Performance Engineering Intern (AI Enablement & Automation) - June 2026
About The Position
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.
Requirements
- 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
Nice To Haves
- 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
Responsibilities
- 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
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What This Job Offers
Career Level
Intern
