Reddit Senior Software Engineer Igor Bulyga shares how the company built its unified payments architecture, why experimentation drives product growth, how AI is reshaping everyday engineering work.
A Unified Payments System: Building the Reddit Payments SDK
As Reddit's user economy expanded with initiatives like Awards, Collectible Avatars, and third-party developer integrations the company faced a growing need for a unified architecture to manage payments seamlessly. Previously, each product team maintained its own integration with Apple, Google, or Stripe, which created maintenance overhead, inconsistencies, and slower feature delivery.
"The main goal was to create one standardized system for handling payments across all platforms," Bulyga recalls. "We designed a modular SDK that abstracts common flows purchase validation, entitlement delivery, error handling, and analytics into reusable components that any team can implement."
This shift drastically reduced code duplication and made integration much faster. Features that once took months to develop can now launch in a matter of weeks. The Payments SDK has become the backbone of Reddit's User Economy, ensuring a consistent user experience, enhanced security, and streamlined compliance across iOS, Android, and Web.
Experimentation as a Product Growth Engine
At Reddit, experimentation is the cornerstone of product growth. Every change from small interface adjustments to large-scale launches is tested through structured A/B experiments. Teams begin with a hypothesis, define measurable outcomes such as engagement, conversion, and retention, and test the variations on randomized user groups.
"Every hypothesis is validated by data," Bulyga says. "We define the metrics, run controlled tests, and assign users randomly into test and control groups to see what actually works."
All user events flow through Reddit's internal analytics pipeline, providing near real-time visibility into performance. This tightly integrated workflow connects engineers, analysts, and product managers, enabling rapid iterations and data-informed decisions that directly shape the platform's direction.
Reducing Crashes and Speeding Up Safe Releases
Bulyga's team introduced a combination of architectural and operational practices that significantly improved the reliability and predictability of Reddit's mobile releases. These include modular architecture, automated telemetry and monitoring, real-time dashboards (using Grafana), automated regression testing, and gradual rollouts managed through feature flags.
"We made the release process as predictable as possible," Bulyga notes. "Metrics are collected in real time, automated tests run in the background, and new versions roll out gradually. That helped us reduce crash rates and dramatically increase the speed of safe releases."
With this setup, the team can confidently scale new functionality across multiple initiatives from Awards and Gold to the AI-driven Reddit Answers maintaining product stability and user trust even during peak traffic periods.
When Frontend and Backend Speak the Same Language
Another core focus of Bulyga's work lies at the intersection of client and server systems an area where alignment is essential for scalability and reliability.
"We start with a shared technical specification that clearly defines APIs, data schemas, and ownership boundaries," he explains. "Then we conduct joint design reviews with backend engineers to align on scalability goals, data models, and telemetry."
Regular async discussions and early prototyping allow both sides to develop in parallel, reducing bottlenecks. "The goal is for both layers to evolve in sync the client understanding server constraints and the server understanding the interface and UX requirements," Bulyga adds.
This model not only minimizes integration issues but also creates a more predictable, collaborative development rhythm one that scales across multiple systems and teams.
Engineering for LLM Products: The Case of Reddit Answers
One of Bulyga's most technically complex projects was Reddit Answers, a feature powered by large language models designed to improve search relevance and generate natural, high-quality responses. The challenges were substantial: ensuring low latency, managing context, and optimizing computational efficiency at scale.
"We designed a hybrid architecture," he explains. "Inference and ranking ran on the server, while the client handled caching, rendering, and feedback loops. That balance helped us maintain fast performance and high-quality answers on mobile devices."
The system was built with stability, safety, and user experience in mind delivering high-quality AI responses while meeting Reddit's internal standards for speed, reliability, and security.
How AI Is Transforming Engineering Work
AI has become deeply embedded in Reddit's engineering workflow. Neural networks now assist in code reviews, automatically generate unit tests, and analyze data, allowing engineers to focus on architecture, performance, and long-term impact.
"AI accelerates our entire development process," Bulyga says. "It automates routine tasks like reviews, tests, and data analysis, freeing us to think about architecture, design, and product decisions."
Bulyga also uses AI personally to validate architectural ideas early in the cycle. "AI lets me explore multiple solutions in parallel before committing to one. It doesn't replace engineers, but it changes how we think less time spent on mechanical work, more on creative problem-solving," he says.
Technical Depth as Part of Reddit's Engineering Culture
Reddit's open engineering culture encourages shared ownership and technical curiosity, values that have shaped Bulyga's professional approach.
"You can't just execute tasks here," he explains. "Every technical decision must be justified how it affects product metrics, why the approach was chosen, and what risks it mitigates."
That mindset pushes engineers to think beyond immediate implementation and view architecture as a system for managing complexity and growth. "Architecture isn't just code. It's the framework that allows you to scale and adapt," Bulyga says.
Trends iOS Engineers Should Watch
Bulyga highlights three major trends shaping modern iOS development today:
SwiftUI. "The biggest shift is the widespread adoption of SwiftUI. It's been around for six or seven years, but now it's finally mature enough for enterprise-level projects. Large companies tend to lag a few versions behind Apple's latest releases, but this is the moment SwiftUI becomes the default."
Swift Concurrency. A modern framework replacing callbacks and reactive programming for handling asynchronous code. "Migration takes time and planning," Bulyga notes, "but it's the right long-term direction for clean, maintainable architecture."
AI Tools for Development. "Every iOS engineer knows how slow Xcode can get on large builds," he says. "Many are switching to VS Code with Copilot or Cursor it's faster, lighter, and far more responsive than waiting for Xcode to compile."
