Fellow Quality Assurance Engineer

Our world is transforming, and PTC is leading the way. Our software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business.

Our people make all the difference in our success. Today, we are a global team of nearly 7,000 and our main objective is to create opportunities for our team members to explore, learn, and grow – all while seeing their ideas come to life and celebrating the differences that make us who we are and the work we do possible.

The Fellow Quality Assurance Engineer – AI Focused is a senior technical expert responsible for ensuring end-to-end quality across AI-driven and traditional software components, including core products, plugins, toolchains, and machine-learning-enabled features.

This role leads quality strategy for AI initiatives, drives complex automation efforts, defines testing standards for AI/ML functionality, and provides deep technical guidance across engineering teams. The Principal QE is involved in all phases—from design and planning, through implementation and execution, to release—ensuring quality, reliability, and responsible AI practices across the development lifecycle.

Key Responsibilities

• Define and lead the quality strategy for AI-driven features, ML workflows, inference pipelines, and integrated AI services
• Drive manual and automated testing efforts across multiple concurrent projects, including complex AI-related components
• Provide expert technical guidance to QA engineers on AI test design, data validation, model evaluation, and defect analysis
• Develop advanced automated test frameworks tailored for both traditional software and AI behavior validation
• Establish testing methodologies for LLM-based features, generative AI outputs, recommendations, and model-driven logic
• Evaluate model performance, accuracy, fairness, stability, and regression behavior across versions and datasets
• Perform root cause analysis for complex, cross-system issues involving AI components, backend services, and integrations
• Collaborate with data scientists, ML engineers, and software developers to ensure responsible and high-quality AI deployments
• Conduct exploratory, regression, usability, acceptance, and adversarial testing for AI features
• Build and maintain automated test suites integrated with CI/CD pipelines at scale
• Execute performance, scalability, and stress tests for both traditional services and AI inference workloads
• Lead QA participation in architectural reviews, risk assessments, and release planning for AI modules
• Deliver accurate estimations and drive continuous quality improvements across teams
• Track and report advanced quality metrics, including model KPIs, drift indicators, defect trends, and test coverage

Required Qualifications

• Extensive experience in both manual and automated software testing across large-scale, enterprise-grade systems
• Deep, hands-on knowledge of testing AI/ML systems, including validation of models, data pipelines, or LLM-based features
• Expertise with automation frameworks (e.g., Playwright, Selenium, Cypress) and strong coding skills in Python, JavaScript, or TypeScript
• Experience testing AI models, LLM prompts, inference APIs, embeddings, or ML-driven functionality
• Proficiency with performance and load-testing tools (e.g., JMeter, k6)
• Strong experience with CI/CD pipelines and modern version control practices (e.g., GitHub Actions, Jenkins, Git)
• Strong understanding of Agile/Scrum and engineering best practices
• Advanced analytical skills, critical thinking, and the ability to dissect ambiguous AI behaviors and identify root causes
• Excellent communication skills with the ability to influence stakeholders across engineering, ML, product, and leadership

Preferred Qualifications

• Experience with cloud platforms and containerized environments (e.g., AWS, Docker, Kubernetes)
• ISTQB Advanced or equivalent certification
• Experience with observability and monitoring tools (e.g., Grafana, Prometheus, New Relic)
• Familiarity with MLOps tools or workflows (MLflow, SageMaker, Vertex AI, Databricks, or similar)
• Background in performance, scalability, or security testing for AI systems
• Knowledge of responsible AI principles: fairness, guardrails, bias detection, and model drift monitoring

Life at PTC is about more than working with today's most cutting-edge technologies to transform the physical world. It's about showing up as you are and working alongside some of today's most talented industry leaders to transform the world around you.

If you share our passion for problem-solving through innovation, you'll likely become just as passionate about the PTC experience as we are. Are you ready to explore your next career move with us?

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