Software Design Engineer Intern

Job Description: DataRobot 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 at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot 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. What you'll do: Build CI/CD Checks & Workflow Automation: Develop lightweight GitHub 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, changelogs, 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. What you'll learn: CI/CD & Developer Productivity: Practical experience building GitHub 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 lifecycles. 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. Program Structure: Phase I (Month 1) — Onboarding & Foundation: Learn the platform, toolchains, 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. Qualifications: 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 GitHub workflows (branching, pull requests, code reviews). Basic exposure to or enthusiasm for CI/CD concepts (e.g., GitHub Actions) and web/documentation formats (Markdown, HTML/CSS, or JavaScript/TypeScript). Curiosity and eagerness to experiment with LLM APIs for developer productivity. Strong written communication skills and an organized, problem-solving mindset. Nice to Have: Experience writing GitHub Actions or automating developer workflows. Prior experience with static site generators (Docusaurus, MkDocs, Next.js, etc.) or MDX. Familiarity with running automated tests or linting tools in CI pipelines. Personal or academic projects integrating LLM APIs (e.g., OpenAI, Anthropic, or open-source models). The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more! DataRobot Operating Principles: Wow Our Customers Set High Standards Be Better Than Yesterday Be Rigorous Assume Positive Intent Have the Tough Conversations Be Better Together Debate, Decide, Commit Deliver Results Overcommunicate Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit. DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information. Use of Artificial Intelligence in Our Hiring Process DataRobot uses approved AI-powered tools to support the hiring process in selected regions. These tools may assist in writing job descriptions, reviewing applications, assessing qualifications, and evaluating candidate materials. All decisions regarding applications are made by members of the DataRobot team. All applicant data submitted is handled in accordance with our Applicant Privacy Policy.