AI Test Architect

Driven by the passion to improve quality of people’s lives, WS Audiology continues to grow as market leader in the hearing aid industry. With our commitment to increase penetration in an underserved hearing care market, we want to accelerate our business transformation in order to reach more people, more effectively.

We’re looking for anAI Test Architect to define, implement, and scale the next generation of quality engineering powered by AI. You will own thetest architecture strategy end-to-end—combiningLLM-driven automation,computer vision, andhardware-in-the-loop (HIL) systems—to deliver robust, scalable, and privacy-first testing formobile applications and hardware-integrated products.

This is a senior, hands-on architecture role: you’ll set the strategy, establish standards, lead technical decision-making, and build reusable platforms and frameworks while mentoring teams across QA, Dev, and DevOps.

What You’ll Do

1) AI Test Strategy & Architecture

• Define and maintain theenterprise test architecture, roadmap, and standards spanningfunctional, non-functional, integration, mobile, and HIL layers.

• Drive ashift-left andautomation-first culture; architect frameworks that are modular, resilient, and easy to evolve.

• Establishtest design principles, risk-based testing approaches, and coverage models aligned with business goals and compliance requirements.

• Lead architecture reviews and decision forums; evaluate build vs. buy for AI tooling and frameworks.

2) AI-Driven Test Innovation (LLMs, RAG, CV/OCR)

• Architect and implementRAG-based test generation usinglocal LLMs (e.g.,Ollama, llama.cpp) and frameworks likeLangChain/LlamaIndex to reason over requirements, app states, and logs.

• BuildAI agents that can: interpret acceptance criteria, propose and prioritize test scenarios, and auto-generate test cases/scripts.

• Developcomputer-vision andOCR pipelines (OpenCV, Tesseract, or equivalent) forprecise UI validation, visual diffing, andvisual regression analysis.

• Design models forUI anomaly detection, flakiness prediction, andself-healing locators beyond traditional Appium-style selectors.

• Automatelocalization testing for text, layout, and formatting across languages and screen sizes using AI.

3) Hardware-in-the-Loop (HIL) & Mobile Systems

• Define and evolve aPython-based HIL framework for end-to-end validation ofMobile/Desktop/WebApp interacting with hardware (e.g., medical devices, sensors, wearables).

• Architect communication interfaces (USB, Bluetooth, Serial) and test harnesses to control/observe device interactions reliably at scale.

• IncorporateAI-driven adapters that learn device behaviors, detect drift, and improve robustness of HIL scenarios over time.

• Partner with mobile teams (Android/iOS) to integrateAppium/Espresso/XCUITest/FlaUI where appropriate and augment with AI components.

4) On-Prem Infrastructure & MLOps for Test at Scale

• Designon-prem/private-cloud inference infrastructure forlow-latency, high-throughput model execution with strongdata privacy guarantees.

• Containerize models and agents (Docker) and integrate intoCI/CD (Jenkins, GitLab CI) for parallel execution andtest-on-commit workflows.

• Implementcontinuous learning loops to leverage test failures, telemetry, and labels toretrain andimprove models.

• Establish model lifecycle practices (versioning, evaluation, rollback, governance) using tools likeMLflow/Langchain, self-hosted vector stores, and caching.

5) Automation Platforms & Tooling

• Extend or replace traditional frameworks (e.g.,Appium) withAI-assisted components that enhance stability and coverage.

• BuildPython-based toolchains for model training/inference and integrations into test workflows; standardize reusablelibraries and templates.

• Define reference architectures forUI, API, performance, security, and resilience testing; ensure seamless observability, logging, and triage workflows.

6) Quality Governance, Metrics & Risk

• Definequality gates,entry/exit criteria, andrelease readiness bars; ensure compliance and privacy-by-design.

• Track and publishleading indicators andoutcome metrics—defect escape rate, test yield, visual regression detection rate, flakiness, mean-time-to-detect/triage, inference latency, infra utilization.

