DDN - Principal Architect - Quality Engineering Framework

About the Role :

As Principal Architect for Quality Engineering Frameworks, you will own the technical vision, architecture, and evolution of Infinias pytestbased automation platform.

This role is responsible for transforming automation into a scalable, developer centric service that validates correctness, performance, resilience, and real world behavior across highly distributed systems.

This is a hands on, staff plus individual contributor role with broad organizational influence.

You will write and review production quality code, define architectural standards, and mentor engineers across QE and Development.

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 selfservice 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 S3compatible 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 baremetal systems.

- Validate cloudspecific 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 rootcause 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.