About StarCompliance
StarCompliance is on a mission to make compliance simple and easy. Trusted globally by enterprise financial institutions, the user-friendly STAR platform empowers organizations to achieve regulatory compliance while safeguarding their integrity and business reputations. Through a customizable, 360-degree view of employee activity, the STAR software enables firms to automate the detection and resolution of potential areas of conflict while streamlining daily workflows and increasing efficiency.
Role
The Lead Platform Quality Architect is a senior, hands-on technical leader responsible for defining, architecting, and executing StarCompliance’s centralised Platform Quality Engineering strategy across the enterprise SaaS platform.
This role is the technical authority for platform-level quality assurance, including integration assurance, CI/CD quality gates, performance engineering, and enterprise-level release confidence. Reporting to the VP of Engineering, the Lead Platform Quality Architect leads a centralised team of highly skilled Platform Quality Engineers, while remaining deeply hands-on in architecture, framework design, complex automation scenarios, and performance engineering.
The role is accountable for translating quality strategy into executable architecture and measurable outcomes, ensuring that quality is engineered into the platform rather than inspected at the end. The Lead Platform Quality Architect owns the Staging environment as the primary platform integration and validation layer and plays a critical role in shaping how product teams design, test, and release software at scale.
As StarCompliance continues to treat AI as a foundational engineering capability, this role is also responsible for embedding AI-assisted Quality Engineering practices into platform-level tooling, automation strategy, and release governance in a controlled, measurable, and compliant manner.
This is a delivery-focused role requiring proven experience leading Quality Engineering functions in SaaS environments through both architectural design and hands-on execution.
How We Think About AI
At StarCompliance, AI is not a side experiment or an isolated specialist capability. We treat it as a foundational part of modern software engineering and SaaS platform development.
We expect engineers to:
- 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.
- Define, architect, and execute StarCompliance’s centralised Platform Quality Engineering strategy for the enterprise SaaS platform.
- Act as the technical authority for platform-level quality, including integration testing, CI/CD quality gates, performance assurance, and release governance.
- Build and lead a centralised team of Platform Quality Engineers, setting a high technical bar through hands-on involvement in architecture, automation frameworks, and complex quality scenarios.
- Design and maintain shared quality architecture and automation frameworks supporting cross-product integration and core enterprise user journeys.
- Own the Staging environment as the primary platform integration and validation layer, defining enterprise quality gates, release readiness signals, and go/no-go criteria.
- Embed automated quality controls and feedback loops directly into CI/CD pipelines (Azure DevOps).
- Define and execute the enterprise performance and scalability testing strategy in partnership with Architecture and Platform teams.
- Establish platform-level quality standards and guardrails for product teams, ensuring integration safety and release confidence while product teams retain feature-level quality ownership.
- Monitor and analyse quality metrics and trends across the platform, using data to identify systemic risks and drive continuous improvement.
- Lead the structured adoption of AI-assisted Quality Engineering practices, including AI-supported test generation, intelligent failure analysis, flake detection, performance anomaly identification, and risk-based test prioritisation.
- Define architectural guardrails for safe and compliant use of AI within Quality Engineering workflows.
- Represent Platform Quality Engineering in architecture forums and selected client, pre-sales, and audit engagements, articulating StarCompliance’s quality, performance, and AI-enabled assurance posture with technical credibility.
- 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.
Equal Opportunity Employer Statement
We prohibit discrimination and harassment of any kind based on race, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, gender identity or expression, marital/civil union/domestic partnership status, veteran status or any other protected characteristic as outlined by country, state, or local laws.
This policy applies to all employment practices within our organisation, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. StarCompliance makes hiring decisions based solely on qualifications, merit, and business needs at the time. For more information, please request a copy of our Equal Opportunities Policy.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
