Senior Software Development Test Engineer

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

Job Description

We are looking for a Senior QA Engineer / SDET to drive quality across our AI-native backend services and platform systems. You will own test automation strategy, release quality gates, and quality engineering practices — working closely with backend engineers (Java + Python), product managers, and platform architects. This role focuses heavily on validating hexagonal architecture adapters, Kafka event pipelines, multi-database correctness, and AI scoring model outputs.

Key Responsibilities

• Design, build, and scale automated test frameworks for Java microservices built on hexagonal architecture — with distinct test strategies for the domain core, adapter layers (MongoDB, PostgreSQL, Cosmos DB, Kafka, Elasticsearch, Redis/Aerospike), and external integrations.

• Develop and maintain comprehensive test suites: functional, integration (Testcontainers), regression, contract, and end-to-end across all adapter implementations.

• Validate Kafka event pipelines: consumer behavior, event ordering, idempotency, poison pill handling, and dead-letter queue processing.

• Validate MongoDB document integrity, PostgreSQL relational consistency, Cosmos DB partition correctness, and Elasticsearch index accuracy across service boundaries.

• Design and execute golden dataset test scenarios — seeding realistic dealer and customer data to validate scoring accuracy, suppression correctness, and attribution logic.

• Validate Python-based AI/ML service outputs: scoring model results, recommendation correctness, and LLM response safety gates.

• Collaborate closely with backend engineers and architects to embed quality early in hexagonal domain design and adapter implementation.

• Drive testability improvements by influencing API design, logging, observability, and error handling.

• Own release quality and go/no-go decisions by defining and tracking quality gates in CI/CD pipelines.

• Define and monitor quality metrics: test coverage, defect leakage, flakiness, MTTR, and automation ROI.

• Lead root cause analysis for productio