QA Engineer

From disconnected data to confident, explainable decisions

data² delivers trustworthy, explainable AI (eXAI) that automates critical workflows and turns complexity into clarity. Our patented, hallucination-resistant eXAI reView platform harmonizes data across your ecosystem delivering real-time actionable insights.

Job Description

reView is a microservices backend over a graph data layer. Correctness in our system depends not just on API behavior, but on whether data is correctly structured, linked, and queryable across services. In a regulated-industry product, the difference between a result that runs and a result that is right is the entire value of the platform.

Concrete examples of what that means in practice:

• Did the right nodes and relationships get created across multiple services?
• Does a multi-step query return the correct result, not just a plausible one?
• Are data integrity guarantees holding under realistic load and failure conditions?

If testing API contracts and data integrity across a graph sounds interesting, this role is designed for that.

Scope

• Backend and data-focused testing (not UI-heavy)
• Integration and workflow correctness over broad end-to-end coverage
• Deeper performance and full-system validation evolve over time
• Embedded with the platform team, pairing closely with backend engineers
• Local and test environments are containerized (Docker-based), with shared staging for integration validation

Leveling

At the mid level, you will execute and extend an evolving test strategy. At the senior level, you will shape that strategy and influence how the platform is built for testability.

Requirements

API & Service Quality (Primary)

• Design and maintain automated tests for FastAPI services
• Validate request/response schemas, error handling, and auth flows
• Write tests across layers: unit tests (targeted handler-level validation), integration tests (service-level using test environments), and API-level smoketests against running services
• Prevent regressions across service boundaries

Integration & Workflow Testing (Primary)

• Validate behavior under realistic conditions (retries, partial failures, async flows)
• Ensure consistency of data across services

Data & Graph Validation (Targeted but Important)

• Verify correctness of node and relationship creation in Neo4j / Memgraph
• Validate key queries and multi-hop traversals against expected outputs
• Detect issues such as missing or incorrect relationships, duplicate entities, broken identity assumptions, and incorrect mappings during ingestion
• Define and evolve the approach to graph test fixtures (data seeding, isolation, repeatability)

End-to-End & Smoke Testing (Selective)

• Implement a small number of high-value end-to-end or API-level tests
• Focus on critical workflows rather than broad UI coverage
• Use pragmatic approaches (e.g., pytest-driven flows, containerized environments)

CI/CD & Quality Gates

• Integrate test suites into CI pipelines
• Define and enforce quality gates for merges and releases (coverage thresholds, integration test pass rates, graph-integrity checks)
• Maintain test reliability and reduce flakiness

Performance & Reliability (Shared)

• Run basic load and stress tests using standard tooling - e.g., recurring load tests to catch regressions in core ingestion and query paths
• Identify obvious bottlenecks in APIs and graph queries
• Collaborate with engineers on scaling behavior in Kubernetes

Debugging & Observability (Shared)

• Use logs and dashboards (Grafana + Loki) to investigate failures
• Trace issues across services and data layers
• Help reproduce production issues locally and in test environments

Qualifications

• Experience testing backend systems (APIs, microservices)
• Comfortable reading and writing production-quality Python (not just test scripts)
• Experience with pytest or similar frameworks
• Experience designing integration tests across services
• Experience working with CI/CD pipelines
• Comfortable working in systems where requirements are incomplete and tests help define expected behavior
• Strong written and spoken English skills for cross-border collaboration

Preferred (Not Required)

• Experience with FastAPI or similar Python frameworks
• Experience working in Kubernetes or distributed systems
• Experience testing data pipelines or ETL workflows
• Familiarity with graph or query-based systems (e.g., Neo4j, Memgraph, SQL, Cypher)