Performance Engineering Intern (AI Enablement & Automation) - June 2026

About This Role

Staples is business to business. You are what binds us together.

We are seeking a graduate level student for a Performance Engineering Intern to join our team with a focus on AI\-level Performance Engineering (PaCE) Intern to join our team with a focus on \-level Performance Engineering (PaCE) Intern to join our team with a focus on AI automation and performance intelligence. This role offers enabled automation and performance intelligence. This role offers \-enabled automation and performance intelligence. This role offers hands\-on experience improving the scalability, efficiency, and resilience of Staples’ critical digital platforms by automating performance testing, analyzing large scale telemetry, and applying AI scale telemetry, and applying \-scale telemetry, and applying AI techniques to accelerate performance insights and driven techniques to accelerate performance insights and decision\-driven techniques to accelerate performance insights and decision\-making.

Target Start Date: June 1, 2026 \- August 14, 2026 (11\-week program)

What you bring to the table

• Performance Mindset – motivated by understanding system behavior under load and ensuring platforms perform reliably at scale.
• Automation First – strong interest in eliminating manual performance testing and analysis through scripting, frameworks, and intelligent automation.
• Analytical Thinker – curious about metrics, trends, baselines, and anomalies, and how data can be transformed into actionable insights.
• Collaborative – able to work closely with application engineers, SREs, platform teams, and enterprise tools partners.
• Continuous Learner – eager to explore modern performance engineering practices and AI\-assisted analysis techniques.

What You’ll Be Doing

• Build and enhance automated performance testing frameworks and workflows to improve repeatability, coverage, and efficiency
• Apply AI/ML or LLM\-based\-based approaches to performance data for tasks such as test run summarization, baseline comparison, anomaly detection, and insight generation
• Work with performance and observability signals, including response times, throughput, error rates, logs, and infrastructure metrics
• Develop scripts, tools, or services using languages such as Python, Java, or JavaScript to support performance testing, data analysis, and reporting
• Assist in analyzing performance test results and communicating findings clearly to engineering and platform teams
• Contribute to performance testing pipelines integrated with Git\-based workflows and CI/CD processes

What’s needed – Basic Qualifications

• Currently pursuing a master’s degree in Computer Science, Software Engineering, Data Engineering, or a related field
• Strong foundation in software engineering fundamentals, data analysis, and system performance concepts
• Proficiency in at least one programming or scripting language, such as Python or Java
• Comfort working in Linux \-based environments and using Git for version control

What's needed \- Preferred Qualifications

• Exposure to performance engineering concepts such as load testing, stress testing, scalability analysis, and capacity planning
• Interest or academic experience in applying AI/ML techniques to analytics, automation, or engineering workflows
• Interest in agentic AI concepts and how LLM\-driven assistants can help automate engineering workflows.
• Familiarity with or interest in monitoring/observability tools like Splunk, New Relic, Azure Monitor, and similar platforms
• Experience or coursework related to test automation, CI/CD pipelines, or observability platforms
• Familiarity with cloud\-based systems, distributed architectures, or containerized environments