Senior Quality Engineering & AI Test Lead - 20556/20543
Veritaz AB · Stockholm · 6 månader – upp till 12 månader · Deadline 2026-12-02
Veritaz AB is seeking a **Senior Quality Engineering & AI Test Lead** for a client consulting assignment focused on AI-accelerated system development and modernizing testing practices. Combining strategic direction with hands-on delivery, the role acts as a subject-matter expert across the testing domain without formal personnel responsibility. Core tasks include identifying practical uses for AI and Generative AI in quality assurance, directly supporting pilot teams with experimentation, and scaling AI-assisted ways of working across the software development lifecycle. The lead will also establish approaches for test automation, test environments, and test data, while coordinating alignment between delivery teams, shared functions, and management across complex technology landscapes. Candidates must have **senior-level Quality Engineering experience**, extensive background defining test strategies within large IT environments, and documented success leading through influence rather than formal authority. **Practical experience with AI and Generative AI** applied to software testing is required, alongside deep knowledge of the full SDLC, test automation, and CI/CD or DevOps pipelines. Practical programming or scripting experience is advantageous, as is familiarity with enterprise integration environments and leading Quality Engineering communities of practice.
Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Job Overview
Role Summary
Our client is seeking a Senior Quality Engineering & AI Test Lead for a consulting assignment focused on AI-accelerated system development and the advancement of testing and quality assurance practices. The role combines strategic ownership with hands-on delivery. You will serve as a subject-matter expert in testing and Quality Engineering, support pilot teams directly, and help develop and scale AI-assisted practices across the software development lifecycle.
You will provide direction and coordination across the testing domain, creating structure, alignment, and momentum across multiple teams and functions. The assignment does not include formal personnel responsibility; leadership is exercised through technical expertise, coordination, influence, and the ability to establish a shared direction.
Key Responsibilities
- Define and advance the strategic direction for testing, quality assurance, and Quality Engineering across multiple teams and functions.
- Identify practical opportunities to apply AI and Generative AI within software testing and quality assurance.
- Support pilot teams through hands-on experimentation, implementation, and evaluation of AI-assisted engineering practices.
- Develop and improve approaches related to test automation, test data, test environments, and quality analysis.
- Capture lessons and outcomes from pilot initiatives and convert them into shared, repeatable, and scalable ways of working.
- Assess the current state of testing and Quality Engineering, identify organizational needs, and prioritize development areas.
- Clarify responsibilities and interfaces between shared functions and delivery teams.
- Drive the transformation of testing and QA practices across complex technology environments without relying on formal authority.
- Promote collaboration and alignment between technical specialists, delivery teams, shared functions, and management.
- Challenge established practices constructively while maintaining a pragmatic focus on measurable progress.
Technical Stack & Requirements
- Quality Engineering: Deep expertise in building quality into engineering processes rather than treating testing as a separate final-stage activity.
- Test strategy and quality assurance: Extensive experience defining and evolving testing strategies in large, complex IT environments.
- AI and Generative AI: Practical experience applying AI technologies to software testing and Quality Engineering.
- Software Development Life Cycle: Strong understanding of the complete SDLC and how quality controls, feedback, and validation can be integrated throughout it.
- Test automation: Experience improving automated testing practices and enabling scalable quality assurance.
- CI/CD and DevOps: Strong understanding of modern delivery pipelines, DevOps practices, and contemporary development environments.
- Test enablement: Experience improving test data, test environments, and quality analysis capabilities.
- Coding or scripting: Practical programming or scripting experience is advantageous.
Qualifications & Experience
The successful consultant will have senior-level experience in Quality Engineering, test strategy, and quality assurance within large and complex IT environments. The role requires demonstrated experience developing or transforming testing and QA practices across multiple teams, together with the ability to move effectively between strategic planning and hands-on implementation.
Documented success in leading through expertise and influence without formal authority is essential. Experience working within large enterprise and integration landscapes is advantageous, as is experience establishing or leading Quality Engineering communities of practice. The role also requires the ability to create practical structure, communicate effectively with both technical specialists and management, and align diverse stakeholders around a common engineering direction.