Deployed at Brain Co.

Two deployed engineers on what it takes to build AI products inside complex institutions.

Ammar Alqatari

Member of Technical Staff

Kanav Petkar

Member of Technical Staff

We’re an AI product engineer and AI/ML engineer in the rapidly growing deployed team at Brain Co.

Over the last year, we’ve shipped AI products into production across a range of complex environments, including government services, petrochemical companies, and healthcare organizations.


We’ve learned a lot from being embedded with customers, and want to share some of our learnings to help demystify what being a deployed engineer looks like. 

It was 40°C outside in this coastal Gulf country. The air shimmered over the hot asphalt as our teammate traversed a large chemical plant campus on foot. In the distance, he sees a rapidly approaching Land Cruiser. A client he had been working with had spotted him and insisted on driving him.

In the air-conditioned truck, the conversation got personal. The client wanted to know what AI meant for his son's future: what should his son study, whether their jobs were at risk. Our teammate told him he didn't have answers, “just opinions,” and to take them as such. From that point on, the client trusted him enough to reach out directly for almost everything from bugs to feature requests and platform walkthroughs. Not because he was the most technical person on the project, but because they'd had a real conversation.

That's one of countless small interactions that shape how our projects move forward as deployed engineers. Brain Co.'s mission is oriented around transforming the world’s most important institutions across public and private sectors with AI. Though it sounds abstract and daunting, on the ground, it looks like showing up and working alongside our partners every day. A lot of the job is just being there in person, sitting beside users while they walk through their painful workflows, walking over to an engineer's desk to unblock a data request, or chatting by the water cooler about houseplant care (a tip we learned from a customer: try talking to your sad houseplants. No, really!). All of those interactions help us foster much deeper empathy with our clients and allow us to build better products.

We’ve learned that real transformation, even as AI progress accelerates, takes patience, trust, and genuine relationship-building.

That’s nice, but what do you actually do?

We both came in expecting the job to be about 70% engineering, 20% client management, and 10% everything else. On average, this is true, though in reality, the ratio shifts project to project, person to person, and even week to week. Some weeks are all building, while others are knee-deep in user research brainstorming valuable use-cases. 

A typical week from our calendars: sprinting to ship a clinician workflow PoC Monday and Tuesday, flying onsite Wednesday to unlock a data request, and optimizing our medical coding model the rest of the week. Another week is two days of scoping sessions, a day of user shadowing, and then building a solution from those client inputs for the rest of the week.

The engineering work spans product surfaces, enterprise integrations, and deployment architecture. Much of our effort goes into building representative evaluations that reflect the messiness of production data. Reaching the accuracy levels required for real-world performance often means experimenting with the latest research and doing novel work where standard playbooks fall short. We spend a lot of time identifying the subspace of meaningful errors, hunting down long-tail failures, and iterating until our systems consistently clear this very high bar. And what we learn and build with each deployment makes Brain Co.’s platform better, helping teams build and ship the next product faster.

We've come to love moving across deep engineering work, product judgment, and the trust-building required to ship in real institutions. Each week feels different, but our mandate remains consistent: to make our projects successful while owning the process and its outcomes.

The team behind the work

When your week splits across many contexts, having a stable home base helps. Many of us live close to our regional office, and the culture there is tight-knit in a way that makes the constant context-switching sustainable. We grab meals together, compete over chess and pool, and can’t miss the Arabica coffee breaks that are often highlights of the day.

Our team reflects the institutions we work with. In any given week, we work with partners across different languages and functions, in Arabic, English, Urdu, Spanish, and others, in whatever language they feel most comfortable using. Our engineers come from almost every corner of the world. The people who thrive here are curious, adaptable, and genuinely interested in the places and organizations they work with.

En Fin

Trust compounds. A first meeting with a partner might just be a cup of coffee and a conversation, with the project discussion coming only after they’ve gotten to know and trust you. Once partners know we will show up, they call when something breaks, advocate for the product internally, and tell us when something is not working. Those relationships often become more than typical vendor-client dynamics, and they make our products better in ways that are hard to quantify but easy to feel.

As deployed engineers, we work at the boundary between engineering constraints and ambitious transformation goals. Most days, that looks less like grand strategy and more like showing up and doing great work, alongside incredible teammates and the people we are building for.

We're hiring at Brain Co. If you want to build AI products in production with some of the world’s most important institutions, get in touch.

Thank you to Matias for contributing his deployed perspective to this post!

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