Co-op/Intern Fall 2026 (Aug-Dec) – AI for Software Testing & Quality Engineering

Responsibilities

• Research, evaluate, and prototype AI technologies applicable to software testing and quality engineering.
• Design and implement agentic workflows for areas such as test selection, test prioritization, defect triage, root-cause analysis, and test result summarization.
• Develop and maintain AI agents, skills, prompts, and supporting automation to improve engineering workflows.
• Collaborate with software developers, test engineers, and product teams to identify opportunities for AI-driven process improvements.
• Build proof-of-concepts and pilot solutions using modern AI frameworks, APIs, and tooling.
• Analyze testing data and engineering metrics to improve test coverage, execution efficiency, and defect detection.
• Document solutions, findings, and best practices for broader organizational adoption.
• Present project progress, technical findings, and recommendations to stakeholders.
• Stay current with advancements in AI, machine learning, large language models (LLMs), and software testing methodologies.

Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or a related technical discipline.
• Strong academic performance and demonstrated technical aptitude.
• Experience developing software in at least one modern programming language such as Python, JavaScript/TypeScript, C#, Java, or C++.
• Familiarity with software development lifecycle processes and version control systems such as Git.
• Demonstrated interest in AI, machine learning, automation, or software quality.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently while collaborating effectively within a team environment.

Special Knowledge, Skills, And Abilities

• Knowledge of software testing concepts, including unit, integration, system, and automated testing.
• Understanding of basic AI and machine learning principles.
• Experience writing scripts or applications in Python or a similar language.
• Ability to analyze technical problems and propose practical solutions.
• Strong verbal and written communication skills.
• Ability to learn new technologies quickly and adapt to evolving priorities.
• Strong organizational skills and attention to detail.
• Ability to document technical work and communicate findings to both technical and non-technical audiences.

Preferred

• Experience with large language models (LLMs) and AI-assisted development tools.
• Familiarity with agent frameworks, prompt engineering, retrieval-augmented generation (RAG), or multi-agent systems.
• Experience building applications using AI APIs or platforms.
• Knowledge of software quality metrics, test automation frameworks, or continuous integration/continuous delivery (CI/CD) pipelines.
• Experience with Python testing frameworks such as pytest.
• Familiarity with cloud platforms, containerization technologies, or DevOps practices.
• Experience analyzing structured and unstructured data sets.
• Contributions to open-source projects, academic research, hackathons, or personal AI-related projects.
• Interest in applying AI to improve engineering productivity, software quality, and development workflows.