Quality Engineer

Role Description & Responsibilities:

Dassault Systemes is a seeking a Quality Engineer for our ENOVIA brand, ENOVIA provides the leading enterprise collaboration applications for many industries promoting innovation and operational excellence with a variety of product solutions. From Aerospace and Defense to customers to in the Life Science based industries, our solutions manage mission-critical data. You will help drive the quality delivery of best-in-class applications of ENOVIA by supporting client fix packs validations and providing technical assessments of the enhancements along with Cloud and On-premise validation support for the team onsite. You will work closely in an agile environment with a group of experienced Developers, Quality Engineers, and Business Consultants to help create and validate Gen7 products of ENOVIA Resilient Value Network domain.

Design

• Validate Specification of new functionalities: ensure their completion and compliancy with DS standards
• Define functional testing scenarios: Use cases (customer scenarios) corresponding to functionalities to be tested.
• Strong understanding of testing principles, methodologies, and test case design
• Define scenarios based on Industrialization Strategy and Function Specifications
• Identify and qualify bugs and non-conformity areas within specification requirements.

Implement

• Execute testing: Run defined scenarios (acceptance, convergence & non regression)
  • On Premise and CLOUD environments
  • Mobile
• Understanding our Automation Framework and Developer environment
  • Authoring and executing software test automation scripts using JavaScript
• Manage and Publish Test results
  • Participate in GO/NOGO according to the DS defined Gates
  • Define recovery plans with development teams
  • Escalate issues and priority arbitration to stakeholders and management
  • Document issues through Incident Reports (IRs) raised to the development teams for resolutions
  • Constant follow-up on critical issues and ensure closure
• Understanding and testing of AI/ML based applications
  • Develop and execute detailed test plans to assess AI algorithms, data quality, and system performance.

Support

• Monitor and control testing process: steer in details QA activities for overall quality improvement
• Capitalize on feedbacks from the incidents reported by customers to continuously improve testing process (content and efficiency)
• Plan convergence and non-regression tests according to the targeted GA (final delivery) date and Define Industrialization plan:
  • Compilation and arbitration between all scenarios.
  • Necessary time and resources for testing
  • Organization of activities between all the Development and Operations cycle gates
  • Optimization of QA costs
• Focus efforts on automation and testing strategies for Continuous Integration
• Cover broad spectrum of tests including functional, UI, API and more along with regression tests to ensure a comprehensive test coverage

Collaborate and Grow

• A fast learner and highly motivated individual who is keen to take ownership
• Excellent communication skills, both oral and written
• Continually looking for ways to improve
• Desire to work in a collaborative team environment
• Strong critical thinking skills and organizational skills
• Work with cross-functional and multi geo teams.

Qualifications:

• Bachelor’s degree (Computer Science or related field)
• 2–5 years in software QA with enterprise-level products
• QA automation tools (e.g., Selenium, SAHI)

• Agentic AI, LLM & Advanced QA Capabilities

• Strong understanding of Transformer-based LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), Function/Tool Calling, Multi-Agent Systems, Agent Planning & Reasoning Workflows, and Memory Architectures.

• Experience validating Agentic AI applications through scenario-based testing, adversarial testing, edge-case identification, and failure-mode analysis.

• Conduct hallucination testing, prompt injection validation, jailbreak detection, memory corruption testing, and tool-selection accuracy assessments.

• Design and execute AI evaluation frameworks using benchmark datasets, ground-truth validation, human evaluation methods, and LLM-as-a-Judge approaches.

• Validate agent workflows, reasoning chains, tool-calling accuracy, and multi-step decision-making processes.

• Experience with LangChain, LangGraph, OpenAI APIs, and Azure OpenAI services.

• Perform A/B testing, benchmarking, statistical analysis, and model comparison studies to measure improvements in accuracy, hallucination reduction, and tool-use effectiveness.

• Strong expertise in Python, SQL, API Testing, Log Analysis, CI/CD Automation, REST APIs, JSON, Authentication, and Test Case Design.