
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Remote - United States"), this listing's salary midpoint is about 35% higher. The offer still falls within the benchmark range (€1,667–€20,050). The listed pay band (€12,363–€16,963) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 7 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Quality Engineer | €2,720/per month | €4,250/per month | €5,500/per month |
| All roles in Remote - United States | €1,667/per month | €11,003/per month | €20,050/per month |
| From job ad (Senior) | €12,363/per month | €14,663/per month | €16,963/per month |
As we transition into an AI-First Operating Model and move from exploration into execution at scale, we are seeking a Staff Quality Engineer to join our AI Platform team and serve as a strategic catalyst for this shift. In this high-impact role, you will be accountable for architecting the quality standards that underpin our next generation of market intelligence. Your remit is to define how we build, test, and operate in an AI-centric ecosystem. You will lead quality initiatives that ensure our engineering workflows—covering everything from complex data pipelines and AI model validation to system observability and agentic search interactions—are robust, scalable, and AI-boosted. You will be a key leader in establishing "AI-First" as our standard operating procedure, defining the quality gates that enable us to deliver state-of-the-art market intelligence with confidence and precision at scale. Who You Are: - Fluency with AI tools and a proven track record of enabling AI tools to accelerate software delivery and processes. - Deep knowledge in at least one of the following programming languages: Kotlin, Python, JavaScript, or Java - Proficiency in testing methodologies and deep understanding of the QA domain and theory - Great experience with Test Management Systems (e.g., Allure TestOps) - Excellent test design skills and experience in API testing - Experience with any UI test automation framework - Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes) - Strong understanding of continuous delivery - Strong communication skills and ability to collaborate with stakeholders Bonus points if you have: - Experience in setting up and configuring CI/CD tools and pipelines - Good understanding of GraphQL - Proven expertise in Performance Engineering (using k6 or similar) and Observability (OpenTelemetry/Grafana) to drive data-informed quality decisions - Experience with AI/ML model evaluation and test data management for non-deterministic systems - BS/MS degree in a relevant technical discipline such as Computer Science, Engineering, or Information Technology What You’ll Do: - Define and drive the long-term testing strategy and quality culture for the AI Platform, emphasizing "Quality by Design" and "Automation by Default." - Define quality metrics and coverage standards, partnering with product and engineering teams to ensure data-driven, measurable, and self-sustaining quality outcomes. - Grow test coverage through scalable, domain-specific automation and define/maintain complex test datasets, partnering with developers to ensure automation readiness. - Guide and support test planning for new features, ensuring alignment with acceptance criteria and coverage across unit, integration, and E2E layers. - Continuously improve and streamline testing processes; perform targeted exploratory testing to discover risks, inform automation, and validate model outputs. - Coach and mentor engineers on sustainable, scalable quality practices, serving as a strategic partner to ensure delivery standards are met through rigorous release gates.
Job Details
Responsibilities
- Define and drive long-term testing strategy and quality culture for AI Platform
- Establish quality metrics and coverage standards
- Grow test coverage via scalable, domain-specific automation
- Maintain complex test datasets
- Guide test planning for new features across unit, integration, and E2E layers
- Perform targeted exploratory testing to discover risks and validate model outputs
- Coach and mentor engineers on sustainable quality practices
Requirements
- Fluency with AI tools to accelerate software delivery
- Deep knowledge of Kotlin, Python, JavaScript, or Java
- Proficiency in testing methodologies and QA theory
- Experience with Test Management Systems (e.g., Allure TestOps)
- Excellent test design and API testing skills
- Experience with UI test automation frameworks
- Experience with cloud platforms (AWS, GCP, or Azure) and Kubernetes
- Strong understanding of continuous delivery
- Strong communication and collaboration skills
Skills & Technologies
Education Level
BachelorBenefits & Perks

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