Working Hours: Full overlap with MT
Location: Remote / LATAM

About the Team

Our client is building next-generation AI-powered clinical tools used by dental professionals across North America. Our products combine voice recognition, AI-assisted workflows, and clinical automation to improve the speed and accuracy of dental charting and documentation.

Current product areas include:

• AI Voice Scribe — real-time clinical transcription and note generation

• Voice Perio — AI-assisted periodontal charting through voice commands

• Voice Charting — hands-free clinical data entry integrated into dental workflows

This is a fast-moving engineering team working at the intersection of AI, voice technology, and healthcare software.

About the Role

We are looking for a highly technical Software Engineer in Test (SDET) to lead quality strategy for our AI voice and clinical products.

This is not a traditional QA role focused only on manual testing or UI automation. We are looking for someone who can think deeply about how to validate non-deterministic AI systems, build scalable automation frameworks, and define quality standards for products powered by speech recognition, LLMs, and NLP workflows.

You will be the first dedicated QA/SDET hire on the Innovation team and will play a critical role in shaping how quality is approached across both our internal engineering team and external development partners.

The ideal candidate combines strong automation engineering fundamentals with hands-on experience testing AI-powered systems such as conversational AI, transcription platforms, voice assistants, LLM features, or NLP workflows.

Responsibilities

AI & Voice System Testing

• Design and execute testing strategies for AI-powered voice and clinical workflows

• Validate speech-to-text accuracy, NLP/entity extraction, and AI-generated outputs

• Build approaches for evaluating non-deterministic systems, including hallucination detection, regression tracking, and model output validation

• Create and maintain benchmark datasets and evaluation methodologies for AI quality measurement

• Test real-world voice workflows involving accents, noisy environments, and clinical terminology

Automation Engineering

• Design, build, and maintain scalable automation frameworks and test infrastructure

• Develop automated functional, integration, regression, API, and performance tests

• Integrate automated testing into CI/CD pipelines and release workflows

• Improve test reliability, maintainability, and execution speed across environments

Quality Strategy & Ownership

• Define quality standards, risk-based testing strategies, and release criteria

• Establish metrics and monitoring approaches for AI quality and regression detection

• Partner closely with engineering and product teams to identify risks and improve release confidence

• Help shape quality processes across both internal and partner engineering teams

Collaboration

• Work closely with engineers, product managers, designers, and stakeholders throughout the development lifecycle

• Participate actively in sprint planning, refinement, reviews, and retrospectives

• Clearly communicate testing strategies, quality risks, and recommendations in written and verbal form

Required Qualifications

• 4+ years of experience as an SDET, Software Engineer in Test, or QA Automation Engineer

• Strong hands-on automation experience using frameworks such as Playwright, Cypress, Selenium, pytest, or similar

• Experience building or extending automation frameworks independently

• Strong programming skills in Python, JavaScript/TypeScript, Java, or C#

• Experience testing REST APIs and distributed systems

• Strong understanding of CI/CD pipelines and automated quality gates

• Excellent analytical and problem-solving skills

• Strong written and verbal communication in English

Preferred Qualifications

• Experience testing AI/ML-powered products or workflows

• Experience with conversational AI, transcription systems, voice assistants, chatbots, or NLP-based products

• Familiarity with LLM evaluation, AI output validation, regression detection, or prompt/workflow testing

• Experience testing cloud-based SaaS products and distributed systems

• Exposure to performance testing tools such as k6, JMeter, or Locust

• Experience working in healthcare or regulated software environments is a plus

• Familiarity with dental software or healthcare terminology is a plus

What We’re Looking For

Successful candidates typically demonstrate:

• Strong automation engineering depth

• Ability to reason about probabilistic/non-deterministic systems

• A thoughtful approach to AI quality validation

• Strong ownership mentality and initiative

• Clear communication and documentation skills

• Comfort operating in ambiguous, fast-moving environments