How much of a company’s operations can one great engineer automate?

At Recall.ai, you’ll get to find out. We raised a $38M Series B led by Bessemer on the back of fast growth and a customer list of major names. We've done it all with a small team. You’ll build software that helps that team accomplish much more, and explore how a company can operate with today’s AI models.

You’ll be our eleventh engineering hire and the first dedicated to internal products. You’ll define the role, own the roadmap, and build tools your coworkers rely on every day.

Your first customers: sales and finance

Start with the work that brings in revenue and keeps it flowing: getting contracts signed, helping sales close deals, and making sure customers are billed correctly.

These workflows cross systems, teams, and spreadsheets. You’ll understand where they break, decide what’s worth fixing, and build the solution. Revenue tooling comes first; your mission is company-wide. As you learn the business, you’ll decide where to expand next.

How much operational scale can one engineer create?

Why this role is different

You’re founding the function. You’ll establish how we discover problems, prioritize work, and measure results.
Your work has immediate consequences. An improvement can unblock a deal, prevent a billing mistake, or give a team hours back every week.
You have room to experiment. Claude already helps run our office. You’ll have unlimited tokens and the freedom to explore what else the latest models can automate.
Your users are right here. You can spot a problem in the morning, work through it with the person affected, and ship an improvement they use that afternoon.

What you’ll own

Find the right problems. Work with sales, finance, and other teams to understand broken workflows, challenge proposed solutions, and define practical projects.
Build and run the tools. Own applications, integrations, and automations through deployment, adoption, and ongoing support.
Set the roadmap. In your first three months, take over ownership of the entire function and establish priorities with sales and finance. Expand into other workflows as you find opportunities.
Keep revenue moving. Resolve urgent sales and billing blockers, then fix their underlying causes.

Success means fewer manual steps, fewer errors, faster workflows, and tools people choose to use.

Who we’re looking for

You uncover what people actually need. You ask good questions, dig into workflows, and turn vague concerns into clear problems.
You’re comfortable explaining tradeoffs and pushing back constructively with non-technical users and identifying the core blocker and navigating around it yourself.
You have strong product judgment. You define useful first releases and know when a small improvement is enough versus when a workflow needs rethinking.
You can ship and maintain what you propose. You’re comfortable building applications, APIs, and SQL integrations.
You’re curious about how the business works. Experience with internal tools, CRMs, billing platforms, or AI automation is useful. Prior sales or finance experience isn’t required.

Is this your kind of work?

Expect substantial time exploring workflows, testing ideas, and making scope decisions alongside coding. Urgent business problems will sometimes change your plans.

If you want to build across a company, experiment with what AI makes possible, and see your work used by the people sitting next to you, we’d love to meet you.

Recall.ai is building a new hyperscaler for the world's largest dataset: conversation data. Our mission is to get all the conversation data in the world into a form that's accessible and understandable by AI.

Companies like Salesforce, HubSpot, Datadog, Rippling, Deel, Monday.com, Calendly, Asana, and Workday already work with us. Every software company of note is either already powering their AI features through Recall, or in a deal cycle with us.

They choose us because this problem is genuinely important and hard to solve.

Here's why our mission is important: 50-70% of an office worker's day is uncreative toil that AI can alleviate (e.g. sending emails, scheduling, drafting contracts, etc.). But AI is bottlenecked by context, not intelligence. Just like how humans get most context from conversations, we’re giving AI the eyes and ears to access the same conversation data set.

This is a brutal infrastructure problem because conversations happen all at once. At 9am Pacific, millions of people across North America click "start meeting" within 60 seconds of each other, every single hour. Our load graph spikes vertically at the top of every hour. Our weekly peak load is 4,000% higher than our weekly minimum. When Amazon built AWS, they built it to handle Black Friday, one day a year where millions of people hit their systems at once. We deal with the equivalent of roughly 240 Black Fridays a week.

We run nearly 100,000 computers in our cluster, processing the equivalent of 3,000 full length movies of raw video per second at peak load, and we're just getting started. All the words ever written in human history are still less than 20% of one year of US office conversations.

What makes this exciting is how early we are. We captured 0.02% of office conversations last year, just in the US. If in 5 years, 20% of tech forward companies want conversation context inside their AI tools, that's a thousand times more data than we process today.

Recall.ai

Founding Internal Products Engineer

About the role