Atlassian is putting elite AI engineers directly inside its customers’ teams to accelerate AI transformation initiatives.
The role is called the Forward Deployed Engineer, and we’re scaling it fast. We have 46 engineers today and are moving quickly towards 100 by the third quarter, deployed across the US, EMEA, and India. In fact, they’ve already worked with more than 100 enterprise customers and put 80+ AI agents into production.
To understand the role, why Atlassian is investing in it now, and where it leads, we spoke with Paavany Jayanty, who leads AI Forward Deployed Engineering in the US.
Setting the scene
The FDE role itself isn’t new. The Forward Deployed Engineer was invented by Palantir in the mid-2000s, when its earliest customers, mostly intelligence and defense agencies, couldn’t fully explain their problems, share their data, or wait out a traditional software rollout.
Palantir’s answer: sending engineers to live inside those organizations, build against real conditions, and feed what they learned back into the product. The model was such a success that by 2016, the company reportedly employed more FDEs than traditional ones.
The AI era has brought the model roaring back: OpenAI, Anthropic, Databricks, and a wave of startups have all stood up FDE teams, and Andreessen Horowitz recently called it one of the hottest jobs in tech.
For Atlassian, it’s a natural fit. Enterprises already run their work inside our products, and our platform is built to turn one team’s solution into a capability every customer can use. This field-to-product loop is exactly what makes FDEs so powerful.
Unpacking the role
Leaders should start by understanding what an FDE is not: a consultant. Enterprises rarely arrive asking to “use AI.” They arrive with a business goal, like faster developer velocity, less time lost to busywork, or a service desk that keeps up with demand. In turn, the FDE’s job is to go build the thing that gets them there.
“An FDE is, fundamentally, a teammate for a customer to solve a business goal,” Jayanty says. “We embed a member of our team into the customer’s environment to solve a really important problem, and to maximize the value Atlassian can provide.”
The distinction from advisory work is deliberate. “We’re not consultants. We deploy a highly qualified, full-stack AI engineer with a very specific skillset into the customer’s environment to go solve that problem.”
How does it work?
It’s always a race to the next big thing in Silicon Valley. Today is no different; the ground is moving under every enterprise at once.
“With the advent of AI and agentic solutions, there’s been such an explosion in what’s possible that enterprises have to reconfigure how they work,” Jayanty says. “It’s an inflection point.”
The perennial challenge is that no two companies reconfigure the same way. That’s why any one-size solution is bound to fall flat.
“Every enterprise is a snowflake; no two are the same. You can’t take one solution and just go deploy it,” Jayanty says. “It has to be molded for their needs.”
That molding shows up in the results.
At Expedia, Atlassian FDEs have scaled AI-powered content operations across Confluence, archiving 600,000 pages and saving 3,200 hours annually. Himanshu Singh, an engineering manager at Expedia, said the Atlassian FDEs have helped teams “turn an ambitious idea into real business impact” and “simplify critical workflows, move faster, and build lasting confidence in how AI can improve the way we work.”
These changes start from the goal itself; never from the technology.
“Enterprises have a business goal. FDEs latch onto that goal and build the most cost-optimal, highest-ROI solution to get there,” Jayanty says. “We’re customer first, and we build with our products.”
Feeding the loop
What makes an FDE program a strategic bet (rather than a services line) is the loop it creates. FDEs don’t ship a solution and disappear; they carry what they learn in the field straight back into Atlassian’s product teams, grounded in the products customers already run.
“We don’t just deliver solutions,” Jayanty says. “We take the signal we get from customers and bake it back into our product teams, so it has a multiplier effect; every customer benefits.”
One customer’s hardest problem becomes a better product for everyone; that compounding factor is what makes the model worth scaling.
In practice at Atlassian, an FDE engagement is hands-on from the first conversation. The program is open to a select group of enterprise Cloud customers using Rovo, and it usually begins through an account executive or customer success manager.
From there, an FDE runs deep discovery, often via in-person workshop, to learn the business, its real pain points, and where AI can move a number that matters.
Then they pick one or two high-value use cases and build.
Case in point: at one financial institution, FDEs went from uncertainty to a working agent in a secure sandbox in under three weeks. A motorsports organization went from zero AI use cases to six production agents in under five months.
What started as a small pilot late last year earned the results to justify a major US expansion this past June, which is how a handful of engineers became 46 and, soon, will hit 100.
To the moon
Ask Jayanty where this goes, and she describes a default, not a niche. As building gets easier, she says, more of the people who make products should spend real time where those products are used.
“With building becoming easier, I’d argue every PM or engineer should be an FDE at some point. I think it should be mandatory,” Jayanty says. The payoff is a kind of discipline that’s hard to develop from a distance. When you’re embedded with the customer’s team, “you develop genuine customer empathy. You don’t have the luxury of building something people don’t want.”
“It’s humbling,” she says, “and that’s a muscle you want early.”
If one idea defines how FDEs work, it’s that transformation inside a large company is never purely a technical problem. “It takes two things,” Jayanty says. “The curiosity to leverage AI, safely, and the willingness to be nimble and improve. And you have to try, because enterprise change is as much cultural as it is technological.”
For all our lessons from the field, check out the Atlassian Forward Deployed Engineering Playbook.
