Software Engineer Co-op - Winter/Spring 2027

## What You Will Do: Immerse yourself in a full-time, Monday-Friday co-op session, that will run January-August (including the Spring semester; it is expected students will take a semester off from coursework to fully engage with this working mentorship opportunity). The Intelligent Aerospace Technologies Development Sandbox team within Applied Research & Technology (ART) is seeking a high‑energy, inquisitive, and motivated student co‑op with academic or personal project experience in Artificial Intelligence or Generative AI. As a co‑op, you will contribute to defining disruptive new development processes for Collins Aerospace, helping enable faster cycle times, lower lifecycle cost, reduced tech debt, and improved reuse across next‑generation avionics systems. This position is on-site in Cedar Rapids, Iowa. - Support the development, design, and execution of experiments exploring Generative AI for safety‑critical development - Work collaboratively within the Sandbox environment to investigate new tools, workflows, and prototype solutions - Apply curiosity and problem‑solving skills to real engineering challenges - Assist in creating documentation, demos, or prototype integrations related to AI/ML technologies - Collaborate with engineers across multiple sub‑projects and contribute to technical discussions ## Qualifications You Must Have - Must be pursuing Bachelor’s or Advanced degree in Science, Technology, Engineering or Mathematics (STEM) and actively enrolled through the completion of the internship/co-op session. - Must have a minimum of 60 hours of credit by the start of the internship / co-op session. - Coursework or personal project experience in Artificial Intelligence, Machine Learning, or Generative AI - Familiarity with Python development and Linux/Unix environments - Experience may be obtained through on-the-job experience, research, coursework, or projects. - Ability to communicate clearly and work effectively in a collaborative environment - Experience experimenting with LLMs, Generative AI models, or AI‑driven tools - Understanding of basic software engineering concepts (via coursework or projects) - Exposure to full‑stack concepts or API‑driven development - Familiarity with frameworks such as LangChain, Haystack, or similar technologies - Prior RTX internship, co-op, or work experience.