Every smooth digital payment hides a split-second chain of decisions — routing, fraud checks, and compliance, all happening in the background. This is especially true for a large company like Adobe, whose multi-billion-dollar subscription engine is built to process millions of these transactions daily, making sure they’re not just fast, but secure and compliant.
At the center of that system is Devang Gaur, senior product manager for Adobe’s payments platform, who ensures that a customer’s click turns into confirmed revenue with no technical hurdles. Here, he shares how to build global payment systems that scale, stay compliant, and keep working, no matter how complex the traffic gets.
Meet Devang Gaur
Devang’s work in payments began not with finance, but with code. After earning his engineering degree and working as a software developer at Dell Technologies in India, he moved into product roles and eventually pursued a master’s in software management at Carnegie Mellon University.
That transition brought him to the U.S., where he joined PayPal’s Braintree group and began working on the payment processing layer used by high-volume merchants. It was here that he developed a broader view of the payments stack, learning how processors connect with stakeholders like card networks and issuing banks.
That level of expertise and big-picture thinking eventually led Devang to Adobe, where he now leads payment systems that handle billions in recurring transactions every quarter. His job is to grow annual recurring revenue by reducing failed payments, strengthening fraud defenses, and driving backend improvements that directly impact performance. His efforts have been partly responsible for Adobe reaching a record revenue of $5.87 billion in its second quarter of fiscal year 2025.
Here are four of the main strategies he’s led as senior product manager.
1. Making Complex Paths Invisible
One of Devang’s main priorities at Adobe is ensuring everyday payments remain frictionless.
To the average customer, a successful transaction takes seconds. But behind the scenes, each charge moves through a web of processors, banks, and card networks, especially in a global company like Adobe. At this scale, even a routine renewal involves dozens of decisions that have to happen instantly and without error.
His team is responsible for making sure these handoffs stay invisible. “The goal is for the payment system to abstract all of that complexity for the user in order to provide a superior customer experience,” he says.
2. Remaining Compliant
Devang also works to ensure this technical billing complexity doesn’t expose the company to serious compliance risks. In Adobe’s subscription methods, users are often offline when the system charges their card. That makes compliance strict, since card networks require businesses to follow thorough regulatory standards when handling renewals.
This is further exacerbated by the fact that, since the company works with multiple processors in parallel, a user might sign up through one processor but later be billed through another, a mismatch that could trigger fines or cause Adobe to be flagged as a risky merchant if appropriate data elements are not used..
“When compliance breaks, it becomes a business-threatening moment,” Devang says. “Issuers start treating the company as risky, and more transactions get declined.”
To close those gaps, Devang led a company-wide overhaul to ensure that renewals stayed compliant, regardless of which processor handled them. His team focused on making the system consistent across all payment flows, helping Adobe avoid costly fines and protect its approval rates in global markets.
3. Tracking Payments With AI
Devang has also focused on using newer technologies to automate processes even further.
His team has incorporated machine learning models, a subset of AI that can scan hundreds of signals like card type, network processor, issuing bank, and user location in real-time to determine the best way to route each payment. These models track these signals automatically, boosting success rates while giving Adobe deeper visibility into millions of transactions.
As a result, Adobe has unlocked millions in new recurring revenue simply by making more transactions succeed behind the scenes.
4. Optimizing For Advanced Fraud Methods
Finally, Devang also continually tracks AI’s rapid growth to stay ahead of its risks, particularly in the fraud detection area. Tools that were once reserved for large-scale attackers (like card testing bots and synthetic identities) are now easily available. “Earlier, it took a while for a card attacker to figure out what card number range they could exploit,” he says. “Now with AI, all of that has become really easy.”
To keep ahead, his team is upgrading Adobe’s fraud defenses to catch more advanced threats, like self-learning bots that adapt to avoid detection. This means exploring the deeper technological risks behind what’s being known as “agentic commerce,” where AI agents make purchases on behalf of users.
“It’s still unclear what the implications of these are,” he says. “We’re experimenting internally so we’re ready when the guidelines come from networks and regulators and can make the right decisions for both our users and our business.”
Payments As Infrastructure, Not Just Cost
Devang Gaur is providing a more advanced blueprint for how companies can think about their payment methods. Instead of looking at it as an operational cost, he’s leading Adobe to treat its payment stack as strategic infrastructure, a system that can be enhanced to boost revenue, protect brand reputation, and lay the groundwork for an increasingly automated future.
