Breaking Into AI Sales: Who Gets Hired and How

You read about AI companies hiring salespeople, open a few postings, and most of them want years of experience you don't have. That's normal. Only a few seats are built for people coming in from outside.

Most people get into AI sales through one of two doors. The first is an SDR or BDR seat, the job of booking first meetings, which accepts little or no sales experience. The second is a move from a sales, technical or customer role where you already have a track record.

The AI part matters less on day one than the postings make it sound. What they screen for is proof that you can find customers, run a conversation, and learn a technical product fast.

This guide shows which seat fits your background and gives you a 90-day plan to get it. It's built from 23 AI sales postings opened live on September 26, 2026 and listed in the directory of companies hiring AI sales roles. Postings change, so treat the quotes as a snapshot.

The five seats and what they ask for

The pattern is plain. Only the SDR and BDR seats are open to people without sales experience, and only three of the 23 postings say so outright: Rogo's SDR, Legora's BDR ("Internship or campus selling experience are welcomed") and Clay's ClayDR ("open to exceptional entry-level candidates as well"). Every other seat wants years of doing a closely related job.

Pick the door that matches your background

The fastest route reuses what you already have. Here's where each background tends to fit, based on what the postings accept.

No sales experience. Aim for SDR or BDR. The postings that welcome newcomers want proof you can handle volume and rejection: campus selling, recruiting, or anything "outbound-heavy," as Rogo puts it. And know that promotion to account executive is not automatic. The Bridge Group's 2025 SDR report, a survey of 351 B2B companies, says promotions fell to 16%, from 34% in 2020.

SaaS sales, not AI. Your quota history carries over. Apply for the same seat at an AI company, and prepare for the parts that differ: pricing based on how much the customer uses, pilots judged on the customer's own data, and more technical people in the buying decision. What is different about selling AI walks through each one. Several postings ask for AI experience only as a plus. Decagon's enterprise AE lists "Previous experience selling AI or Customer Support/Experience software" under "Even better if you have."

An industry, not sales. Vertical AI companies hire for the customer's world. Harvey's mid-market CSM welcomes "Experienced professionals from legal firms," and Rogo sells into "banks, PE, asset managers." Anthropic's BDR posting accepts experience in "finance & investment banking, consulting or software engineering." If you know how a law firm or a bank buys, find the AI company that sells to it.

An engineering or technical role. Sales engineering is the natural seat, but the postings want pre-sales experience (helping close deals), not just engineering. A common bridge is a customer-facing technical role first: solutions, support engineering or implementation. The GTM engineer, RevOps and sales engineer comparison and what a forward-deployed engineer does show the neighboring seats.

Support, success or consulting. Customer success and account management fit best. Replit's account manager posting counts customer success and technical sales, and Anthropic's CSM counts technical account management. Bring numbers you can defend: accounts managed, renewals, expansions.

An example: from paralegal to BDR

Here's how that sorting works for one made-up person.

Maya has spent three years as a paralegal at a mid-size law firm. She has never had a quota. She knows how a firm decides to buy software, because she sat in on the last two tool reviews.

She has no sales track record, so the AE and sales engineer seats are out for now. Her industry knowledge is the asset. So she targets BDR seats at AI companies that sell to law firms. There, her background is the reason a hiring manager calls her back.

Her account brief in the plan below is about a real law firm, written in the language a managing partner uses. That's something a generic candidate can't easily copy.

A 90-day plan

This plan assumes you're going after one seat at a short list of companies. Each block ends with something a hiring manager can look at.

Days 1 to 30: learn the product category and choose targets

1. Pick one seat from the table and one to three segments you understand: developer tools, legal, finance, customer support, public sector.
2. Build a list of 10 to 15 target companies. Start with the hiring directory, then add companies selling into your segment.
3. Learn enough of the technology to run discovery without guessing. The AI APIs beginner guide covers tokens, models and API calls. Sign up for the free tier of two or three target products and use them on a real task.
4. Read each target's pricing page and write one line on how it charges: per user, by usage, per result, or a mix.

Deliverable: a one-page target list with, for each company, what it sells, who buys it, how it prices, and one open role.

Days 31 to 60: build proof a hiring manager can check

1. Write an account brief for one real prospect of your top target company. Who at that prospect would buy, what problem they have, what public evidence supports it, and what you would say in the first message. Keep it to one page and cite your sources.
2. Draft a short outbound sequence to that prospect: three messages, each with a different reason to reply. The AI SDR outbound playbook covers the structure.
3. Write a pilot plan for the same prospect: what they'd use the product for, how success gets measured, the sample of their data you'd ask to test on, and the timeline. This shows you understand how AI deals close.
4. Practice a discovery call out loud with a friend playing the buyer. Record it and listen back for how much you talked.

Deliverable: the account brief, the sequence and the pilot plan, as three short documents you can attach or link.

Days 61 to 90: apply, reach out and interview

1. Apply to the roles on your list. For each one, send a short note to the hiring manager or a rep on the team, with your account brief for their company attached. That note is the job itself, done once, for free.
2. Run the pay for every live posting through the AI Sales Pay Calculator, and read how OTE and sales pay plans work so you know what to ask about quota, split and ramp.
3. Prepare for interviews with the role-specific guides: the AI SDR and BDR interview guide or the AI account executive interview guide. Expect a mock call and a question about how you would handle a pilot.
4. Track every application, conversation and result in a simple sheet. After 30 days, look at where you stall and fix that step.

Deliverable: applications out, a record of responses, and at least one mock or real interview completed.

What the pay looks like at the door

Entry-level pay in these AI postings mostly sits at or above the cross-industry median. The Bridge Group's 2025 report puts median SDR on-target earnings (OTE, meaning base plus commission if you hit your target) at $80K. The SDR and BDR postings in the directory range from Legora's "OTE $75,000 – $91,667" in Denver to Anthropic's $116,480 to $131,040, which that posting defines as OTE, in San Francisco and New York. Clay's ClayDR pays a "Fully Guaranteed Base" of $90K to $110K with no commission stated.

Those numbers aren't comparable at face value. Some are base salary, some are OTE, and the locations differ. Put them through the calculator at a realistic attainment before deciding which one is better.

Where to go next

• The AI SDR and BDR career guide and the AI account executive career guide go deeper on the two most common entry seats.
• How to run an AI sales cycle shows what the account executive's job looks like once you're in.
• The career transition guide covers moving into AI from other fields more broadly.