Senior QA Engineer

Cross River; Barcelona; Presencial; EUR 50.000 - 70.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Ongoing learning and development opportunities

Retirement planning

Charitable donation matching

Employee development fund

Monthly happy hours

Free haircuts at HQ

Complimentary dry cleaning at HQ

Valet parking at HQ

Gym located at HQ

Shuttle service to/from NYC

Descripción de la vacante

Cross River is seeking a Senior QA Engineer to join their Card Processing team in Barcelona. In this role, you will design quality systems that ensure reliability of our payment platform, collaborating closely with software engineers to enhance their testing processes.

Ideal candidates will have 5+ years in software engineering, strong English skills, and a deep understanding of testing methodologies, CI/CD pipelines, and regulated environments. The position provides comprehensive benefits including ongoing development opportunities and a supportive work culture.

Responsabilidades

• Design and build quality systems for payment platform.
• Own sensor strategy for quality assurance.
• Review PRs for test intent alignment.
• Improve E2E test suites for payment flows.
• Collaborate on quality strategy and risk prioritisation.

Conocimientos

Strong proficiency in English

Experience testing RESTful APIs

Strong analytical thinking

Excellent communication skills

5+ years in software engineering

Comfort with regulated environments

Demonstrated AI fluency

Proficiency in Go

Understanding of failure modes in distributed systems

Experience using observability platforms

Knowledge of Domain-Driven Design (DDD)

Descripción del empleo

Responsibilities

• We are seeking a Senior QA Engineer to join our Card Processing team
• You will design and build the quality systems that keep our payment platform reliable at scale - in an environment where new code is produced using AI tooling and judgment is the bottleneck, not generation speed
• This is not a traditional “write and execute test cases” role
• We believe software engineers own their tests — your job is to make them better at it
• You will own the sensor strategy that catches what AI gets wrong, verify that test intent matches business requirements, and raise the quality bar for the entire team
• Design and implement layered quality sensors across our CI/CD pipeline — from static analysis to AI-driven code review passes
• Improve and maintain E2E test suites for critical payment flows (card authorisation, clearing and settlement, tokenisation, 3D Secure)
• Review PRs for test intent alignment — ensuring AI-authored and human-authored code meets the same quality bar
• Identify test coverage gaps and prioritise them by risk (customer impact, regulatory exposure)
• Build load testing and performance validation frameworks
• Collaborate with the team on quality strategy — you raise the bar, you don’t gatekeep it
• Explore chaos engineering approaches to validate system resilience
• Contribute to audit-trail thinking — ensuring generated diffs and suppressed checks are traceable and defensible

Benefits

• Ongoing learning and development opportunities
• Retirement planning
• Charitable donation matching
• Volunteer opportunities
• Employee development fund
• Monthly happy hours
• Free haircuts in our salon located at HQ
• Complimentary dry cleaning at HQ
• Valet parking at HQ
• Shuttle service to/from NYC
• Gym located at HQ
• River Cafe at HQ

Qualifications

• Strong proficiency in English — written and verbal
• Familiarity with CI/CD pipelines, containerisation, and infrastructure-as-code
• Experience testing RESTful APIs and event-driven systems
• Strong analytical thinking — you pull bugs back to the spec, not just the code
• Excellent communication skills — this role enables and mentors, not just audits; you need to teach, not agitate
• 5+ years in software engineering with a strong focus on quality and testing (equivalence partitioning, boundary analysis, risk-based prioritization)
• Comfort with regulated environments — you think in terms of audit trails, blast radius, and data classification
• Demonstrated AI fluency — you use AI assistants daily, you know when they’re wrong, and you know when not to use them
• Proficiency in Go (or strong willingness to learn — test-design thinking matters more than language syntax)
• Understanding of failure modes in distributed systems (event ordering, retries, idempotency, eventual consistency)
• Experience using observability platforms (Datadog, New Relic, Elasticsearch, Grafana) to investigate issues and validate system behaviour
• Knowledge of Domain-Driven Design (DDD) — bounded contexts, ubiquitous language, aggregate boundaries