Specialist, QA Test Automation
Role details
Job location
Tech stack
Job description
We aren't looking for an all-knowing AI guru to define our entire organizational strategy from scratch. We are looking for a sharp, curious Specialist, QA Test Automation who can bridge the gap between strategic vision and day-to-day technical execution. Working closely with the Chapter Lead, QA - who provides the overarching AI QA strategy-you will be embedded within Cogeco's AI squads to bring that strategy to life., * Embrace the Unpredictable: Implement and refine testing workflows tailored for AI powered solutions where outputs are probabilistic rather than deterministic.
- Regression & Drift Detection: Build guardrails to identify model drift, prompt regression, hallucination risks, and safety violations before they hit production., * Golden Datasets: Own the creation, maintenance, and scaling of high-quality golden datasets used as the source of truth for benchmarking model changes.
- AI Eval Tooling: Champion programmatic evaluation tools such as Promptfoo, DeepEval, or Ragas to automate the assessment of prompt variants and model performance.
Strategy Execution & Collaboration
- Chapter Alignment: Partner closely with the Chapter Lead, QA to translate high-level AI QA frameworks into actionable, daily tasks for technical teams.
- Feedback Loop: Provide real-time feedback to the Chapter Lead on how the strategy is performing in the trenches, recommending practical pivots based on real-world results., * Smart Pipelines: Collaborate with DevOps specialists to inject AI evaluation metrics directly into modern CI/CD pipelines, ensuring automated gates handle fluid AI responses.
- Data Validation: Validate data pipelines feeding our models, ensuring that data integrity is maintained from ingestion to inference.
Requirements
Do you have experience in Quality check automation?, In this role, you will move past standard "pass/fail" scripts to tackle the complex world of non-deterministic outputs. You will focus heavily on probabilistic testing, curating golden datasets, and leveraging cutting-edge LLM evaluation tools like Promptfoo. If you have a solid foundation in QA or software engineering, a healthy obsession with automation, and a restless drive to learn, you'll fit right in., * College diploma or Degree in Computer Science, Engineering, or a related discipline (or equivalent practical experience).
- The Right Mindset: A strong foundation in core QA principles combined with a passion for AI/ML. You don't need a PhD; you just need to be eager to learn how LLMs behave.
Work Experience & Technical Skills
- 3+ years of experience in Quality Assurance, Software Engineering, or Data Engineering.
- Hands-on Scripting: Experience in Python or JavaScript/TypeScript (essential for configuring evaluation frameworks like Promptfoo and manipulating test data).
- Modern QA Ecosystem: Experience with test automation frameworks, API testing, and code repositories (Git).
STRONG ASSETS
- Exposure to Golden Datasets: creating, maintenance, and/or scaling of high-quality golden datasets used as the source of truth for benchmarking model changes.
- Expsosure to AI Eval Tooling: Champion programmatic evaluation tools such as Promptfoo, DeepEval, or Ragas to automate the assessment of prompt variants and model performance.
- CI/CD Familiarity: Experience working with pipeline tools (e.g., Bitbucket pipelines, Google Cloud run, GitHub Actions, GitLab CI, Jenkins).
SPECIFIC COMPETENCIES
Technical Execution & Curiosity
- Analytical Deep-Dives: Comfortable analyzing data inputs/outputs and debugging prompts to identify the root causes of unexpected AI behavior.
- Tool Adaptability: Ready to quickly learn, test, and implement new open-source AI evaluation and observability tooling as the ecosystem evolves.
Growth Mindset & Adaptability
- Comfortable with Ambiguity: Thrives in a high-uncertainty environment where standard QA blueprints don't always apply.
- Execution Focus: Excel at taking an established roadmap or framework and running with it, troubleshooting technical blockers independently.
Collaboration & Communication
- Squad Partner: Able to communicate technical testing gaps clearly to both AI developers and product owners.
- Open to constructive criticism: Open to constructive feedback, willing to experiment, and values an environment where mistakes are treated as learning milestones.
Benefits & conditions
- Flexibility: Yes, we think that what you do matters. At work and at home.
- Fun: We laugh a lot, it makes every day brighter.
- Discounted services: We provide amazing services to our clients, and you'll get them at home, because you deserve them.
- Rewarding Pay: Let's be honest, everybody likes to make a good salary. We offer attractive compensation packages, and it comes with a great culture.
- Benefits: We've got you covered.
- Career Evolution: Join us and we will give you the tools to achieve your career goals!
- Technology: You have a passion for technology? Excellent, we do too. Here, you will manage, influence, play, create, fix, and shape the industry.
For candidates whose primary place of work will be in Massachusetts, the expected salary range for this position is $85 600 - $128 400. For candidates whose primary place of work will be in Cleveland, OH, the expected salary range is $77 800 - $116 800.
This range represents the annual salary or hourly wage that Breezeline expects to pay for this position at the time of this posting. Individual pay is determined by various factors, including but not limited to job-related skills, relevant experience, education, and specific work location.