We9re looking for a Quality Assurance Engineer to join our AI Product Org and build our quality function from the ground up. We operate a data-intensive visualization platform spanning web application, APIs, and data ingestion pipelines. You9ll be designing test strategy, building automation, establishing test case management, validating data correctness at scale, and using GenAI to work faster than a traditional QA team could. This is a 0-to-1 role for someone who wants to own quality end-to-end.
What You9ll Do:- Own the full testing lifecycle: test planning, execution, bug triage, and release verification.
- Design test plans/cases for our data ingestion pipelines, APIs, and analytics platform.
- Build automated test suites (Python, JavaScript, Playwright) covering frontend, backend, and data pipelines.
- Validate data correctness end-to-end - from raw ingestion through Parquet/Iceberg transformation to dashboards.
- Design and run stress/performance testing for high-volume data, APIs, and real-time charting.
- Set up test case management and coverage tracking (e.g., Testiny).
- Build CI/CD-integrated testing (GitHub Actions) across Kubernetes/AWS services, including Redis and SQL/analytical stores (DuckDB, etc.).
- Establish bug tracking and Hotfix verification processes for visibility across teams.
- Partner with engineering, product, and data teams to turn requirements into testable acceptance criteria.
- Review test automation code and enforce QA best practices.
What You Need:- 0-to-1 builder mentality - comfortable creating process and tooling where none exists.
- BS/MS in Computer Science or related field, or equivalent practical experience.
- 5+ years of QA engineering experience delivering scalable, reliable production software.
- Proficiency in Python, JavaScript, and test automation frameworks.
- Experience testing data pipelines and data-heavy applications.
- Working knowledge of SQL/relational databases to independently verify data correctness.
- Proven ability to design and execute stress/performance testing for APIs or data-intensive systems.
- Strong grasp of CI/CD, testing philosophy, and bug tracking practices.
- Experience with, or aptitude for, cloud-native infrastructure (AWS, S3, Kubernetes).
- Strong communication skills across technical and non-technical stakeholders.
Bonus Qualifications:- Experience validating data lake/lakehouse formats (Parquet, Apache Iceberg).
- Familiarity with DuckDB, Redis, or similar analytical/caching technologies.
- Experience testing data visualization layers (D3.js, Plotly, Grafana, or similar).
- Background in high-availability, real-time, or event-driven data systems.
- Experience using GenAI/LLM tooling to accelerate QA workflows (test generation, synthetic data).
- Familiarity with container orchestration and CI/CD tooling.
- Background in aerospace, especially flight test data analysis or aircraft health monitoring.
Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company9s business strategy. For this position we are targeting a base pay between $130,000 - $150,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.
