INTERNSHIP Agentic AI RelOps Quality Engineer

Role Description & Responsibilities

Dassault Systèmes SIMULIA is seeking an innovative AI Quality Engineering Release Operations (AI QE Rel Ops) Intern / Co-op to join our Software Quality Engineering organization. SIMULIA delivers advanced software simulation tools used by leading designers, engineers, and scientists worldwide to transform product development. This role is located in our Johnston, RI office in a flexible work capacity at your managers discretion and being at least 3 days in the office.

In this role, you will work at the intersection of Artificial Intelligence, Quality Engineering, and DevOps. You will focus on building AI Agents designed to analyze and summarize release operations data, enabling engineering leadership to make data-driven decisions.

Additionally, you will contribute to building and enhancing our LLM automated testing infrastructure and validation capabilities.

• Design, develop, and deploy AI Agents to aggregate, analyze, and report on complex release operations data.
• Build automated reporting workflows and actionable dashboards to support release readiness decision-making.
• Contribute to the development and enhancement of LLM-based automated testing infrastructure and testing capabilities across SIMULIA products.
• Identify opportunities to optimize quality assurance processes using agentic automation, machine learning, and modern LLM frameworks.
• Collaborate with software quality engineering leads, software developers, and DevOps teams to streamline release pipelines.
• Design, implement, and run validation scripts and test suites to evaluate AI model accuracy, consistency, and reliability.
• Document technical architecture, agent workflows, and test infrastructure to promote knowledge sharing across R&D teams.

Develop AI Agents and Skills to assist with QE R&D Operations Management including Function, Regression Testing and IR analysis, Release Convergence Assessment and Risks, and Test Automation Gap Analysis and Script development.

Qualifications

• Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Computer Engineering, Software Engineering, Data Science, or a related technical discipline.
• Strong programming background in Python, with experience leveraging standard data analysis libraries and APIs.
• Hands-on experience or coursework involving Large Language Models (LLMs), AI agent frameworks (e.g., LangChain, Llama Index, or Auto Gen), and prompt engineering.
• Familiarity with software testing methodologies, continuous integration/continuous deployment (CI/CD) pipelines, and software release operations.
• Understanding of database concepts, RESTful APIs, and data visualization tools.
• Strong analytical, problem-solving, and algorithmic skills.
• Excellent written and verbal communication skills with the ability to present technical data clearly.
• Ability to work effectively in a hybrid team environment in Johnston, RI.
• Knowledge of software quality engineering automation frameworks or exposure to engineering CAD and simulation tools is a plus.