Quality Engineer
Listed on 2026-06-19
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IT/Tech
IT QA Tester / Automation
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.
- 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.
- 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 Java Script
- 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.
- 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
- 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.
- 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 Lang Chain, Lang Graph, 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.
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