For one exceptional Stanford student
Run the agents. Grow the company.
E2 is looking for a Stanford student who already understands AI agents deeply. Not as a novelty. As working systems that research, write, build, publish, sell, and improve. You will help run those systems and turn their output into reach, users, and revenue.
01Set the brief
02Run the agents
03Review the work
04Ship the improvement
05Measure and learn
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This is not a general helper job. We are not looking for someone to run a few errands. We need a sharp operator who can manage agent workflows, catch weak work before it ships, and keep pushing until the result is genuinely better.
Your mission
More reach. Better systems. More revenue.
You will work on live products and live agent workflows. The scoreboard is simple: useful work shipped, quality raised, more people reached, and more money earned.
Mission 01
Grow our reach
Turn strong work into distribution. Test ideas across the web, social platforms, communities, partnerships, search, and campus. Find the channels that compound and cut the ones that do not.
Mission 02
Make the agents better
Supervise workflows, review outputs, diagnose failures, improve prompts and handoffs, and build repeatable systems. Your job is not to babysit AI. Your job is to make it more useful.
Mission 03
Build revenue
Spot offers people actually want, improve pages and funnels, test messages and pricing, follow the numbers, and help turn attention into customers. Good taste matters. Commercial judgment matters more.
The work
What you will actually do
This role sits where AI operations, product quality, growth, and startup execution meet. You will own real pieces of work, not observe from the sidelines.
Agent operations
- Run and monitor agent workflows across research, content, product, and growth projects.
- Triage stalled work, unclear briefs, missing inputs, and broken handoffs.
- Turn one successful run into a documented, repeatable playbook.
Evaluation and quality control
- Score agent output against a clear standard and explain what falls short.
- Catch factual errors, weak reasoning, bland writing, and work that misses the brief.
- Compare approaches, choose the stronger one, and feed the lesson back into the system.
Growth experiments
- Help turn finished work into pages, posts, campaigns, and offers people can discover.
- Propose focused experiments with a clear hypothesis and a way to judge the result.
- Study what earns attention, trust, signups, and sales, then do more of what works.
Startup leverage
- Research users, competitors, markets, and distribution opportunities.
- Find bottlenecks that waste human time and design agent systems to remove them.
- Bring back concise recommendations, evidence, and a next action, not a pile of links.
The standard
Interested in AI is not enough.
We need someone who has already used agents to produce real work and can talk clearly about context, tools, evaluation, failure modes, and iteration.
Bring proof. Show us a workflow you built, a system you improved, or a result you shipped. Then tell us what still breaks and how you would fix it.
Who should apply
Built for a hard working builder
You do not need a perfect resume. You do need evidence that you are sharp, serious, and already operating at a high level.
You are the right fit if
- You are a current Stanford student who can protect real time for the work each week.
- You already use AI agents to do real work, not just to chat or summarize articles.
- You understand the moving parts: prompting, context, tools, structured output, evaluation, and human review.
- You think like an owner. You notice what matters, make a call, and finish the job.
- You care about growth and revenue, not only technical elegance.
- You write clearly and work fast without hiding behind vague updates.
Bonus points for
- Building with APIs, automations, scripts, or agent frameworks.
- Designing evaluations or catching subtle failures in model output.
- Running growth experiments, building an audience, or selling something online.
- Strong product taste and the ability to say why one version is better.
- Experience with startups, media, communities, or campus distribution.
- A portfolio, GitHub, demo, or written breakdown we can inspect.
RoleAgent Operator
Pay$30/hr + bonuses
SchedulePart-time, flexible
BasedStanford
Why this role
Responsibility earlier than usual
Real work from week one
Our agents and products are already live. You will help operate and improve real systems, not complete a pretend internship project.
Direct access
Work close to the founder and the core team. Bring ideas, challenge weak plans, and see how decisions get made in a growing company.
Proof you can point to
Build a track record in agent operations, quality systems, growth, and revenue. Strong work earns more responsibility.
Apply with proof
Do not send a generic application.
Send us a DM on Instagram with the code below and answer four things briefly. Specific beats polished. Links beat claims.
STANFORD AGENT OPS
- Your Stanford year and field of study.
- The best agent workflow you have built or run. What does it do, and what tools does it use?
- One weakness in that workflow. How would you improve it?
- One idea for E2. How would you help us reach more people or earn more revenue?
DM us on Instagram →
If you are only curious about AI, please do not apply. If you are already building with agents and want a harder, more consequential problem, we want to hear from you.