Test Automation Engineer
Role details
Job location
Tech stack
Job description
We're looking for an experienced Software Development Engineer in Test to build and maintain robust testing infrastructure for our AI-driven aviation solutions.
This is a hands-on, technical role - ideal for someone with a strong background in test automation, data engineering, and infrastructure setup, particularly in AI software environments. You understand the complexities of testing AI models, including benchmarks, regression suites, and data pipelines. And you're excited to ensure our products are reliable, scalable, and easy for the team to test and iterate on.
In this role, you'll drive test automation and data validation efforts, set up testing infrastructure, and collaborate with engineering teams to make testing seamless. You'll focus on regression testing, feature validation, and automating benchmarks for AI systems in aviation operations.
Tasks
Test automation support: Develop and maintain automated test frameworks to validate AI features and ensure high code quality.
Data testing and automation: Create, maintain, and run benchmarks for AI software; implement regular automated data validation pipelines to verify model performance and accuracy.
Data engineering tasks: Build and optimize data pipelines for testing datasets, ensuring clean, reliable data flows for AI evaluation.
Testing infrastructure setup: Design and deploy scalable infrastructure for running tests, including CI/CD integrations and cloud-based environments.
Regression and feature testing: Implement comprehensive regression suites and new feature tests; streamline processes to make it easier for the team to write, run, and debug tests.
Collaboration and knowledge sharing: Work with cross-functional teams to integrate testing best practices, document processes, and enable efficient testing workflows.
Requirements
4+ years of experience in software engineering, with a focus on test automation, data engineering, or AI/ML testing
Strong proficiency in testing tools and frameworks (e.g., pytest, Selenium, or similar) and data validation techniques for AI systems
Experience with data engineering practices, including ETL pipelines, SQL/NoSQL databases, and tools like Apache Airflow or dbt
Proven skills in infrastructure as code (e.g., Terraform, Docker, Kubernetes) for setting up testing environments
Familiarity with AI/ML workflows, including benchmarking models (e.g., using TensorFlow, PyTorch) and regression testing in dynamic environments
Exceptional problem-solving skills and the ability to thrive in fast-paced, collaborative settings
Experience in a remote-first, globally distributed team is a strong plus
Fluent in English
Self-starter with a passion for building reliable systems that support AI innovation
Benefits & conditions
True ownership & impact - Take real responsibility from day one. Your ideas, decisions, and work will directly shape our product, team, and company.
Global team, global mindset - Collaborate with an international crew across time zones and cultures. We believe the best ideas come from everywhere.
Fast growth, real development - We don't believe in waiting a year for feedback. You'll have structured development talks every quarter and real chances to grow with the company.
Startup at the right stage - We're early enough that your work makes a visible difference - and mature enough to support your success.
Radical transparency - We default to open communication, shared decisions, and high trust. No silos, no secrets.
A mission that matters - Help build AI that keeps aircraft flying safely and efficiently. This is tech with real-world impact, at global scale.
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