SoloCo is building the operating system for AI-native companies.
SoloCo helps founders and small teams turn goals, SOPs, tools, and knowledge into agentic workflows, giving small teams the execution power of much larger organizations.
We believe AI is not just a smarter assistant. It is becoming the collaboration, execution, and decision-making infrastructure for a new kind of company. We are not building another chatbot; we are building the coordination layer for how companies operate in the AI era.
We are not only telling an AI story. We have built across model infrastructure, agent products, autonomous systems, and real enterprise workflows.
NTU MSc / Jiangsu Alumni Association
Serial founder in AI applications. Helped build AI energy-saving company Arloid, researched GPT-3 commercialization early at MiraclePlus, and scaled an Agent + crypto quant focus to 70M RMB.
HKU + Cambridge Engineering / Columbia Robotics
Robotics and control background with Columbia research experience, NASA ISS project work, senior autonomous-driving algorithm work, and leadership of an enterprise Agent technical committee.
Columbia MSc / AI Infrastructure
Led a 10-person Huawei team on LLM inference acceleration, KV Cache prefix storage, and high-performance C++ systems, spanning AI infrastructure, distributed databases, cloud native, and full-stack engineering.
Oxford Theory CS / Imperial Math PhD / Tsinghua Postdoc
Research background across theoretical computer science, model theory, and graph theory. Focused on the intersection of graph theory and multi-agent orchestration, from frontier research to engineering.
NTU MSc / Jiangsu Alumni Association
Serial founder in AI applications. Helped build AI energy-saving company Arloid, researched GPT-3 commercialization early at MiraclePlus, and scaled an Agent + crypto quant focus to 70M RMB.
HKU + Cambridge Engineering / Columbia Robotics
Robotics and control background with Columbia research experience, NASA ISS project work, senior autonomous-driving algorithm work, and leadership of an enterprise Agent technical committee.
Columbia MSc / AI Infrastructure
Led a 10-person Huawei team on LLM inference acceleration, KV Cache prefix storage, and high-performance C++ systems, spanning AI infrastructure, distributed databases, cloud native, and full-stack engineering.
Oxford Theory CS / Imperial Math PhD / Tsinghua Postdoc
Research background across theoretical computer science, model theory, and graph theory. Focused on the intersection of graph theory and multi-agent orchestration, from frontier research to engineering.
Every role has real tasks and visible output. No busy work, no shadowing.
Own frontend modules from design to launch, build data interfaces, and get code merged in week one.
HTML/CSS/JS fundamentals required. React, Next.js, or database experience is a plus.
const page = KVCache.allocate(seq); prefill(page.blocks); agent.route(taskGraph.next());
Build workflow nodes for AI agents, integrate frontier model APIs, and improve memory, delegation, and execution.
Python and basic API skills required. OpenAI, Claude API, or RAG experience is a plus.
Stress-test AI behavior, research competitors, and turn findings into product improvements.
No coding required. You need rigorous thinking, clear writing, and product intuition.
Own the intelligence behind what we build and the networks that adopt it. Drive market, competitive, and product research that shapes the roadmap — and operate Soloco's open-source community alongside the closed-beta program where the agent OS earns its trust.
Strong research, clear writing, and community communication are required. Open-source, AI product, or developer ecosystem experience is a plus.
We care less about grades and more about what you have built, noticed, and questioned.
Not because it is trendy, but because you have real opinions about what it changes.
You question assumptions, ask better questions, and push ideas forward.
Code, product, experiment, research project. The domain matters less than the doing.
Most technical docs are in English. Reading fluency is enough.
High school graduates, gap year students, and deferred admits are welcome.
This is an in-person program at the Xuhui Waterfront office.
Interns are treated like early team members: accountable, visible, and close to the work.
Own features from brief to deployment. Your name is in the commit history.
Work directly with the CTO and founding team. No layers, no busy work.
Use frontier model APIs and GPU resources. Hardware should not limit your ideas.
Pair one-on-one with mentors across product, engineering, AI application, and career growth.
A modern office on Shanghai's Xuhui Waterfront with fast equipment and strong team energy.
The program runs 8-12 weeks. Outstanding interns may receive full-time offers.
In-person collaboration with the team, close to the product and the decisions.
No formal resume required. Tell us who you are, what you are curious about in AI, and something you have seriously worked on. We will read it carefully.
Open Form