AI Quality Engineering Lead
Role At StarCompliance, we build software that supports critical compliance needs for global clients. AI
Overview
Role
At StarCompliance, we build software that supports critical compliance needs for global clients. AI is now a core capability within our platform, embedded directly into our products and services.
We are looking for an experienced AI Quality Engineering Lead to drive modern, automation-first quality engineering across our global engineering organisation. This highly technical leadership role will focus on AI-assisted testing, agentic engineering, automation strategy, performance validation, and release confidence across cloud-native and legacy platforms.
This is not a traditional QA management position. You will partner closely with Engineering, Architecture, DevOps, Product, and Release Management teams to embed quality throughout the software development lifecycle and enable scalable, continuous delivery.
How We Think About AI
At StarCompliance, AI is a core part of how we build and operate modern SaaS platforms.
We expect our engineers to:
- Use AI-assisted engineering tools in daily workflows.
- Apply AI to improve development speed, automation, operational insight, and engineering quality.
- Ensure AI-generated outputs remain secure, compliant, auditable, and reliable.
Key Responsibilities
AI & Agentic Quality Engineering
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Lead adoption of AI-assisted testing tools and agentic engineering workflows.
-
Design and implement autonomous and semi-autonomous testing agents.
-
Develop best practices for AI-generated testing, intelligent validation, and automated quality analysis.
-
Enable engineering teams to embed AI-driven quality practices into day-to-day delivery.
Platform & Release Quality
-
Own release quality strategy across products and services.
-
Build scalable end-to-end, integration, and regression testing approaches.
-
Improve release confidence through automation, telemetry, and quality intelligence.
Performance & Scalability Testing
-
Define and execute performance, load, stress, and scalability testing strategies.
-
Validate reliability across distributed and high-volume environments.
-
Identify bottlenecks and support engineering teams in improving platform resilience.
Quality Engineering Enablement
-
Establish frameworks and standards for modern quality engineering.
-
Partner with development teams to strengthen automation and quality ownership.
-
Mentor engineers in automation, AI-assisted testing, and agentic engineering practices.
Metrics & Quality Intelligence
-
Define meaningful quality metrics aligned to operational and customer outcomes.
-
Build dashboards focused on release health, reliability, and platform performance.
-
Use data-driven insights to identify risks and drive continuous improvement.
Skills and Experience
- Strong background in Quality Engineering, Software Engineering, or SDET disciplines.
- Hands-on experience with automation frameworks and modern CI/CD pipelines.
- Experience implementing AI-assisted development or testing workflows.
- Knowledge of agentic systems, autonomous workflows, or AI-driven automation.
- Strong understanding of performance and scalability testing.
- Experience testing APIs, distributed systems, cloud-native platforms, and microservices.
- Excellent analytical, communication, and technical leadership skills.
Desirable Experience
- Experience within SaaS or regulated software environments.
- Knowledge of Azure cloud platforms and DevOps tooling.
- Familiarity with observability, telemetry, and production monitoring.
- Understanding of modern engineering metrics including DORA and release health indicators.
- Experience leading quality transformation initiatives.
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.
Role
At StarCompliance, we build software that supports critical compliance needs for global clients. AI is now a core capability within our platform, embedded directly into our products and services.
We are looking for an experienced AI Quality Engineering Lead to drive modern, automation-first quality engineering across our global engineering organisation. This highly technical leadership role will focus on AI-assisted testing, agentic engineering, automation strategy, performance validation, and release confidence across cloud-native and legacy platforms.
This is not a traditional QA management position. You will partner closely with Engineering, Architecture, DevOps, Product, and Release Management teams to embed quality throughout the software development lifecycle and enable scalable, continuous delivery.
How We Think About AI
At StarCompliance, AI is a core part of how we build and operate modern SaaS platforms.
We expect our engineers to:
- Use AI-assisted engineering tools in daily workflows.
- Apply AI to improve development speed, automation, operational insight, and engineering quality.
- Ensure AI-generated outputs remain secure, compliant, auditable, and reliable.
AI & Agentic Quality Engineering
Lead adoption of AI-assisted testing tools and agentic engineering workflows.
Design and implement autonomous and semi-autonomous testing agents.
Develop best practices for AI-generated testing, intelligent validation, and automated quality analysis.
Enable engineering teams to embed AI-driven quality practices into day-to-day delivery.
Platform & Release Quality
Own release quality strategy across products and services.
Build scalable end-to-end, integration, and regression testing approaches.
Improve release confidence through automation, telemetry, and quality intelligence.
Performance & Scalability Testing
Define and execute performance, load, stress, and scalability testing strategies.
Validate reliability across distributed and high-volume environments.
Identify bottlenecks and support engineering teams in improving platform resilience.
Quality Engineering Enablement
Establish frameworks and standards for modern quality engineering.
Partner with development teams to strengthen automation and quality ownership.
Mentor engineers in automation, AI-assisted testing, and agentic engineering practices.
Metrics & Quality Intelligence
Define meaningful quality metrics aligned to operational and customer outcomes.
Build dashboards focused on release health, reliability, and platform performance.
Use data-driven insights to identify risks and drive continuous improvement.
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