Billions of users today can click “opt-out,” “reject all,” or “manage settings.” But what happens after that click? Too often, not much. Most digital systems still treat user control as a front-end gesture, a cosmetic nod to regulatory expectations, rather than a persistent architectural commitment. Preferences fade, data flows resume, and systems quietly revert to defaults.
Shaurya Jain, a seasoned software engineer, and a senior IEEE member, has spent the last few years confronting this very problem. Working across privacy infrastructure and monetization pipelines at one of the largest platforms on the planet, Jain has focused on building the internal frameworks that track, honor, and enforce user preferences at scale. His work bridges the theoretical promise of user choice with the practical demands of global systems engineering.
"User control means little if the system forgets it a few API calls later. Designing for control is not a UI problem, it is an architectural responsibility," he explains.
Most privacy tools operate at the user interface level: toggles, switches, consent banners. But as platforms fragment into microservices, modular teams, and increasingly dynamic third-party integrations, the flow of consent across a system becomes brittle. Consent given on one device is often not honored on another. Preferences decay after product updates. Backend monetization services frequently bypass or misinterpret UX-level privacy decisions. In some cases, even regional laws force platforms into inconsistent behavior across geographies.
"Engineering privacy starts where UI ends," Jain notes. "The gap between what users choose and what systems execute is where trust erodes."
This implementation gap represents a growing fault line in platform design. No amount of elegant UX can make up for infrastructure that silently disregards user intent. As Jain emphasizes, solving this means going deeper: embedding choice into the very fabric of data and revenue systems.
To meaningfully honor user control, platforms must shift from surface-level toggles to deeply integrated control logic. This begins by treating user preferences as a first-class data model, not ephemeral flags stored in local caches, but persistent entities synchronized across services.
Jain’s work focused on exactly this challenge. In leading the development of scalable backend systems for responsible monetization, he helped implement a framework that allowed user consent preferences to persist across Facebook and Instagram. This meant integrating consent logic into ad delivery systems, personalization engines, and downstream data pipelines, so a user's choice at the point of entry echoed throughout the entire stack.
"We had to rethink how preferences cascade," he says. "A user's decision at the point of entry should echo across all downstream systems, whether that’s ad serving logic or data warehouse ingestion."
Key to this was an event-driven pipeline that could broadcast changes in consent across system components, along with fallback protocols that ensured continuity even in offline or degraded conditions. Geo-aware logic and modular registries provided enforcement consistency across regulatory zones.
As a paper reviewer for the International Journal of Advancements in Computational Technology, Jain has also contributed to shaping industry discourse on privacy-preserving infrastructure design.
The challenge was not just storage, it was enforcement. A platform must ensure that every internal system respects the same version of user choice, regardless of how or where that choice was captured.
While much of the public debate on control focuses on privacy, the deeper engineering problem often lies in monetization. Personalization logic, the core of most digital revenue systems, defaults to maximizing conversion. But ethical engineering demands something more nuanced: monetization systems that adapt to user preferences without manipulating or punishing the user.
Jain’s work underscores this principle. He contributed to backend systems that enabled hybrid monetization models, allowing users to toggle between ad-supported and subscription-based experiences, and ensuring that choice was respected by the underlying revenue engines.
"Monetization logic cannot exist in a vacuum," he says. "If we claim to offer control, the business logic must follow, without reducing the user to a statistic."
This required building fallback strategies for limited-data scenarios, enabling graceful degradation of features, and training AI systems to operate within stricter data minimization constraints. The result was not just regulatory compliance, it was a monetization framework that could flex around user dignity.
Jain’s commitment to ethical monetization has also earned industry recognition, including a Stevie Award for Technical Professional of the Year (Bronze), a testament to his impact at the intersection of scalable systems and principled design.
In this approach, trust becomes a design boundary. Revenue systems are not exempt from ethical architecture; they are central to it. Systems that treat user dignity as a boundary condition will outperform in retention, brand equity, and long-term adaptability.
User control is no longer about checkboxes or pop-ups. It is about designing for longitudinal trust, where user intent, once expressed, becomes a system-wide invariant. This shift requires more than new features. It demands a new mindset.
In the future, control systems will be inherently cross-device, cross-region, and cross-surface. Privacy taxonomies will evolve from binary toggles to contextual, adaptive permission models. Consent orchestration will be seen not as compliance overhead, but as a core infrastructure layer, on par with observability, authentication, or billing.
As explored in his Hackernoon article, ‘The Internet’s New Privacy Tax: Consent or Pay’ Jain critiques coercive consent models and emphasizes the need for backend systems that encode user autonomy by design. These are not theoretical aspirations, they are the principles guiding the engineering frameworks he now helps build.
"The next decade of engineering will not be defined by what systems can do, but by what users can decide they should not," Jain concludes.
For engineers building at scale, user choice is no longer a design option. It is the blueprint.