Summary / Purpose At Delta Air Lines, connection is at the heart of everything we do and guides our every action. We strive to welcome and care for all our customers during their travels with us and aim to deliver an elevated experience. Delta is focused on sustaining a strong IT operation, growing our capabilities, and maximizing optimization across each of our tech hubs to elevate the travel experience for our customers and empower our 90,000 Delta people. We’re committed to fostering innovation, and we’re excited to invite you to be part of our journey as we shape the future of technology at the world’s best airline! We are looking for a Cloud Architect with deep AWS and Red Hat OpenShift (ROSA)/Kubernetes expertise to make testing and verification a core enterprise discipline for how Delta builds and operates cloud services. The architect will provide technical leadership across application architecture, full-stack development, cloud engineering, DevSecOps, artificial intelligence, and agentic AI capabilities to advance enterprise testing and validation. This is an enterprise-level role, not a single-team role. You will work across architecture and platform engineering organizations to define how cloud services are tested and verified across the enterprise, from infrastructure, serverless, and Kubernetes workloads to the APIs and microservices running on top of them. The ideal candidate understands the gap between "it deployed" and "we know it works" and is passionate about closing that gap at scale. This individual will evaluate and adopt the right tools where appropriate, build services where needed, and establish the standards that make rigorous testing and verification the default. As AI coding agents increase the volume and speed of code changes, this role is also responsible for ensuring that verification practices scale accordingly. You will help define AI-native testing and validation approaches that provide teams with confidence in the quality, reliability, and security of code generated at the pace of modern AI-assisted development. Key Responsibilities - 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. Minimum Qualifications - 10+ years of software engineering, application development, cloud engineering, or platform engineering experience. - 3+ years in an Architect, Principal Engineer, Technical Lead, or similar technical leadership role. - Hands-on experience developing enterprise applications using Java, Python, TypeScript, JavaScript, or similar technologies. - Experience designing cloud-native solutions on AWS, Kubernetes/OpenShift, using microservices, APIs, and distributed architectures. - Strong knowledge of application architecture, DevSecOps, CI/CD, observability, security, and operational excellence. - Experience implementing automated testing and verification practices across applications, APIs, cloud infrastructure, and platforms. - Familiarity with test automation, API, contract, performance, resilience, and security testing practices. - Experience guiding development teams through architecture reviews, mentoring, and hands-on technical problem solving. - Understanding of test data management, synthetic data, and test environment strategies in enterprise environments. - Experience defining technical standards, reference architecture, and engineering roadmaps across multiple teams. - Bachelor’s degree in computer science, Engineering, Information Systems, or a related field, or equivalent experience. - Embraces diverse perspectives and inclusive collaboration. - Consistently prioritizes safety and security of self, others, and personal data. - Possesses a high school diploma, GED, or high school equivalency. - Is at least 18 years of age and has authorization to work in the United States. Preferred Qualifications - Experience delivering enterprise AI, generative AI, machine learning, or agentic AI solutions in production environments. - Experience with AI platforms and frameworks such as Amazon Bedrock, SageMaker, Strands, LangChain, LangGraph, Semantic Kernel, or similar technologies. - Experience with cloud modernization, platform engineering, developer experience, quality engineering, or enterprise automation initiatives. - Experience developing reusable platforms, reference implementations, shared services, or enterprise engineering frameworks. - Experience influencing architecture strategy and technology standards across a large organization. - Cloud, architecture, security, DevOps, or AI-related professional certifications. - Master’s degree in computer science, Engineering, Artificial Intelligence, or a related field. Benefits / Compensation (if stated) - Not stated (see full benefits list referenced on posting page) ---