• Conductroot cause analyses and drive systemic fixes across tooling, test design, and pipelines.

• Audit processes for adherence to standards; champion continuous improvement.

7) Technical Leadership & Enablement

• Mentor QA engineers and SDETs on AI/ML testing, HIL, and architectural best practices.

• Facilitate collaboration across QA, Development, Data/ML, Security, and DevOps.

• Curate internal playbooks, patterns, sample repos, and training content to scale adoption.

What You Bring

Must-Have

• 10+ years in Quality Engineering / Software Development, with5+ years intest architecture / QA leadership.

• Strong Python expertise and hands-on experience withAI/ML in testing contexts.

• Proven experience training or fine-tuning models usingPyTorch,TensorFlow, orHugging Face.

• Solid background inComputer Vision (OpenCV) andOCR for UI/visual validation.

• Track record buildingautomation frameworks formobile and/or device-integrated systems, and clear understanding of limitations of traditional tools (e.g., Appium).

• Experience withCI/CD,Docker, anddeploying AI models into test or production environments.

• Demonstrated ability to definestrategy, setstandards, and lead cross-functional technical initiatives.

Highly Desirable

• Hands-on withlocal LLMs (Ollama, llama.cpp) andRAG usingLangChain/LlamaIndex.

• Prior experience withHardware-in-the-Loop (HIL) orSoftware-in-the-Loop (SIL) testing.

• Familiarity withAndroid/iOS ecosystems and tooling (ADB, Xcode, Fastlane, Espresso, XCUITest, Detox).

• Observability and analytics (e.g.,Prometheus/Grafana, OpenTelemetry) for test health and triage.

• Experience inregulated environments (e.g.,medical devices) and familiarity withrisk management and compliance (e.g., ISO 13485, IEC 62304, IEC 62366, ISO 14971, HIPAA/GDPR) is a plus.

Soft Skills

• Strategic thinker with abuilder’s mindset and strongsystems design instincts.

• Excellent communicator who simplifies complex concepts and aligns stakeholders.

• Strong ownership, bias for action, and comfort navigating ambiguity.

• Passion for mentoring and uplifting engineering excellence across teams.

Success Metrics (Examples)

• >40% reduction in flaky test failures and>30% faster triage through AI triage/visual diffing.

• >25% increase in critical defect detection pre-release (vs. prior baseline).

• P95 AI inference latency withintarget SLA for CI pipelines.

• Adoption of standardized AI-assisted frameworks acrossX product teams withinY quarters.

• Documented compliance with privacy and model governance standards.

Tech Stack (Indicative)

• Languages/Frameworks: Python, PyTorch/TensorFlow, Hugging Face, OpenCV, Tesseract OCR, LangChain/LlamaIndex

• LLMs/Inference: Ollama, llama.cpp, local vector DBs (FAISS/Chroma), Triton Inference Server (optional)

• Mobile & Automation: Appium, Espresso, XCUITest,FlaUI, and Azure DevOps

• HIL/Protocols: USB, Bluetooth, Serial; vendor SDKs; Python-based device controllers

• CI/CD & Infra:Azure DevOps, self hosted Ubuntu / MacOS instances

• Observability: Prometheus, Grafana, OpenTelemetry, structured logging

Personal competencies

• Strong leadership and coordination skills.

• Excellent communication skills in professional written and spoken English.

• Detail-oriented with a structured and analytical approach.

• Ability to work collaboratively across global teams.

• Proactive mindset with a focus on quality and compliance.

Who we are

At WS Audiology, we provide innovative hearing aids and hearing health services.

Together with our 12,000 colleagues in 130 countries, we invite you to help unlock human potential by bringing back hearing for millions of people around the world.

With us, you will become part of a truly global company where we care for one another, welcome diversity and celebrate our successes.

Sounds wonderful? We can't wait to hear from you.

WS Audiology is an equal-opportunity employer and committed to creating an inclusive employee experience for all. Regardless of race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status we firmly believe that our work is at its best when everyone feels free to be their most authentic self.