Find Back-End Developer Jobs

Web - Node, React, Python, PostgreSQL.

Mobile - React Native, Swift (iOS) / Java (Android).

d3.js/React/Redux single page webapp, Go backend, multi-language support for client libraries

Frontend: React, Relay, Flow, Jest, Enzyme.

Mobile: React Native, Apollo.

Backend: Ruby on Rails, Postgres, GraphQL, Python, RSpec.

CI: GitHub, Buildkite.

Infrastructure: AWS, Python.

On the frontend, we use TypeScript, React, Redux, GraphQL, Apollo. On the backend, we use Node.js, Go, TypeScript, MySQL, Elasticsearch, Redis. Everything is containerized in Docker and running on Kubernetes.

On the web, we’re a Ruby on Rails shop with a React.js front-end. Other items in our stack are Sass, Webpacker, Postgres, Mongo, Kafka, S3, AWS Lambda, Terraform, and Docker.

On Mobile, our apps are primarily built with React Native alongside some custom native libraries in Java, Objective-C, Swift, and C++ for core functionalities. We use Apollo and GraphQL, alongside Redux for local state management.

Go 1.3, Rails 5.1, Ruby 2.6, Java 8, PostgreSQL 9.4, TypeScript 3.5, Angular 8, AWS

Python / Django, Scala, Golang, Postgres, Cassandra, ElasticSearch, Redis, AWS (EC2, S3, ALB, EBS, Kinesis, SQS), Linux (Ubuntu)

We use whatever tools are appropriate to accomplish the task at hand. The backend stack currently consists of Node.js, Express, GraphQL, PostgreSQL, Docker and Lambda in AWS. We also have a strong bias towards a micro-service architecture. The frontend stack currently consists of React Native, TypeScript, Expo, Apollo client (GraphQL), and Jest testing framework. We have a mobile app with cross platform support.

We use Golang for our backend, Typescript and React for our web client, GraphQL to fetch data from our backend, and React Native for our mobile app. Direct experience with these technologies is not required.

Backend: Node + Express, Typescript, Go Microservices. Frontend: Next.js, React + Hooks, Storybook. Infrastructure: Heroku + AWS, CircleCI, DataDog.

AWS rds + mysql for data storage API is in python + flask apache thrift for interface definition android app is in java ios apps in swift 3 front-end web is in python, flask, node, and react

Dark’s backend is written in a combination of OCaml, Rust, and Dark (that’s right, Dark is partially built in Dark!). We use Kubernetes and Postgres, running on top of Google Cloud.

Our frontend is also in OCaml – we don’t expect you to know OCaml before you join, and you typically learn it in the first few weeks. We compile the OCaml to JS using Bucklescript/ReasonML, and use a framework similar to Redux or Elm for managing state.

We use React and React Native for our frontends and Node.js for our backend, which is built around the microservices paradigm. Some services have been migrated to serverless logic, in order to have more concurrent users on Aula simultaneously.

In order to support this architecture, we use Docker and everything is deployed and managed on our AWS infrastructure which is defined by Terraform code. More details here!

Backend: Ruby on Rails, Postgres, Elasticsearch, Google Cloud Platform, Kubernetes.

Frontend: Typescript, React, Redux.

Data: BigQuery, BigTable, DataFlow, DataProc.

For Comply: JS, React, Ruby, Flow, Postgres. For Deploy: Cloud IaaS (AWS), Docker, PostgreSQL, Redis, sqlite.

AWS (ECS, ECR, EC2, S3, Cloudwatch…), Docker, Ruby (Sinatra), Python, Postgresql, Mysql, Swift, Kotlin, Sentry, Jenkins, React.js

Python, Flask, PostgreSQL, Redis, Heroku, AWS, GraphQL, React Native

Outside of our data teams, our engineering teams use Java, JBoss, CDI/Spring, Freemarker, Jquery, Knockout, SpringBoot, Redis Kinesis, Docker.

Our Data Engineering team uses Groovy, Redshift, AWS Data Pipeline, AWS Lambda, Cassandra, AWS Elastic Bean Stalk, Python, Docker.

Our Data Science team uses Python, Jupyter Notebook, SciKitLearn, Redshift, and Docker.

Airtable’s core stack is written using JavaScript, augmented with static type checking and other tools. We use Node.js on the backend, and mostly-React on the frontend, but our application requirements drive a substantial amount of custom software architecture; that is, Airtable is pretty far from a boilerplate “React + Express” application. We also periodically evaluate adding other languages into our codebase for ecosystem or performance reasons. Mobile apps are currently written in the standard platform language, mixed with JavaScript in webviews where appropriate. Our production infrastructure runs on a variety of AWS services, principally using Terraform for deployment; for data collection, aggregation, monitoring, and alerting, we use a mixture of ELK and some carefully selected third-party services.

