QA​/Test Coordinator Italian; Remote

Role overview

A remote QA/Test Coordinator role embedded in a large Salesforce delivery programme. The position focuses on test coordination, process improvement, documentation discipline, and QA governance across multi-party delivery work streams. Fluent Italian is required for stakeholder-facing communication.

• Coordinate end-to-end QA activities between internal delivery teams, internal QA functions, and external testing providers
• Plan, prepare, and manage the evidence package required for formal quality gates, customer reviews, and delivery acceptance
• Maintain structured test documentation, including testbooks, coverage reports, static analysis outputs, execution records, and audit-ready traceability
• Track QA dependencies through consolidated deliverable registers and tie them to acceptance criteria, release readiness, and invoicing milestones
• Run defect triage and own the full lifecycle in Jira, from reporting and prioritisation to assignment, re-testing, and closure
• Identify recurring quality issues and risks from test and defect trends, driving corrective actions and continuous improvement in QA governance

• 5+ years of QA experience with a strong track record coordinating testing across complex delivery projects
• Fluent Italian combined with strong stakeholder management and clear communication for technical and non-technical audiences
• Hands-on Salesforce testing background covering functional, regression, integration, and end-to-end scenarios
• Practical knowledge of static analysis and quality tools such as Sonar Qube, Salesforce Code Analyzer, PMD, or comparable solutions
• Solid understanding of the SDLC, release processes, and the role of quality gates in delivery governance
• Based in the European Union with a valid work permit

• Hands-on use of AI coding assistants (e.g., Claude Code, Git Hub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery
• Experience applying GenAI more structurally inside the SDLC, including defined workflows, prompt patterns, or embedded tool integrations
• Familiarity with emerging AI-driven practices such as agent-based workflows or AI-augmented development, with a willingness to experiment beyond standard approaches