AI Engineer Intern

AI Engineer Intern

7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants and fuel through cutting edge innovation — working hard to be the customer's first choice. 7-Eleven empowers our employees to 'activate awesome' and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead and make a difference, come join our team and help shape the future of convenience.

The paid internship takes place during Summer 2027. You will gain practical experience, grow your professional network, develop in-demand skills, and help shape the future of merchandising at the world's largest convenience retailer.

As an AI Engineer Intern, you will join a multidisciplinary team of senior engineers, API engineers, and AI engineers building customer-facing AI products (conversational shopping and customer support agents) and the AI platform behind them: an AI gateway with model routing, an agent builder framework, MCP services, and observability and evaluation tooling.

This is a hands-on internship. You will own a scoped project from prototype to a demo-ready deliverable, working inside real code, real pipelines, and real engineering standards, with a dedicated mentor and regular code reviews. Interns typically spend about 70% of their time building and 30% learning, pairing, and presenting.

What You Will Do

• Build and test LLM-powered features such as tool and function calling, retrieval-augmented generation (RAG), and multi-step agent workflows in Python and/or Node.js.
• Develop evaluation harnesses for LLM applications, including golden datasets, regression tests, automated scoring, and trace review.
• Help instrument AI services for observability: tracing, prompt and version tracking, tool-call monitoring, latency, token usage, and cost.
• Experiment with prompts, context design, and retrieval quality; compare models on accuracy, latency, and cost, and document the trade-offs.
• Contribute to the AI platform by building small services, API integrations, SDK samples, or developer tooling that helps other teams adopt the AI gateway and agent framework.
• Write clean, tested, documented code, and participate in code reviews, sprint ceremonies, and design discussions.
• Apply responsible-AI practices, including guardrails, PII handling, and safety testing, in every project.
• Present your project results and recommendations to the team and leadership at the end of the internship.

Required Qualifications

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Machine Learning, Mathematics, or a related field, with an expected graduation date at least one semester and no more than one year after the internship.
• Proficiency in Python; working knowledge of at least one other language such as JavaScript/TypeScript (Node.js) or Java.
• Understanding of software fundamentals: data structures, algorithms, REST APIs, and Git workflows.
• Familiarity with LLM concepts such as prompting, embeddings, RAG, and tool calling, gained through coursework, personal projects, or hackathons.
• Strong problem-solving skills, curiosity, and a willingness to learn quickly in a fast-moving field.
• Clear written and verbal communication; comfortable asking questions and giving and receiving feedback.

Preferred Qualifications

• Hands-on experience with LLM frameworks such as LangChain/LangGraph, or with model APIs from OpenAI, Google (Gemini/Vertex AI), Anthropic, or Amazon Bedrock.
• Experience with vector databases or search (for example, pgvector, OpenSearch, MongoDB Atlas), and basic SQL or NoSQL databases.
• Exposure to cloud platforms (AWS or GCP), containers (Docker), and CI/CD.
• Familiarity with LLM observability and evaluation tools (for example, Langfuse, LangSmith, OpenTelemetry).
• Interest in AI safety, guardrails, and responsible-AI practices.
• Personal projects, open-source contributions, research, or prior internships involving AI/ML or agentic systems (link your GitHub or portfolio).