starcompliance - Lead Platform Quality Architect

• Actively use AI-assisted engineering tools as part of their daily workflows. • Apply AI to improve design quality, development velocity, automation depth, operational insight, and overall engineering effectiveness. • Ensure AI-generated outputs are validated, auditable, and compliant with security, privacy, and regulatory standards. • Understand and manage the risks associated with AI use in regulated environments. • Adopt AI responsibly, pragmatically, and at scale in ways that strengthen engineering outcomes without compromising governance. • For Engineering, AI is a force multiplier - accelerating delivery, improving quality, enhancing diagnostic capability, and strengthening release confidence. It must be applied with architectural discipline and measurable impact. • Extensive hands-on technical experience in Quality Engineering, test architecture, or software engineering roles within complex SaaS platforms. • Proven experience defining and executing Quality Engineering strategy and architecture at platform scale. • Demonstrated experience leading centralised or platform-level Quality Engineering functions supporting multiple autonomous product teams. • Strong background in distributed systems, microservices, APIs, and enterprise integration patterns. • Deep, practical experience embedding quality controls into CI/CD pipelines and release workflows (Azure DevOps preferred). • Strong coding skills in one or more of C#, TypeScript, or Python, with experience building and maintaining automation frameworks (Playwright experience highly beneficial). • Proven experience designing and executing performance and scalability testing for enterprise SaaS platforms. • Demonstrated, hands-on experience applying AI-assisted engineering tools to achieve measurable improvements in automation coverage, defect detection, test reliability, or performance insight. • Working understanding of modern AI concepts (e.g., large language models, prompt engineering, model-assisted analysis, data sensitivity considerations) sufficient to design safe and scalable AI-enabled quality workflows. • Ability to define governance and guardrails for AI usage in regulated environments. • Ability to operate as a credible technical peer to senior engineers, architects, and platform leads. • Strong communication and influencing skills, with experience operating in cross-functional and client-facing contexts. • Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline, or equivalent practical experience. • Proven experience leading or architecting Quality Engineering at enterprise SaaS scale. • Practical, professional experience using AI-assisted engineering tools within software or quality engineering workflows. • Demonstrated experience operating in cloud-based environments (Azure preferred). • Relevant certifications in cloud platforms, performance testing, or quality engineering are beneficial but not required. • StarCompliance Background Checks • All positions require pre-employment screening due to employees potentially having access to highly sensitive and confidential information involving finance and compliance; candidates must be trustworthy and have a heightened sensitivity to protecting confidential financial, professional information.  To be eligible for employment with StarCompliance, candidates must undergo a rigorous background investigation with checks including, but not limited to, criminal record history, consumer credit, employment history, qualifications, and education checks.