Founder's Office - GTM

Libra AI · Bengaluru

Apply on the company website

GTM Intern, Founder's Office (US Market)

Location: Bengaluru, in office, full week

Term: 6months fixed-term internship, with a full-time conversion decision in 3months based on performance

Reports to: Founder/CEO

What Libra is

Libra is an agentic Work OS, a company brain that connects to the tools a company already runs on (Slack, Gmail, Notion, Jira, Drive, Salesforce, HubSpot) and executes work across them rather than just searching them. Ask it to chase the open items from yesterday's customer call and it opens the tickets, drafts the follow-up, and posts the summary in the right channel.

We hold SOC 2, ISO 27001, and GDPR, and we sign BAAs. That matters more than it sounds, because it removes the single most common blocker in regulated US buying.

We sell from Bengaluru into the United States. That is the whole GTM motion right now.

Why this role exists

We are trying to answer one question: which specific job, for which specific US buyer, gets someone to pay us. We have competing hypotheses and not enough data. Until that is settled, everything downstream (the sales hire, the ad spend, the content plan) is guesswork.

You are the instrument we use to settle it. This is not a role where you shadow a founder and summarize meetings. You will build the target lists, write and send the outbound, sit on the calls, and own the notes that turn a pile of rejections into a positioning decision.

What you'll actually do

First, get loaded. Learn the product well enough to run a live demo of a couple of workflows without help. Read every call recording and every cold reply we have received. Build the first target account list against a written ICP spec: real companies, verified contacts, disqualifications logged with reasons.

Then, run the wedge test. Competing positioning hypotheses, tested head to head with founder-signed cold email. You own list build, enrichment, sequencing, deliverability hygiene, and the reply log. Every reply gets coded: interested, wrong problem, wrong person, no budget, silence. At the end you present which hypothesis produced meetings and why, with the reply data rather than a narrative.

Then, build the machine that works. Depending on what the test says, that means some combination of: scaling outbound on the winning message, prepping founder calls with real account research (their tool stack, their org chart, their recent hires, their public pain), maintaining CRM truth, drafting the sales collateral we keep not writing (security one-pager, pilot agreement, objection handling doc), and running competitive research on Glean, Dust, and whoever shows up next.

Throughout. You write the weekly GTM update: what was sent, what came back, what it means, what changes next week. One page. It goes to the whole company.

The bar

We evaluate on outputs, not effort:

What we look at What good looks like Target lists Every account defensible on its own terms, disqualifications logged rather than deleted Outbound Personalized well above template level, at real volume, without dropping quality Deliverability Clean domain, clean bounce rate, no shortcuts that cost us the sending domain Meetings Booked with people who can actually buy, not whoever will take a call The wedge test Concluded, defensibly, with data we can act on Collateral Sales artifacts drafted, shipped, and used on live calls

A wrong hypothesis killed cleanly and early is worth more to us than a calendar full of meetings with the wrong buyers.

Who this is for

Who this is not for

How to apply

Do not send a cover letter. Send the following to careers@trylibra.ai with the subject line GTM Intern, [Your Name]:

  1. A target account list you build yourself. US companies you believe would pay for Libra. Company name, why them in one line, the named person you would contact, and their title. Spreadsheet or doc, your call.

  2. Cold emails to a few of those named people. Short. Different companies, not the same email templated.

  3. One paragraph on which account you think is the worst fit on your own list, and why you left it in.

We read the third one first.

Applications reviewed on a rolling basis. If your list is good, you will hear from us shortly.

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