Senior Full Stack Developer with AI-driven workflows

Christopher Wei Senior Full Stack Developer

+1-737-***-**** *********.****@*****.*** https://www.linkedin.com/in/chrisjwei/ Austin, TX SUMMARY

Full Stack Developer with over 9 years of experience designing and shipping user-facing web, desktop, and mobile applications powered by React, Node.js, Electron, and AI-driven workflows. Across recent roles, built production-grade systems integrating agentic capabilities, REST APIs, React Native with Expo, and OpenShift container deployments that served real customers at scale. Brings end-to-end ownership from frontend UX through backend services, with a collaborative approach to translating complex AI system outputs into reliable, trustworthy product experiences.

TECHNICAL SKILLS

Frontend: React, React Native, Expo, Electron, JavaScript, TypeScript Backend: Node.js, REST APIs, multi-tenant architecture, WebSocket AI and Agentic Systems: agentic workflow integration, AI-powered feature design, intelligent automation Containerization and Infrastructure: OpenShift, Kubernetes, cloud deployment, microservices Mobile and Cross-Platform: React Native, Expo, web, desktop, mobile development Databases: SQL, relational database optimization, indexing Analytics and Monitoring: usage instrumentation, analytics integration, performance monitoring EXPERIENCE

Software Engineer April 2022 – Present

Optiver Austin, TX

• Redesigned the core trading dashboard as an Electron desktop application, replacing a legacy web-only interface with a cross-platform shell that cut trader workflow friction by 35% across 3 platform environments.

• Architected a Node.js backend service layer exposing 40+ REST API endpoints to feed real-time market data into frontend components, reducing average data-fetch latency by 28%.

• Built a React-based live risk monitoring interface that surfaced P&L, Greeks exposure, and position limits in real time, giving traders immediate observability across 5 active asset classes.

• Integrated an agentic position management module into the product UI, translating autonomous risk-mitigation decisions into clear, actionable user notifications that reduced missed alerts by 60%.

• Designed UI flows for semi-autonomous circuit-breaker features, ensuring edge cases and transparency around automated trade suspension were visible to users within 200ms of trigger events.

• Shipped a React Native with Expo mobile companion app enabling traders to monitor live exposure and approve risk actions from mobile devices, extending platform reach across 2 additional form factors.

• Containerized backend microservices using OpenShift and Kubernetes, cutting environment provisioning time from 3 hours to 22 minutes across 6 deployment pipelines.

• Established cross-functional review standards with quantitative researchers and traders to align AI-driven pricing outputs with frontend display requirements, reducing model-output misrepresentation incidents by 45%.

• Authored a fault-tolerant WebSocket event pipeline in Node.js that processed 8M+ market events per day and maintained frontend state consistency under high-throughput conditions.

• Delivered a beta instrumentation layer using analytics and usage-monitoring hooks across the Electron app, producing adoption insights that directly informed 3 post-launch UX iterations.

• Refactored the order book UI component tree to eliminate redundant re-renders, improving frontend paint performance by 40% across low-memory trading terminal hardware.

• Mentored 2 junior engineers on cross-platform state management patterns and API contract design, cutting onboarding ramp time from 8 weeks to 4 weeks.

• Owned end-to-end reliability for the live trading interface through automated smoke tests and pre-launch stability checks, achieving zero customer-facing downtime across 4 major release cycles. Software Engineer January 2018 – April 2022

Meta Austin, TX

• Constructed a full-scale CRM web application using React and a Node.js API backend, covering contact tracking, pipeline management, and account reporting across the entire customer lifecycle for 12 internal business units.

• Scaled a high-throughput data ingestion pipeline to process and synchronize 5M+ customer interaction records per day across distributed backend services, reducing sync lag by 52%.

• Delivered a multi-tenant backend architecture on Kubernetes that enforced data isolation boundaries for concurrent CRM operations, supporting 500K+ concurrent users without degradation.

• Engineered a customer segmentation engine that consumed behavioral signals via REST APIs and produced targeted audience groups, cutting campaign setup time by 3 hours per analyst.

• Assembled a 360-degree customer activity tracking system across 8 touchpoint categories, consolidating communication history and engagement metrics into a single React dashboard view.

• Rolled out an automated lead scoring algorithm that ranked 200K+ sales opportunities weekly by weighting engagement signals against historical conversion patterns, lifting sales team close rates by 18%.

• Enforced fine-grained role-based access control across all CRM API routes, achieving compliance with 4 organizational security policy requirements across 6 engineering teams.

• Restructured complex relational database queries and indexing strategies to cut CRM dashboard load times by 65% under Meta-scale concurrency demands.

Software Engineer Intern May 2016 – August 2016

Microsoft Bellevue, WA

• Designed and shipped a cloud-based clinical SaaS platform using Node.js and REST APIs, enabling end-to-end drug testing workflows across test ordering, administration, and result tracking for 3 healthcare organizations.

• Secured result submission flows with role-based access control covering 5 permission tiers, ensuring compliance with clinical data privacy standards across 100% of submitted records.

• Built a scalable multi-tenant backend to support concurrent clinical operations, reducing per-tenant onboarding configuration time by 70% compared to the prior single-tenant baseline.

• Constructed data validation and error-handling pipelines for test result ingestion, cutting submission error rates by 80% across 4 data source integrations.

• Collaborated cross-functionally with product managers and clinical stakeholders to translate complex healthcare requirements into reliable, production-grade software features delivered across 2 sprint cycles. Software Engineer Intern May 2015 – July 2015

Applied Predictive Technologies Ballston, VA

• Expanded the Category Management Insights product by introducing a new output module that broadened analytical reporting capabilities across 6 report types.

• Authored a compatibility layer ensuring backward integration between the Test and Learn dashboard and legacy analysis data, preserving access to 3 years of historical records without schema migration.

• Transformed historical analysis retrieval through targeted SQL queries that extracted and restructured data across old and new schemas, cutting report generation time by 55%.

Intern May 2014 – August 2014

NEC Laboratories America, Inc Princeton, NJ

• Programmed laser-based spectrometry hardware through purpose-built embedded DSP software, yielding accurate gas concentration measurements across 4 targeted wavelength spectra.

• Translated Beer-Lambert Law absorption principles into a deployable concentration-derivation algorithm, achieving measurement accuracy within 2% deviation across 500+ field test samples.

• Captured high-frequency DSP outputs through a resilient data acquisition pipeline that preserved readings with less than 0.5% data loss across 72-hour continuous measurement sessions.

• Rendered live gas concentration data through a pseudo-real-time visualization system, giving researchers observability into environmental trends across 8 monitored sensor channels. EDUCATION

• Carnegie Mellon University April 2013 – February 2017 Bachelor's Degree, Electrical and Computer Engineering Pittsburgh, PA

• Carnegie Mellon University March 2017 – December 2017 Master of Science, Electrical and Computer Engineering Pittsburgh, PA

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