About Georgian

Georgian is a growth equity firm that seeks to invest in B2B technology companies, We invest in ~6 new companies per year and support our portfolio companies with capital and technical capability.

Georgian has been active in analytics and applied AI since its founding in 2008 and invests across the AI technology stack, from infrastructure and applications to cybersecurity and developer tools.

Georgian’s in-house AI Lab of 10+ engineers and scientists assist portfolio companies on production AI deployment. Georgian’s team brings together investors with machine learning professionals, software entrepreneurs and experienced operators aiming to provide a differentiated experience across the investment lifecycle.

The firm manages $5.8B AUM (as of December 31, 2025) and has invested in more than 80 companies.

About the Role

Are you an aspiring AI Engineer eager to gain real-world impact and learn how to push AI’s boundaries? Imagine diving into diverse, cutting-edge AI problems across multiple high-growth companies with the support of a leading VC firm. That’s Georgian.

We’re not your typical VC. Georgian’s unique R&D team partners directly with our portfolio companies, providing the technical horsepower and strategic guidance to help accelerate their AI initiatives. We also play a critical role in our investment process, conducting deep technical diligence to identify promising AI-driven businesses.

Think of it as working in a dynamic startup environment, but without the inherent risks of a single venture. You’ll tackle fascinating challenges, meet and potentially work with brilliant founders and CTOs, and try to help unearth the next generation of industry leaders. It’s a fun, engaging, and highly impactful way to build your career.

Why This Role Exists

Georgian’s mission is to empower the world’s leading B2B software companies with an unfair advantage, accelerating their participation in the digital economy. As an AI Engineer Intern on our R&D team, you’ll support this mission by contributing to cutting-edge machine learning projects. You’ll assist in bringing machine learning expertise directly to our portfolio companies’ most pressing challenges, helping them build and scale potentially transformative AI products. You’ll also contribute to our investment process technical diligence, helping us identify innovative and technically sound companies.

What You’ll Own & Deliver

• Support AI system development. Assist in building LLM agents, Retrieval‑Augmented Generation (RAG) pipelines and fine‑tuned domain‑specific models under guidance; help implement workflows with frameworks like LangChain/LlamaIndex/PydanticAI.
• Contribute to portfolio projects. Support Georgian “strike teams” embedded in portfolio companies; assist with code implementation, testing, and documentation.
• Technical analysis & documentation. Help convert technical concepts into clear documentation; support preparation of demos and presentations for stakeholders.
• Hands‑on R&D support. Assist in rapid prototyping, run experiments and ablation studies, contribute to internal tech notes and documentation.
• Support AI roadmap development. Help gather requirements in discovery workshops, assist in documenting technical specifications and implementation plans.
• Contribute to safety & governance. Assist in implementing evaluation pipelines and testing frameworks to keep models reliable and compliant.

What We’re Looking For

Ideal Attributes

• Education & Experience: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Statistics, or a related quantitative discipline with a focus on machine learning, optimization theory, or related areas.
• Hands-On Foundation: Familiarity with deep learning toolkits such as Scikit-learn, TensorFlow, or PyTorch. Understanding of GenAI, LLM tooling and Context Engineering fundamentals.
• Software Development: Proficiency in Python and foundational software development skills, enabling you to write clean, efficient code.
• Problem Formulation & Communication: The ability to understand applied research problems, assist in designing experiments, implement solutions, and clearly document findings for diverse audiences with varying technical backgrounds.
• Collaboration: Demonstrated ability to work on team projects, collaborate effectively with technical …