QA Architect - Storage

As a Principal Architect for Quality Engineering Frameworks at DataDirect Networks (DDN), you will have the opportunity to own the technical vision, architecture, and evolution of Infinias pytest-based automation platform. Your role will involve transforming automation into a scalable, developer-centric service that validates correctness, performance, resilience, and real-world behavior across highly distributed systems. **Responsibilities:** - **Framework Architecture** - Own the end-to-end architecture and technical direction of the Python/pytest automation framework. - Define architectural standards, extension points, and long-term evolution. - Make and document architectural tradeoffs through design reviews and Architectural Decision Records. - Ensure the framework scales with system complexity and organizational growth. - **Automation Platform and Reusable Tooling** - Design and implement reusable Python libraries, pytest fixtures, and plugins. - Provide a self-service automation platform with a clear, opinionated paved road for developers. - Enable testing of APIs, CLIs, storage systems, and distributed workloads using shared abstractions. - Maintain strict standards for determinism, readability, and maintainability. - **System Correctness, POSIX, S3, and Storage Validation** - Architect automation validating POSIX filesystem semantics, including metadata operations, locking, concurrency, permissions, and consistency. - Validate object, block, and networked storage systems including S3-compatible object storage, NVMe/iSCSI, and NFS/SMB. - Ensure correctness under failure scenarios, scale, and sustained load. - **Distributed Systems, Resilience, and Scale** - Design automation covering clustering behavior, membership changes, failover, and recovery. - Validate horizontal and elastic scaling in real deployment conditions. - Extend automation into repeatable resilience and chaos testing beyond simple failure injection. - **Performance and Stress Testing** - Integrate performance and stress testing into CI/CD pipelines. - Use tools such as fio, IOR, Minio Warp, Mongoose, and MLPerf. - Validate throughput, latency, and stability and continuously detect performance regressions. - **Cloud and Execution Environments** - Architect automation to execute consistently across AWS and GCP. - Support execution on Kubernetes, Docker, hypervisors, and bare-metal systems. - Validate cloud-specific behaviors including autoscaling, contention, networking variability, and zonal failure modes. - Balance execution scale, cost, and feedback time. - **Telemetry-Driven Validation** - Integrate automation with Grafana, Prometheus, and ELK. - Validate system behavior using metrics and logs in addition to test assertions. - Enable deep diagnostics and root-cause analysis from automated runs. - **Code Quality and Technical Leadership** - Lead code reviews for framework and automation contributions. - Enforce architectural and coding standards across the automation repository. - Act as a technical authority for test design and framework usage. - Mentor QE and Development engineers in Python, pytest, and automation architecture. This role at DDN offers the chance to work with cutting-edge technology and be part of a team of passionate professionals dedicated to innovation and customer success. If you are a driven professional looking to make a lasting impact in the world of AI and data storage, this position is an exciting and rewarding opportunity. As a Principal Architect for Quality Engineering Frameworks at DataDirect Networks (DDN), you will have the opportunity to own the technical vision, architecture, and evolution of Infinias pytest-based automation platform. Your role will involve transforming automation into a scalable, developer-centric service that validates correctness, performance, resilience, and real-world behavior across highly distributed systems. **Responsibilities:** - **Framework Architecture** - Own the end-to-end architecture and technical direction of the Python/pytest automation framework. - Define architectural standards, extension points, and long-term evolution. - Make and document architectural tradeoffs through design reviews and Architectural Decision Records. - Ensure the framework scales with system complexity and organizational growth. - **Automation Platform and Reusable Tooling** - Design and implement reusable Python libraries, pytest fixtures, and plugins. - Provide a self-service automation platform with a clear, opinionated paved road for developers. - Enable testing of APIs, CLIs, storage systems, and distributed workloads using shared abstractions. - Maintain strict standards for determinism, readability, and maintainability. - **System Correctness, POSIX, S3, and Storage Validation** - Architect automation validating POSIX filesystem semantics, including metadata operations, locking, concurrency, perm