Front-End Engineer

Remote, San Francisco, CA, United States, Silicon Valley, CA, United States • $130k - $175k

VoiceOps


Role Locations

  • Remote
  • San Francisco, CA, United States
  • Silicon Valley, CA, United States

Compensation

$130k - $175k

Employees

11 - 25 people

Address

680 8 Th St Unit 202
San Francisco, CA, 94103-4902, US

Tech Stack

  • Ruby on Rails
  • PostgreSQL
  • AWS
  • Python
  • React
  • Go
  • Rust

Role Description

About the Role

VoiceOps is looking for an enthusiastic, driven, and capable Front-End Engineer with a desire to push the state of the art.  In this role you will contribute to applications and systems that transform the way call centers do business. This position will work closely with Full-Stack, Back-End, and Machine Learning engineers to deliver personalized and actionable suggestions to our users.

Responsibilities

  • Develop robust and interactive web applications that allow users to understand voice and text data at a glance, surface effective options, and choose relevant, impactful advice for their teams
  • Work together with Full-Stack and Back-End engineers to define flexible, performant APIs and data models
  • Optimize front-end build / development toolchain
  • Create re-usable application platform assets such as component and style libraries, permission abstraction layers, and logging strategies
  • Collaborate with Product Management to capture customer feedback, estimate effort, prototype MVPs, and prioritize features

Qualifications

  • 3+ years of professional engineering experience
  • Expertise with modern front-end / JavaScript technologies and frameworks such as: ES 2015+, React, Redux, TypeScript, Sass, Babel, and Webpack
  • Understanding of HTTP request lifecycles
  • Strong command of HTML, CSS3, and SVG
  • A BS/MS in computer science or related field of study, or equivalent experience
  • Proven ability to communicate ideas to technical and non-technical colleagues

Beneficial Experience

  • Experience building interfaces for data labeling/annotation for training Machine Learning models
  • Recent experience with common server-side languages: Ruby, Python, JS/Node, Elixir, Go, or similar
  • Previous work in a Scrum/Agile -based team
  • Prior experience in a SaaS startup
  • Familiarity with functional/declarative programming

About you

  • You have strong opinions about technology and the facts to back it up
  • You welcome healthy but respectful debate
  • You keep up-to-date with the rapidly evolving front-end landscape
  • The thought of code sitting undeployed for more than a week sends shivers up your spine
  • You want to be go-to subject matter expert for front-end questions

About VoiceOps

VoiceOps uses AI to improve call center rep performance with world-class coaching.

Our average customer makes tens of thousands of calls per week. In a world without VoiceOps, they have literally no idea what their sales reps are doing on the phone. It's a total (and scary) black box.

By applying ML and a great UI to this problem, call center leadership has all the data they need about customer conversations at their fingertips, and can coach their reps more effectively and efficiently.

The technical problem is interesting, and gets more interesting as we grow. Our core challenge is how to take billions of audio recordings (and messy, unstructured human conversations) and make sense out of that data in a way that is: a) accurate b) cost efficient, and c) highly scalable. The corresponding product problem is how to take well-structured data and make it actionable for the end-user.

Call center recordings are one of the richest/largest untapped datasets in the world (literally, billions of calls stored in AWS buckets that no one is touching right now). We're going to be the best in the world at structuring that data and putting it to use to make businesses work better.

Company Culture

Every problem is our problem

We do not look to external sources for why we didn't hit a deadline, meet an objective, etc. We hold ourselves responsible.

Intellectually honest and curious

We challenge each other's ideas daily - on product strategy and beyond. At lunch we are more likely to talk philosophy than TV (though we do some of that too)

Emotionally open and vulnerable

We talk about the ups and the downs of our lives outside of work and strive to have high authenticity interactions with each other.

Ambitious

We work hard to be an enduring company that paves the way for all sorts of applications which require structuring verbal conversational data at scale.

High quality bar, and always rising

We redo our work again and again until it's great. (can be frustrating in the moment but is ultimately extremely rewarding when we build things that are greater than we imagined they would be)

Interested in this role?
Skip straight to final-round interviews by applying through Triplebyte.