Build and scale full-stack customer and agent support experiences using React/TypeScript frontends and Go backends. Partner with Product and Design to deliver measurable CX improvements.
Salary not listed
Remote5+ YOEFullstack Engineering
About the role
Responsibilities
Build end-to-end full-stack features across React/TypeScript frontends and Go backend services for Help Center, chat, and agent-facing workflows.
Partner with Product, Design, CX Ops, and peer engineering teams to turn high-volume customer problems into intuitive self-serve and assisted-support experiences.
Own APIs, service integrations, and UI flows that connect Surfaces with CEE Foundations and Intelligence capabilities, including routing, procedures, data-plane integrations, and evaluation systems.
Drive CX outcomes through experimentation, instrumentation, and iterative delivery, using metrics such as containment, AtR, CSAT, and escalation rates.
Lead integration of AI/ML and vendor capabilities into customer and agent experiences with appropriate guardrails, observability, and rollout discipline.
Strengthen production reliability through on-call participation, incident response, debugging, and mentoring engineers on full-stack design, testing, and deployment practices.
Requirements
5+ years of software engineering experience building and operating production full-stack web applications.
Hands-on proficiency in React (or similar modern frontend frameworks) with TypeScript.
Backend API development in Go.
Demonstrated experience designing and shipping customer-facing experiences in close partnership with Product and Design.
Proven track record with distributed systems and production fundamentals including API design, caching, observability, debugging, incident response, and operational reliability.
Experience integrating AI/ML or third-party platform capabilities into production applications with engineering rigor around guardrails, testing, and rollout.
Track record of delivering measurable product outcomes across cross-functional teams, including translating ambiguous problem spaces into shipped solutions.
Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
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