Software Design Engineer Intern

Job Description:

Data Robot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI aRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on Data Robot for AI that makes sense for their business — today and in the future.

Our interns are not observers—they are contributors. Embedded in real teams and paired with dedicated mentorship, you will work on practical problems and deliver meaningful engineering output.

In this role, you will partner closely with our Documentation and Engineering teams to improve our developer-facing documentation platform, build CI/CD automation, and apply modern AI tooling to maintain freshness and accuracy. You will focus on building tools that minimize manual overhead—such as PR checks, content validation pipelines, and release workflows—helping our documentation evolve seamlessly alongside our product.

This is a fully remote position open to recent college graduates and early-career engineers. The program runs approximately 6 months.

• - Build CI/CD Checks & Workflow Automation:
  Develop lightweight Git Hub Actions/PR checks to streamline doc reviews, run automated linters, and validate content changes against code updates.
• - Automate Testing & Code Snippet Execution:
  Create automated tests that run documentation code examples and notebooks in CI to catch breaking changes early.
• - Implement Content & Documentation Tooling:
  Assist in building tools and scripts to convert, generate, or publish documentation artifacts (e.g., Markdown/MDX pipelines, change logs, and release summaries from Jira/PR data).
• - Apply AI to Developer Tooling:
  Explore using LLMs and agentic scripts for practical site health tasks, such as flagging stale screenshots or enhancing doc indexing and retrieval for AI assistants.
• - Collaborate & Document:
  Work closely with your mentor and docs engineers, communicate progress in weekly syncs, and present your accomplishments at the end‑of‑internship Showcase.

• - CI/CD & Developer Productivity:
  Practical experience building Git Hub workflows, PR bots, and test automation pipelines in a large‑scale engineering environment.
• - Modern Documentation Engineering:
  Hands‑on experience with modern documentation frameworks (Markdown, MDX, static site generators) and API documentation life cycles.
• - Pragmatic AI & LLM Automation:
  
  How to apply
  
  LLMs, scripting, and evaluation to automate real‑world maintenance tasks.
• - Collaborative Software Engineering:
  Working in an async‑first culture using Git, code reviews, Slack, and agile delivery practices.

Phase I (Month
1) — Onboarding & Foundation:
Learn the platform, tool chains, and repos. Co‑create an Individual Learning Plan with your mentor and complete your first guided tickets.

Phase II (Months 2–5) — Core Project Delivery:
Take ownership of scoped automation projects (e.g., CI testing of doc snippets, PR review gating, or generator scripts) with ongoing guidance and weekly 1:1 check‑ins.

Phase III (Month
6) — Refinement, Handoff & Showcase:
Finalize deliverables, write clean documentation for the team to maintain your work, and present your accomplishments at an Intern Showcase.

• - Recent graduate or completed Bachelor’s/Master’s degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent practical project experience).
• - Solid foundational programming skills in Python and comfort with scripting or data parsing.
• - Familiarity with Git and Git Hub workflows (branching, pull requests, code reviews).
• - Basic exposure to…