AI Engineer Intern

We, the TestEnablement team, are dedicated to building a world-class testing framework that drives code quality, accelerates development cycles through automation, strengthens applications against failures, and optimizes system performance—all to deliver a seamless and reliable user experience. Our solution has boosted the productivity of service teams by reducing cognitive load across the SDLC through integrated Performance, Code Quality, Resilience, and Security scans. Looking ahead, we aspire to harness AI to elevate these capabilities further and empower teams to achieve even greater productivity.

What You’ll Do

As an intern, you’ll support the development of AI-driven solutions that enhance software quality and developer productivity. You will:

• Develop tools for automated test generation for unit or performance testing
• Contribute to Pull Request reviews with intelligent code suggestions
• Build workflows for automated documentation generation using LLMs and RAG
• Explore and prototype Retrieval-Augmented Generation (RAG) and LLM fine-tuning for engineering enablement
• Assist in creating AI-powered developer support chatbots for self-service knowledge retrieval
• Contribute to performance and load testing pipelines with AI-based anomaly detection
• Help integrate GenAI workflows into CI/CD pipelines (GitHub, Jenkins, Argo, Kubernetes)
• Research emerging areas like AI observability, evaluation frameworks, and safety in GenAI tools
• Document AI-assisted workflows, write knowledge articles, and prepare engineering best-practice playbooks

What You’ll Gain

• Mentorship and collaboration with senior engineers in AI-driven development enablement, focused on quality, reliability, and innovation
• Exposure to real-world AI and DevOps practices at PlayStation scale
• Opportunity to contribute to innovative AI capabilities that improve developer experience for thousands of engineers
• Hands-on experience applying AI/ML techniques to software testing and developer productivity
• Exposure to cutting-edge GenAI workflows in real-world CI/CD environments
• Opportunities to experiment with RAG, LLM fine-tuning, and AI observability in practical engineering settings
• Deeper understanding of performance, resilience, and security testing at scale
• Growth in technical writing and documentation through creating knowledge articles and playbooks

What We’re Looking For

• Currently pursuing a Master’s degree in Computer Science, Software Engineering, or related field
• Familiarity with at least one programming language (e.g., Java, Python, JavaScript, or Go)
• Basic understanding of software testing concepts (unit, integration, performance)
• Exposure to machine learning or natural language processing through coursework or projects
• Familiarity with Git and CI/CD practices through projects or coursework
• Strong problem-solving skills and eagerness to learn new technologies

Nice Haves

• Experience with LLM-based tools and frameworks (LangChain, LlamaIndex, Hugging Face)
• Exposure to RAG, vector databases (e.g., FAISS, Pinecone, Weaviate), or embedding models
• Familiarity with test automation frameworks (JUnit, pytest, JMeter)
• Exposure to containerization and cloud concepts (Docker, Kubernetes, AWS)
• Interest in AI-assisted developer tools (GitHub Copilot, OpenAI APIs, or similar)

Eligibility

• Students with expected graduation between December 2026 and Spring 2027 from an accredited university. Advanced Degree - Master’s
• Able to work during one of the following periods: May 18th - August 7th or June 15th - September 4th. Relocation assistance is available for eligible candidates.
• Must be available for the entire 12-week internship period.

At this time, SIE will only consider applicants who are authorized to work for any employer in the United States and who will not require work visa sponsorship from SIE now or in the future to maintain their authorization to work in the United States.

Our intern positions offer a fixed hourly pay rate. Please note that the pay rate is exclusive to the internship period and may not reflect what pay may look like following the completion of an internship.