Enterprise Tools Engineering Intern - June 2026
About The Position
Staples is business to business. You are what binds us together. We are looking for a graduate-level student for an Enterprise Tools Engineering Intern position to join our Enterprise Tools Engineering team, with a focus on AI-driven automation and observability platforms. This role provides hands-on experience building and enhancing the enterprise tools that power reliability, performance, and operational excellence across Staples’ digital platforms. You will work alongside senior engineers on real production systems used by hundreds of engineering teams. Target Start Date: June 1, 2026 - August 14, 2026 (11-week program)
Requirements
- Currently pursuing a master’s degree in Computer Science, Software Engineering, Data Science, or a related field
- Strong foundation in software engineering concepts, data structures, and algorithms
- Proficiency in at least one programming language such as Python, Java, or similar
- Experience working in Linux-based environments and using Git for version control
- Systems Thinker – interested in how large-scale platforms, tools, and workflows enable engineering teams at scale.
- Automation Mindset – passionate about reducing manual effort through scripting, APIs, AI-assisted workflows, and self-service tooling.
- Data & Insight Oriented – curious about metrics, logs, traces, and how observability data drives better decisions.
- Collaborative – able to partner with SRE, application engineering, performance, and product teams.
- Self-Directed Learner – comfortable operating with ambiguity and proactively learning new tools and technologies.
Nice To Haves
- Exposure to observability or monitoring tools (e.g., metrics, logging, tracing platforms)
- Experience with automation, scripting, or workflow orchestration (Python, shell, REST APIs, etc.)
- Familiarity with cloud platforms, containers, or Kubernetes concepts
- Interest or coursework in AI/ML, applied analytics, or large language models
- Understanding of site reliability, performance engineering, or platform engineering
Responsibilities
- Design and build automation solutions to improve reliability, efficiency, and self-service across engineering teams
- Develop scripts, services, or workflows that integrate with enterprise platforms such as observability, alerting, or ITSM tools
- Apply AI/ML or LLM-based techniques (e.g., analysis, summarization, anomaly detection, or assisted remediation) to operational data
- Work with observability data, including metrics, logs, and traces, to support monitoring, alerting, and insight generations
- Contribute code using modern engineering practices, including version control, code reviews, and CI/CD pipelines
- Collaborate in Agile ceremonies and partner with senior engineers to design scalable, maintainable solutions
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What This Job Offers
Career Level
Intern
