI-native testing, including agent-driven test generation, automated verification, workflow orchestration, synthetic data management, test environment provisioning, quality governance, and human-in-the-loop validation.

Create and maintain architecture documentation, system diagrams, technical decision records, implementation guidance, and operational standards.

Participate in Agile ceremonies, including sprint planning, stand-ups, retrospectives, and hackathons, and contribute to the enterprise GenAI working group, including AI-assisted test generation and closed-loop verification for AI coding agents.

Advise engineering leaders, architects, and delivery teams on testing strategy, tool adoption, modernization initiatives, and migration approaches.