IT Engineering Intern - Accelerate

## WHAT YOU’LL DO - Build and ship features on our customer-facing digital platforms — from streamlining the rental journey to enabling self-service experiences that eliminate wait times and delight customers. - Contribute to AI-powered initiatives, including integrating large language models (LLMs), building intelligent search and recommendation features, and prototyping generative AI tooling across our web properties. - Work directly with Engineering leaders and Solution Architects on technology transformation initiatives that impact millions of renters globally. - Develop across our modern web stack — React, Angular, Node.js, and Java — deployed on AWS with Kubernetes, following best practices in CI/CD, testing, and code quality. - Collaborate on prompt engineering, retrieval-augmented generation (RAG), and AI agent workflows as we embed intelligence into the rental experience. ## WE’RE LOOKING FOR SOMEONE WHO HAS - Currently pursuing a 4-year degree in Computer Science, AI/ML, or a related field. - Hands-on experience coding in at least one language (JavaScript/TypeScript, Python, Java, etc.). - Familiarity with web development fundamentals — HTML, CSS, REST APIs — and curiosity about how modern front-end frameworks like React or Angular work. - An interest in applied AI: LLMs, prompt engineering, vector search, or ML APIs (even if just through personal projects or coursework). - Strong attention to detail and comfort working in ambiguous, fast-moving environments. - Clear written and verbal communication skills — you’ll be working directly with senior engineers and architects. - Availability to work 35 hours per week. ## NICE TO HAVE - Experience with AWS services (Lambda, S3, API Gateway, Bedrock, etc.). - Exposure to Java or Node.js in a project or professional setting. - Familiarity with relational or vector databases. - Experience integrating or fine-tuning AI/ML models or APIs (OpenAI, Anthropic, HuggingFace, etc.). - Understanding of containerization basics (Docker, Kubernetes). - Familiarity with web analytics platforms (Google Analytics, Adobe Analytics, or Segment) and using data to measure feature impact. - Exposure to headless CMS platforms (Contentful, Strapi, or similar) for managing content-driven web experiences. - Basic understanding of SEO fundamentals — semantic HTML, Core Web Vitals, metadata — as they relate to front-end development.