Lead Frontend Engineer
Role:Lead Frontend Engineer(8-12 Years)
Location:Bangalore
About Tekion:
Positively disrupting an industry that has not seen any innovation in over 50 years,
Tekion has challenged the paradigm with the first and fastest cloud-native automotive
platform that includes the revolutionary Automotive Retail Cloud (ARC), Automotive
Enterprise Cloud (AEC), and Auto Location motive Partner Cloud (APC). Tekion
connects the entire spectrum of the automotive retail ecosystem through one seamless
platform. Tekion employs close to 3,000 people across North America, Asia, and
Europe.
We are seeking a Lead Frontend Engineer to be the technical anchor for our frontend capability. This role goes beyond feature delivery; you will define the frontend architecture, establish the component design system, own the Next.js application structure, drive performance standards, and mentor senior and mid-level frontend engineers. You will build the most complex, data-intensive UI surfaces: real-time attribution dashboards, AI-powered campaign builders, and platform-embedded intelligence widgets, all in a React + Next.js stack integrated with Elasticsearch-powered search and streaming AI responses.
Responsibilities:
- Own and evolve the frontend architecture: Next.js App Router structure, component boundaries, state management strategy (Redux), and data-fetching patterns applying hexagonal UI principles where the component layer is decoupled from specific backend service contracts.
- Design and build the most technically complex UI surfaces: real-time attribution dashboards (streaming data), AI-powered campaign builder (LLM response streaming), Elasticsearch-backed customer search with faceted filtering, and platform-embedded opportunity cards.
- Define the component design system: Atomic component library, theming contracts, accessibility standards (WCAG 2.1), and Storybook-based documentation.
- Establish frontend performance standards: Core Web Vitals targets, bundle size budgets, SSR/SSG strategy with Next.js, lazy loading, and virtualisation for large data tables.
- Lead Next.js architecture decisions: App Router vs. Pages Router tradeoffs, RSC (React Server Components) applicability, streaming SSR for AI-generated content, and API route design.
- Integrate AI-native frontend patterns: streaming LLM responses into UI components, real-time score updates from Redis/Aerospike via SSE, and Elasticsearch typeahead search.
- Drive code quality through design reviews, code reviews, pair programming, and frontend-specific engineering standards.
- Mentor senior and mid-level frontend engineers, setting the bar for component design, test coverage, and performance discipline.
- Collaborate closely with backend staff engineers to define API contracts and with designers to implement pixel-perfect, accessible UIs.
Requirements:
- 8+ years of frontend engineering experience with deep React and Next.js expertise in production systems.
- Mastery of Next.js 14+ App Router, React Server Components, streaming SSR, and static generation, knowing when to apply each pattern.
- Strong TypeScript expertise: type safety across component props, API contracts, Redux store shape, and server/client boundaries.
- Deep Redux expertise: slice design, selector optimisation, middleware patterns, and RTK Query for data fetching.
- Proven experience building data-intensive dashboards with real-time data (WebSocket, SSE, or polling) and chart libraries (Recharts, D3.js ).
- Experience integrating Elasticsearch-powered search UIs: typeahead, faceted search, and result ranking display.
- Strong frontend performance engineering: bundle analysis, code splitting, memoisation, virtualisation, and Core Web Vitals optimisation.
- Experience in establishing and maintaining component design systems with accessibility standards.
- Must have proven experience leading front-end development teams, mentoring engineers, and driving technical decisions to deliver high-quality solutions.
- Experience mentoring engineers and raising the technical bar across a frontend team.
Good to Have:
- Experience streaming LLM/AI-generated content into React UI components (token streaming, partial rendering patterns).
- Familiarity with platform-embedded micro-frontend patterns (module federation or iframe-based embedding).
- Background in automotive retail, eCommerce analytics, or SaaS BI/reporting platforms.
- Experience with Storybook for component documentation and visual regression testing.