What is the HUX AI Summer 2026 Research Internship?

Everything you need to know about our Summer 2026 Research Internship program - Q&A

HUX AI 2026 Summer Research Internship Program will focus on developing practical AI governance tools for emerging LLM and agentic AI risks. Unlike a conventional research internship centred on long reports, this program is designed around applied outputs: lightweight frameworks, evaluation rubrics, test libraries, risk taxonomies, control matrices, scorecards, and simple prototype tools.

Each project should produce a short 5–10 page explanatory report, but the core output is expected to be a practical project/tool.

Who is this for?

Most of our applicants are juggling university, work, or multiple projects. That’s okay. We welcome undergraduate and graduate students, recent graduates, and early-career professionals across various disciplines—from public policy to design to computer science.

This internship is fully remote, volunteer-based, and asynchronous-friendly. There are no fixed working hours, so it can easily be combined with full-time work or academic schedules.

You don’t need to have prior experience in AI or policy. What we’re looking for is:

• Curiosity about AI governance and safety
• Clear communication
• Independent follow-through
• Openness to feedback

One thing to note: English proficiency is required. Most documentation is in English, and if your cohort has only English-speaking peers, weekly meetings and webinars will be conducted in English.

What will I actually work on?

Interns will be matched with one of two project tracks based on interest and fit:

• Project 1 — LLM Guardrails Evaluation Toolkit
  Purpose: To develop a practical toolkit for evaluating whether LLM guardrails can resist prompt injection, jailbreak attempts, policy bypass, unsafe tool-use triggers, and related failure modes.

  Scope: The project will focus on defensive evaluation of LLM guardrails. It may include a risk taxonomy, safe test prompt library, scoring rubric, control matrix, and lightweight evaluation template.

  Expected outputs:

  • Guardrail failure taxonomy
  • Safe test prompt library
  • Guardrail effectiveness scoring rubric
  • Risk-control-evidence matrix
  • Lightweight evaluation tool or template
  • 5–10 page report

• Project 2 — Agentic AI Risk Control Matrix
  Purpose: To create a practical governance framework for AI systems that can use tools, access data, trigger workflows, or perform actions.

  Scope: The project will focus on autonomy levels, tool-use risks, human oversight, access control, auditability, action reversibility, and required governance controls.

  Expected outputs:

  • Agentic AI risk taxonomy
  • Autonomy level classification
  • Scenario library
  • Agentic AI control matrix
  • Risk assessment questionnaire or tool
  • 5–10 page report

What is expected of me?

Interns are expected to:

• Understand the selected AI risk area through targeted research.
• Translate conceptual risks into practical assessment dimensions.
• Build a structured taxonomy, scoring rubric, checklist, matrix, or lightweight prototype.
• Use publicly available standards, frameworks, benchmarks, and open-source tools as references.
• Keep the project practical, explainable, and usable by governance, risk, compliance, product, or technical teams.
• Produce a short report that explains the problem, methodology, proposed framework, limitations, and future development potential.

What is not expected of me?

Interns are not expected to:

• Train or fine-tune a new model.
• Build production-grade software.
• Conduct unsafe red teaming or publish harmful jailbreak instructions.
• Produce a long academic literature review as the main output.
• Claim that the tool provides legal compliance certification.
• Evaluate all available LLMs or all possible AI risks.

What kind of support will I get?

This is not a “throw you in the deep end” experience. Throughout the 10-week program, you’ll receive:

• A warm welcome during orientation
• Weekly check-ins with HUX AI mentors
• Ongoing feedback via async channels
• Biweekly webinars with guest experts and mentors covering career pathways and project-related insights
• Optional 1:1 mentor consultations
• Recognition in our final project outputs

Upon joining, you’ll also become a member of the HUX AI Community, our growing network of learners, builders, and thought leaders working on responsible AI futures.

How flexible is the time commitment?

Very. We know your schedule may shift, and that’s okay.

Once accepted, you’ll fill out a scheduling survey to indicate your availability for weekly check-ins. Based on everyone’s preferences and time zones, we’ll coordinate a fixed one-hour weekly meeting at a time that works for the majority.

Beyond that, everything is async. You’ll decide when to read, research, write, or prototype whatever your project requires. All we ask is that you make steady progress and stay communicative.

Is it paid?

This is a volunteer-based internship, but it’s designed to be meaningful. You’ll contribute to real, public-facing resources and build a portfolio you can point to.

Outstanding contributors may be invited to work on future paid research opportunities or receive personal recommendation letters from HUX AI leadership.

How do I apply?

It’s a simple 3-step process:

1. Submit your application by EOD June 24th
2. If shortlisted, we’ll invite you to a 10/15-minute video interview
3. If selected, you’ll join us for orientation starting July 6th

Apply now if you’re excited to work on real-world challenges in responsible AI and want to shape the future alongside a global community.