Goel Taran didn't become a key frontend architect in AdTech and Media Tech overnight. Before Amazon Ads, he helped build media and content platforms for global clients while at Nagarro, including re-engineering dashboards and systems for a major media team. At Amazon Ads, he joined as the first frontend engineer in a major ads division and helped turn a legacy stack into a platform that now serves tens of thousands of ad placements and powers new formats like video and native ads.
In this interview, he opens up the "kitchen" of Amazon Ads: how you build a frontend culture from scratch, convince teams to invest in design systems, and make architectural bets without breaking trust. He also shares advice for engineers moving into leadership and reflects on the future of frontend in a world of strict privacy, AI-driven experiences, and fast-changing digital advertising rules.
Taran, you were the first frontend engineer in a major Amazon Ads division. Where does one start when building a frontend "from scratch" inside a huge tech company, when there is still no established culture, processes, or engineering standards for the FE team?
We started by turning a legacy system written by SDEs into a frontend-focused platform built for Amazon Ads scale and velocity. I defined a North Star: a responsive, component-driven, config-based architecture that would not be limited by fixed viewport sizes and could support thousands of ad layouts.
To make that real, we adopted a design-system-first approach. I introduced a reusable component library, a 4-point-grid-based template system, and performance guardrails wired into CI—including Lighthouse-based performance budgets and client-side metrics—and we brought in Storybook for UX reviews while standardizing our tooling and review practices. Over time, this evolved into a scalable design system that new features and ad formats could be built on top of.
The architecture and guidelines were captured in lightweight design docs, reinforced through regular design and code reviews, and supported by mentoring for new and existing engineers. That combination of North Star, tooling, and culture acted as a force multiplier: we grew from a handful of ad slots to more than 20,000 supported ad sizes, increased developer velocity, and made this frontend approach the default for new formats and future Amazon Ads projects.
Tell us more about building a scalable design system—how did you convince product and engineering teams to invest time into a design system? And how did it impact development speed, UX quality, and the consistency of Amazon Ads products?
For me, the design system was never the goal in itself, but a prerequisite for the outcomes that really matter to the business: faster roadmaps, higher quality, and fewer regressions.
We unified our design tokens and components around a 4-point grid system and built a shared component library that acted as a quality gate. The library was wired into CI with accessibility checks and performance budgets, so any new UI had to meet our standards before it shipped.
The impact was tangible. Responsive layouts became the default instead of a special case, rework dropped, and UX became consistent across surfaces. Review cycles with designers were shorter, we could clearly measure which components and patterns drove the most engagement, and we shipped new ad formats faster and with less risk.
How do you make architectural decisions so that innovation does not break the ecosystem, but accelerates its growth? How do you explain the "cost of technical debt" to leadership in business language?
Balancing innovation with stability starts with being explicit about tradeoffs. For any major architectural change, I document the options, the risks, and a clear mitigation plan. I also translate technical debt into developer-months: how much future capacity we are giving up because we chose a shortcut today. That framing helps leadership understand debt as lost feature velocity, not just "code quality."
At Amazon's scale, we can't afford to break customer trust, so I ship new architecture progressively. We design modular boundaries, use feature flags, invest in integration tests, and monitor real-time metrics so we always have a pulse on the system. That gives us the ability to ramp up new designs, validate impact, and roll back quickly if something doesn't behave as expected.
How can a frontend leader go beyond being "just UI" and become a strategic partner for product, business, and external partners?
Frontend stops being "just UI" when you own the end-to-end story—from business goals to how customers experience the product. In discussions with product and external partners, I speak in terms of funnels, time to market, and KPIs, not React props or build tooling.
Practically, that means proposing reusable libraries, shaping what is technically feasible for new ad formats or partnerships, and reusing community-tested solutions where it makes sense. In Amazon Ads, this mindset helped us open new revenue streams—for example, launching video and native ad formats and enabling partnerships like Pinterest—because frontend was treated as a strategic lever, not just a presentation layer.
Which metrics and analytical approaches do you use to prove the impact of frontend on a product's P&L? What do you consider the "right set of KPIs" for a frontend leader?
Frontend metrics are essential and directly inform product and revenue decisions. On the business side, we track engagement and conversions through experiments, and for ads specifically we monitor viewability and video view-through or completion rates.
On the technical side, we track p50 and p90 latency, accessibility compliance, and error rates from real traffic, and we enforce performance budgets such as TTI and FCP. The key mindset shift for frontend engineers is to connect these: better UX improves funnel metrics, and better web performance translates into higher engagement and a healthier P&L.
Given your experience in building teams and growing talent, tell us which principles guided you when hiring and forming the team. Which qualities are important for frontend leaders in AdTech and Media Tech?
I look for engineers who combine product sense with strong technical skills. They should be able to think beyond a single component, understand the platform and business they are building for, and defend design tradeoffs using data. Tests and metrics need to be first-class for them, not an afterthought.
On my side, I keep the bar high with written coding guidelines, structured code-review checklists, and active mentoring. Over time, that creates a team culture where engineers care about UX, performance, and business impact as much as they care about clean code.
What is the key advice you would give to engineers transitioning from the role of a "senior developer" to a leader and architect? Which skills—both technical and soft—become critically important if the goal is to influence the product and business through frontend?
The key shift is moving from "How can I build this?" to "What should we build, and why does it matter?" As a senior engineer you can own an implementation; as a leader or architect you need to own the problem framing, the tradeoffs, and the risks.
Another critical skill is scope negotiation and alignment—working with multiple teams to find a plan that respects timelines without compromising the architecture. You become a force multiplier when your mechanisms help other engineers grow: design reviews, reusable patterns, clear guidelines, and mentoring. At that point, your impact is measured less by how much code you write and more by how much better and faster the whole team can ship.
Tightening privacy policies, the blocking of third-party cookies, and AI regulation—all of this is changing digital advertising and frontend products. How do you think UX and ad personalization will look in 2–3 years? What should frontend leaders already take into account today to avoid becoming "yesterday's news"?
We'll see more consent- and context-aware experiences. The industry is already shifting from tracking individuals across the web to understanding context and using privacy-safe first-party signals.
For frontend leaders, that means designing experiences where users clearly understand what they're opting into, and systems that can still personalize based on intent, content, and on-site behavior without relying on invasive tracking. The teams that do this well will treat privacy and UX as core parts of the product, not as a compliance checkbox. Those who get it right will be the ones defining what "good" looks like in the next wave of digital advertising.
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