* Developed immersive carousel experience to drive customer traffic for major holiday events (Valentine’s day, etc.) using TypeScript, React, and GraphQL, achieving $140M+ GMV and exceeding revenue targets by over 10%.

* Built discovery experience homepage with a server-driven UI to speed up feature iteration speed by up to 3x and reusability using TypeScript, React, and GraphQL, for page with over 6M daily user traffic.

* Provided technical leadership and guidance to 5+ teams by serving as homepage component owner for server-driven UI library, driving adoption of 10+ projects  through RFC reviews, office hours, and knowledge-sharing sessions, enhancing development velocity and enabling seamless component reuse across multiple product surfaces.

* Functioned as key contributor to on-call runbook, providing clear documentation for setup and configuration of new carousels and troubleshooting live production issues, used by 10+ engineers across 5 teams.

* Developed customizable dashboard for visualizing AI driven sales forecasting data with JavaScript, Vue.js, D3.js, and Sass, providing enhanced visibility for staff and minimizing prep time by 50% for deal reviews.

* Boosted rendering performance by 35% through migrating codebase from Vue 1.x to 2.x, leading project and delegating work on team of 4 engineers; completed migration with no regressions 25% ahead of schedule.

* Engineered self-service admin module, enhancing interactive D3.js-based tree traversal with various atomic hierarchy and user management actions, reducing number of customer success support tickets by 25%.

* Created client-side routing with Vue-router, providing user with Deep Linking support on sharing, back buttons and bookmarking.

* Reduced bugs and minimized regressions in new features; improved design and component documentation by initiating unit and integration testing using Jest and Vue-test-utils.

Aviso is the AI compass that guides sales and go-to-market teams to close more deals, accelerate growth, and find their revenue True North. Aviso delivers true revenue intelligence, nudges team-wide actions, and gives precise guidance so sellers and teams don’t get lost in the fog of customer databases, scattered data lakes, and human biases. Fortune 500 and industry leaders such as Dell, Splunk, Honeywell, MongoDB, and FireEye use Aviso to drive more revenue, achieve goals faster, and win in bold new frontiers with an AI platform that supercharges guided selling. Aviso is backed by Storm Ventures, Shasta Ventures, Scale Venture Partners and leading Silicon Valley investors and is both an award winning Top 50 product for Sales and a 2019 Leader in G2 Crowd

* Led team of 6 engineers to bootstrap codebase to Vue1.x using JavaScript (ES6), Vuex state management, and Webpack, for better code quality and component reusability, improving team productivity by 2X.

* Optimized customer setup time by over 30% through architecting and implementing Deals module for sales executives to see forecasting data, utilizing Vue.js component design, JavaScript, Node.js and RESTful APIs.

* Refactored core business logic and provided convenience APIs to web and mobile apps to offload computing from devices to the browser by introducing Node.js-based (Express) middleware.

* Defined Git workflow and mentored team of 10+ engineers, improving productivity and code quality through efficient code review; minimized merge conflicts, and streamlined release cycle by 2X (14 days down to 7).

* Designed and implemented data acquisition pipeline in JavaScript and MySQL to extract torque tool PLC data using Kepware OPC Client, processed through Flexnet Machine Integrator and stored into relational database.

* Led project and coordinated with vendors to deploy torque tool machine integration into assembly line, enabling production ramping from 10 vehicles per week to 500 per week.

* Collaborated with senior electronics engineers in creating a new automated testing and data acquisition system by integrating instrumentations including PXI Chassis (a measurement and automation system), various sensors such as encoder and thermometer to test the function/performance/reliability of actuators/pedals, optimized the test plan period by 30%.

* Developed proactively a large-data analyzing tool in Labview, improved response time by restructuring data set, added additional graphing features, the solution upgraded the previous Excel tool which was limited by data size.

* Served as a technical liaison role between China engineers and US team during meeting and training sessions