Agentic AI Intern

AI Native Intern

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. Each AI Native Intern is embedded in a real team, working on real problems, and is expected to deliver meaningful output over the course of the program. This is how we identify and develop the next generation of AI practitioners who will carry Data Robot's mission forward.

As an AI Native Intern, you will be placed on one of our engineering or product teams tackling high-impact, process-heavy work that is ripe for AI automation. Current focus areas include CVE resolution workflows (triage, impact assessment, dependency upgrades, and verification) and support ticket lifecycle management (categorization, diagnosis, routing, status updates, and resolution documentation). You will design and build agentic AI solutions that reduce manual toil and free engineers to focus on higher-order problems.

This is a fully remote position. The program runs approximately six months.

What You'll Do:

• Build and deploy agentic AI workflows that automate repeatable, high-volume engineering processes such as CVE triage and support ticket management
• Use the Data Robot platform — including AutoML, GenAI tooling, and MLOps capabilities — to design, evaluate, and ship solutions
• Translate ambiguous team pain points into well-scoped AI/ML problems with defined success criteria
• Work autonomously on defined project deliverables while staying aligned with your mentor and team
• Communicate progress through structured weekly updates and a final Intern Showcase presentation to Data Robot leadership
• Collaborate across engineering, product, and go-to-market teams to understand context and deliver work that sticks
• Document your work thoroughly so findings and solutions can be handed off and extended after the program

What You'll Learn:

• Agentic AI & Autonomous Systems
• Design and implementation of multi-agent systems and autonomous reasoning loops
• Agent evaluation frameworks, tool-use reliability, and safety guardrails for autonomous agents
• Advanced orchestration using frameworks like Lang Graph, CrewAI, or Auto Gen for enterprise automation
• Platform & Product
• End-to-end proficiency on the Data Robot platform: GUI, Python/R clients, and API integrations
• How to automate the ML lifecycle from data ingestion through deployment and monitoring
• Business Acumen & Use Case Development
• How to identify and size AI opportunities within real engineering workflows
• How to communicate technical findings to both technical and non-technical stakeholders
• Communication & Collaboration
• Async-first collaboration using Slack, Confluence, and structured project updates
• How to present technical work clearly to senior leaders at a live Intern Showcase

Program Structure:

Phase I — Month 1:
Onboarding & Foundation

Get oriented to Data Robot's culture, tools, and platform. Complete structured training, co-create your Individual Learning Plan (ILP) with your mentor, and begin shadowing team members on real work.

Phase II — Months 2–3:
Core Project Execution

Take ownership of a defined project scoped by your team. Work moves from guided to increasingly independent as you demonstrate competency. Expect weekly feedback from your mentor and regular touchpoints with your Buddy.

Phase III — Months 4–6:
Synthesis & Showcase

Finalize your deliverables, document your findings, and prepare for the Intern Showcase — a live presentation to Data Robot leaders and peers. Optional rotations or cross-functional exposure may be available based on performance and team need.

What We're Looking For:

Required:

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field
• Working proficiency in Python (pandas, numpy) and comfort…