Are you someone who thrives on helping others succeed, enjoys making an impact, and takes pride in guiding customers to the right solutions for their projects? If you’re also naturally curious and eager to keep learning, consider starting or growing your career with us at The Home Depot.

About the co-op/internship program: 
Looking to turn classroom learning into real-world experience? The Home Depot Canada Internship/Co-op Program is your chance to apply what you’ve studied in a dynamic, hands-on environment. Over 15 weeks, you’ll work on projects that make a real impact, sharpen your skills, and build confidence for your future career. 

Program highlights include:

• Comprehensive Onboarding: Gain insights into our business operations, organizational culture, and core values.
• Strategic Projects: Address genuine business challenges, explore innovative approaches, and contribute meaningful solutions.
• Project Presentation: Share your findings and project outcomes with senior leadership.
• Professional Development Sessions: Participate in sessions designed to enhance skillsets, reinforce company values, and provide perspectives from leaders across the organization.
• Networking Opportunities: Establish connections with peer mentors and leaders who will support your professional growth throughout the program.

Duration: September 8 – December 18th, 2026

# of positions available: 1

• Location: Toronto Store Support Center – 1 Concorde Gate, North York (In office Monday – Friday)

Job Summary:

As an AI Engineer Intern you will:

• Collect, clean, and preprocess large datasets from various sources• Build AI agents in Java using Google’s Agent Development Kit (ADK): prompt design, tool/function calling, and multi-step task orchestration

• Perform exploratory data analysis (EDA) to uncover trends, patterns, and insights• Develop Spring Boot microservices that expose agents and models to downstream applications through REST APIs, and deploy them as containers on Google Kubernetes Engine (GKE)

• Contribute to one of the following: (a) building, training, and evaluating machine learning models, which may include tree-based models, deep learning, time series forecasting, or optimization/operations research techniques; or (b) developing basic AI agent workflows• Implement retrieval-augmented generation (RAG): document chunking, embeddings, and vector search over Home Depot Canada product and content data

• Collaborate with cross-functional teams (between business and technology) to translate data insights into actionable recommendations• Build batch and streaming data pipelines in Java (Apache Beam on Cloud Dataflow) that feed BigQuery and our agent workloads

• Develop data visualizations and dashboards to communicate findings to technical and non-technical stakeholders• Integrate agents with internal systems, including exposing and consuming tools over the Model Context Protocol (MCP)

• Document methodologies and present findings to the team• Evaluate agent behaviour: build test cases and measure accuracy, groundedness, latency, and cost, then iterate on the results

• Apply responsible AI and security practices, including PII handling, hallucination mitigation, prompt-injection awareness, and safe failure modes

• Collaborate with engineers, product managers, and business partners; document your design decisions and present results to the team

Required Qualifications

• Currently enrolled in a Canadian university or college co-op program in Computer Science, Software Engineering, or a closely related technical field, with AI coursework, specialization, or project work

• Strong programming fundamentals in Java (17 or later): data structures, algorithms, object-oriented design, and the ability to write clean, testable code

• Working knowledge of how LLMs are used in real applications: prompting, context management, tool/function calling, and the fundamentals of retrieval-augmented generation

• Experience building server-side applications and REST APIs, ideally with Spring Boot

• Familiarity with a JVM build tool (Maven or Gradle) and unit testing with JUnit

• SQL for retrieving and shaping data

• Comfortable with Git and GitHub (branching, pull requests, code review) and a modern IDE such as IntelliJ IDEA or VS Code

• A portfolio of things you have built: GitHub repositories, side projects, hackathons, research, or open-source contributions

• Sound engineering judgment—you can debug systematically, read unfamiliar code, and reason about trade-offs

• Strong problem-solving skills and genuine curiosity about where this technology is heading

• Excellent communication skills, with the ability to explain technical decisions to non-technical audiences

Preferred Qualifications

• Hands-on experience with Google’s Agent Development Kit (ADK) for Java, or another agent framework such as LangChain4j, Spring AI, or LangGraph

• Google Cloud experience, particularly Gemini Enterprise Agent Platform (formerly Vertex AI), BigQuery, and Google Kubernetes Engine

• Angular, or another modern TypeScript front-end framework, for building internal tools and agent interfaces

• Data pipeline experience with Apache Beam, Cloud Dataflow, Spark, or similar

• Familiarity with the Model Context Protocol (MCP) or agent-to-agent communication patterns

• Familiarity with embeddings and vector search (Agent Platform Vector Search, pgvector, or FAISS)

• Containerization with Docker and Kubernetes, and familiarity with CI/CD pipelines

• Some Python for prototyping or scripting—useful, though not the focus of this role

• Experience evaluating or monitoring LLM applications, whether with an existing framework or a harness you wrote yourself

• Awareness of responsible AI topics: bias, privacy, evaluation, and adversarial inputs such as prompt injection

The successful student will be currently enrolled in a Canadian accredited university or college throughout the period of the Internship/Co-op program.  In addition, you must be legally entitled to work in Canada by way of Canadian citizenship, permanent residency, or a valid study/work permit.

What you can expect to learn and gain from this experience:

• Accountability for key business strategies in partnership with your manager.
• Hands-on experience solving real-world problems in a production environment.
• Experience working in cross-functional teams.
• Coaching and mentoring, along with performance feedback, leadership, and development opportunities.
• Potential for a full-time offer upon graduation.
• Practical experience taking an AI feature from prototype to production, including evaluation, deployment, and monitoring.

Please note: Your current year of study and number of past internship terms will determine your salary band. Actual compensation within each band is based on skills, experience, and academic performance

The pay range for this position is between $31,600.00 - $35,400.00