Why this role exists
neatlogs helps teams understand why their AI agents fail in production, fix the cause, and check whether the fix worked. The product is live, and since launch more teams have been asking to see it.
Our founder, Ajay, currently takes every sales call, runs every demo, and handles the follow-up. That gave us a direct way to learn from early customers. It cannot remain our entire sales process.
We need someone who can own opportunities from first conversation to close, while working out which teams we should pursue, what makes them buy, and how to make the next deal easier to win. You’ll make strategic calls and do the work behind them: prospecting, discovery, demos, follow-up, negotiation, and closing.
What you’ll work on
- Own deals end to end. Respond to inbound interest, find promising teams yourself, run discovery and product conversations, keep momentum through technical evaluation and procurement, and close. Follow up thoughtfully and keep a clear record of what happened and what comes next.
- Find the right customers. Work with Ajay to decide which agent teams have a problem we can solve now. Test segments, use cases, buyer roles, and ways of reaching them. Build pipeline from scratch instead of relying on launch attention to fill it.
- Sell a technical product honestly. Learn enough about traces, evaluations, investigations, and agent workflows to understand a buyer’s system and show the part of neatlogs that matters to them. Bring an engineer into a conversation when depth is needed. Be direct about what the product does today and what it does not.
- Build the sales motion from real deals. Work out which questions reveal urgency, who needs to be involved, what a useful trial looks like, and where deals get stuck. Write down what you learn and improve the demo, follow-up, qualification, and handoff.
- Bring the market back to the team. Share the objections, missing capabilities, language, and unexpected use cases you hear. Separate one loud request from a pattern worth acting on. Work with product and marketing to make the experience and the story better.
Your first few months
- Month one: Join Ajay’s active conversations, learn the product and early customer stories, take over follow-up and selected opportunities, and identify where promising deals lose momentum.
- Months two and three: Own a growing set of opportunities from discovery to close. Build a focused outbound approach for one or two customer profiles, and turn what you learn into a repeatable demo, qualification criteria, and a clear trial or evaluation path.
- After that: Own a pipeline you can explain: where opportunities came from, why they move or stall, what is closing, and which parts of the sales motion need to change. Help us decide when to add more people and what they should inherit.
What good work looks like
A head of AI tells you their agent occasionally gives the wrong answer, but they already have tracing. You ask what happens when someone reports a bad outcome, who investigates it, and how they know a fix worked. You show a relevant workflow, agree on what a successful evaluation would prove, and make the next step easy for their team to take.
You can run the demo and the follow-up yourself. You also notice that the same objection keeps appearing in other deals and change the way we qualify, explain, or demonstrate the product. When a deal is a poor fit, you say so early.
The goal is customers who understand what they bought and can actually use it.
What we’re looking for
- You’ve sold software to technical buyers in the US and closed deals yourself. You can explain a deal from first contact to close, including what you personally did when it stalled.
- You’ve built pipeline in an early or uncertain market. You know how to find a promising account, start a relevant conversation, and change your approach when a segment does not respond.
- You can run discovery that reveals the actual problem, not just gather requirements before a demo.
- You’re comfortable with engineers, AI teams, and product leaders asking detailed questions. You don’t need to know every answer on day one, but you learn quickly and never bluff.
- You can make a sales plan, test it in real conversations, and revise it from the evidence. You keep enough structure to know what is working without waiting for a playbook to appear.
- You write clear follow-ups, manage several deals without losing the thread, and tell Ajay when your read of the market differs from his.
| We look at | We don’t weigh heavily |
|---|---|
| Deals you personally sourced, advanced, and closed | A large number from a mature sales organization without your specific contribution |
| How you learned which customers to pursue | An impressive pipeline number without deal quality or outcomes |
| Your judgment in technical, messy sales cycles | A polished sales methodology you cannot adapt |
Experience selling developer tools, observability, or AI infrastructure helps. Strong 0-to-1 sales judgment and the ability to learn the product matter more.
The working reality
You’ll be our first dedicated salesperson. Ajay will stay close to customers and important deals, but this role exists so he is no longer the person moving every opportunity forward. You’ll have his context and access to the team, and you’ll be expected to make calls yourself.
Some leads will come to us. Others you’ll have to find. The product, pricing, customer profile, and sales materials will keep changing as we learn. You’ll spend time on individual deals and time deciding which part of the process to improve next. There is no team to manage yet.
This probably isn’t the right role if you want a settled territory, a mature enablement function, or a job that is mostly sales strategy without closing deals.
About neatlogs
neatlogs helps teams understand why their AI agents fail in production, fix the cause, and check whether the fix worked. It connects production traces with the judgment of the people who know what the agent should have done, then helps the team investigate what happened and decide what to change.
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