QA / Test Coordinator

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.

You will be:

• With 1. 5+ years of experience in Quality Assurance, with strong experience coordinating QA activities across complex delivery projects.
• Extensive experience coordinating customer-facing QA processes, acting as the primary QA point of contact between internal delivery teams, internal QA, and external testing providers.
• Ability to plan, prepare, and manage QA gate evidence required for formal quality reviews and delivery acceptance.
• Strong experience preparing and maintaining test evidence, including testbooks, coverage reports, static analysis results, execution records, and other quality-related documentation.
• Experience managing quality gates and ensuring that all required QA deliverables and evidence are complete, consistent, and ready for customer review.
• Skilled in maintaining consolidated deliverable registers and tracking QA dependencies that impact acceptance, release readiness, and invoicing milestones.
• Strong experience in Salesforce testing, including functional, regression, integration, and end-to-end testing of Salesforce-based solutions.
• Practical knowledge of static code analysis and quality tools such as SonarQube, Salesforce Code Analyzer, PMD, or similar solutions, with the ability to review and interpret their outputs.
• Designs and manages defect lifecycle processes using Jira or similar tools, including defect reporting, prioritization, triage, assignment, resolution tracking, re-testing, and closure.
• Experienced in coordinating defect triage across development teams, internal QA, and external testing providers to ensure clear ownership and timely resolution.
• Ability to analyze testing and defect results, identify recurring quality issues and risks, and ensure appropriate follow-up and corrective actions.
• Strong understanding of test evidence and documentation discipline, including traceability, versioning, completeness, and audit readiness.
  Deep understanding of Software Development Life Cycle (SDLC), release processes, and QA’s role in delivery governance and quality gates.
• Strong stakeholder management and communication skills, with the ability to clearly communicate quality status, blockers, defects, risks, and readiness to both technical and non-technical stakeholders.
• Ability to organize and coordinate QA activities across multiple parties while ensuring alignment with customer-defined QA processes, acceptance criteria, and delivery timelines.
• Constantly seeks improvements in QA governance, evidence preparation, defect management, and testing processes to increase delivery efficiency and quality.

Your profile also:

• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.

• Work from the European Union region and a work permit are required.

Nice to have:

• Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work.

• Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision