Principal Platform Architect, Quality Engineering

Job Description

A large media and entertainment client is building a next generation internal engineering platform and is seeking a Principal Platform Architect to lead the design of an AI enabled, self service quality platform for engineers.

This role is a hands-on platform engineering position, focused on building scalable internal platforms that modern engineering teams rely on. You will design systems that allow engineers to own their own testing, surface real time quality and release health signals, and reduce risk through AI assisted automation.

The platform will unify existing tools into a cohesive experience and initially support a team of 60 people, with the opportunity to expand across the broader organization.

Success in this role requires balancing strong technical architecture with real execution, close partnership with engineering and product leaders, and a commitment to shifting quality ownership to engineers using data driven insights.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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Skills and Requirements

15+ years of engineering experience, including 5+ years in senior platform or infrastructure architecture roles, owning high‑scale, low‑latency distributed systems (e.g., Golang/Java on AWS)

Proven success architecting and scaling internal engineering platforms used by multiple product teams, with clear ownership of CI/CD, test orchestration, quality gates, and observability

Hands‑on experience designing end‑to‑end quality frameworks across backend, frontend, data, and streaming environments, and transitioning organizations to developer‑owned quality models

Practical application of AI/ML in quality workflows, such as natural language test creation, self‑healing automation, failure classification, or intelligent test prioritization

Deep familiarity with modern testing and automation tools (e.g., Momentic, Mabl, Playwright, Appium, Postman) to enable automation at scale through platform integration

Strong coding and system ownership skills, including designing for scalability, telemetry, and release risk visibility

Exceptional cross‑functional communication and influence, with the ability to guide quality decisions, align stakeholders, and block releases when data indicates unacceptable risk Experience supporting high concurrency live environments

Familiarity with Git Hub Actions, test orchestration, and test data management platforms