Our clients (Android, iOS, and web) and backend are all built in JavaScript using technologies like React, React Native, Nodejs, and GraphQL.

Frontend: express, react, redux, bootstrap

Middleware: express

Backend: everything but dominantly GoLang running on AWS

Backend: Node.js, Express, MongoDB/Mongoose, Testing (Mocha, Jest, Supertest, Nock), and Nginx (Caching server, SSL certificate generation service).

Frontend: Angular 1, React.

Hosting/Infrastructure: Heroku, AWS, MongoDB Atlas, GitHub, Codeclimate, CircleCI.

Our engineering team builds software using JavaScript/ES6, React, Redux, Swift, and Objective-C on the frontend and Python, bash, and Bitcoin Core on the backend.

Backend: Ruby on Rails, Frontend: ReactJS

Web: Typescript, React Native Web

Backend: Typescript, Express, TypeORM, PostgreSQL hosted on Heroku

Agent: Typescript, React, Material UI

JavaScript/CoffeeScript, Python, Node.js, React + React Native, AWS Lambda, Spark, Kinesis, MongoDB, Redshift

Golang, React, Redux, MongoDB, ElasticSearch, Redis, Kinesis, NATS, TimescaleDB, Lambda, Node.js, Postgres, Typescript

Node.js, React.js, Redis / Mongo, AWS, Kubernetes / Terraform / Docker

Blog Post on our Tech Stack

Lever uses our own open source MVC framework called Derby that syncs all data via Operational Transformation (the algorithm behind Google Docs). OT is the way we handle concurrency conflicts for any piece of data that is edited at the same time. In addition to real-time sync, OT allows us to provide a smoother UI since we can render updates on the client instantly without waiting for our backend to respond, while still guaranteeing consistency.

Lever makes extensive use of AWS, Docker, Node, Mongo, ElasticSearch, and Redis within our infrastructure. We use tools like Hubot to streamline deployments and Grafana to see what’s going on under the hood. In addition to automating all the things, we love to version them too! Our systems are all created using Terraform and Chef, working together to ensure consistency at all costs.

We have a service oriented stack deployed on AWS using containers. Most of our backend services are written in Go, with the exception of an NLP/ML service written in Python. Services talk to each other using gRPC.

Our web application is served statically from Cloudfront/S3 and is written using React. Is is a Progressive Web App, with a service worker to speed up delivery.

We integrate with third party software such as Google Drive, Calendar, Jira, GitHub, Asana, Slack. These areas are some of the most complex parts of our systems. They’re also some of the most important: integrations enable the “magic” of a user coming to Range in the morning and seeing all of their work from the previous day already gathered in one place.

Back: Node, Golang

SRE: Terraform, Kubernetes, Rancher, AWS, MongoDB, Postgres, RabbitMq, ElasticSearch, Docker

Front: React-like frameworks, Webpack, Javascript, AngularJS (only until we kill the old product)

Frontend is React Native for mobile, and we’re experimenting with React Native Web on the web side.

Backend is currently Java deployed using Kubernetes, but we have a polyglot approach to problem solving, and we will likely end up with a backend that reflects that.

React

Ruby on Rails

Java

AWS

Frontend: Javascript, React, Typescript, Flow, Mobx, Stylus, Redux, Reactive JS, Styled Components, Focal (our own in-house, open-sourced state management framework)

Mobile (iOS and Android): Java, OkHttp, Butterknife, Retrofit, XCode, Swift, ReactiveCocoa, ReactiveSwift, Kickstarter-Prelude, Argo, Runes, Curry

Desktop app: CoffeeScript, Electron.js, C#, F#, ReactiveUI

Internal tools: Angular, Elm, ClojureScript

Backend: Java, Scala, Python, Haskell, Lisp, Clojure, Go, C++

NLP/Research teams: sklearn, TensorFlow, PyTorch, CNN, RNN, Keras, Seq2Seq, xgboost, CRFs, nltk/spacy/OpenNLP, OpenNMT, Jupyter notebooks

TypeScript, JavaScript, and React

Scala (high performance backend)

Python (infrastructure management and data analysis)

Android and iOS

Luna1 (legacy in-house functional reactive framework, similar to Meteor)

Frontend: React/Redux. Legacy JSP (although increasingly less!)

Monolith backend: Java on Tomcat.

Microservices backend: Java on Spring.

API: Java w/ Swagger.

TechOps: Hashicorp stack + Docker on EC2/AWS. Cloudflare, EBS, Redis. Git/GitHub for Source Control. Jenkins for CI. Ruby/Cucumber for testing.

Databases: MySQL

Search: SOLR

Data: Python (pandas, AirFlow, etc.). Redshift/Postgres.

OnForce Platform (subsidiary): PHP on baremetal LAMP (deprecating, moving to AWS).

React Native, React, Ruby on Rails, Go

Tech stack varies from team to team: PHP, React, Java, Node, Scala, Objective-C, Go, etc.