Versatile JavaScript Engineers for Front-end & Back-end Development
React, Vue, Angular and Node.js engineers from our own network who add AI features to products your customers already use.
We found 113 available JavaScript Developers
Adding AI to a JavaScript product people already use
A growing share of the JavaScript work clients bring to Cortance is not a new app. The product already runs on React, Vue, Angular or Node.js, and the client wants AI inside it: an assistant in the admin panel, replies drafted from CRM data, or a store that answers product questions on its own.
Why AI features break at the seam between front end and Node.js
An AI feature in a JavaScript product lives on both sides of the stack at once. On the front end, it has to stream an answer as it is generated, keep the conversation state when the user switches screens, and show clearly when the model is unsure. On the Node.js side, it has to call the model, connect it to the CRM, the database or the store catalogue, and keep the API key and the cost under control. Most failures happen where the two meet: a key shipped inside the browser bundle, a screen frozen for twenty seconds while the model thinks, or an answer built from yesterday's data. That is why the hire for this work is an engineer who has already built both halves in a live product, not a front-end specialist who has only called an API from a demo.
JavaScript engineers in our network who have shipped AI features
That experience is still rare. Of the 169 JavaScript engineers in our network, 16 list OpenAI, LangChain or LLM work on their profiles, which is why we prefer engineers who are actively developing in GenAI. Stanly M. is one of them. On Kawlo, an exam-preparation app for students in Cameroon, Zambia, Uganda and Tanzania, he built the React Native client and the Express services behind it, then added a retrieval-based bot on LangChain and OpenAI that answers students' questions from the app's own study material. The app has passed 300,000 downloads and 70,000 active users. What made the difference was not the framework list but that one engineer owned the whole path, from the question typed in the app to the answer the model returned.
From a chat box to an assistant that takes actions
The request after a working chat is usually an assistant that does things: sends the email, books the meeting, updates the record. That moves the hard part from the prompt to state management, because every action is an asynchronous call that can fail halfway while the user keeps typing. Danylo P. worked on this kind of product: a generative AI assistant in a Google Workspace sidebar that acts on email, calendar and connected plugins, with its action flows handled in Redux-Saga. Voice adds another layer. Roman N. integrated a live voice AI agent into a site's front end over WebSockets, where the interface has to track which state the agent is in at every moment.
Every engineer we present is part of our own network, not resold from another firm. The same work fits around a legacy product. If your front end runs on AngularJS or jQuery, an engineer who has worked in those codebases can add the assistant without a rewrite.
Send us your current stack and the first AI feature you want in the product. You get matched profiles within 30 minutes, the engineer you choose can start within 2 days, and our vetting process shows what stands behind each one.
Front end, Node.js or full stack: which JavaScript developer do you need?
The right JavaScript hire depends on where the hard part of your product sits. Our network reflects that choice: of 169 JavaScript engineers, 72 work full stack, 39 on the front end and 33 on the back end, so a full-stack or front-end brief fills faster than a server-only one. Below is how we tell the three apart for a client.
Front end, when the interface is the product
Dashboards, booking flows and permission-heavy admin panels fail in specific ways: a table that stalls at ten thousand rows, form validation that disagrees with the API, or a role check that exists on the screen but not on the server. Each of these passes a demo and fails with the first customer account with production data, which is why screenshots of a finished UI tell you little. For this brief we match on engineers whose projects show a slow screen made fast and covered by tests, and in the interview you can ask them to walk you through that screen instead of a framework quiz.
Node.js, when the server is the hard part
Choose a Node.js specialist when the risk is in live data, queues or an API many clients depend on. The typical failures are a rejected promise nobody handles until the process restarts, a heavy calculation that blocks every other request, and a webhook retried twice that charges a customer twice. None of them shows up in a code sample, so we match on engineers whose projects describe running a service under load, not only building one. With 33 back-end profiles in our JavaScript network, a server-only brief is often better started from our Node.js developers page.
Full stack, when one person can hold the whole product
Full stack fits an MVP, an internal tool or a first AI feature that has to reach users quickly. The risk is depth: an engineer comfortable in Next.js and Express can still be thin on database design, and it shows with the first slow query or the first schema change under production data. Ask for a schema the engineer designed and later had to change, because that story shows whether they own the data layer or only use it. Our full-stack developers page goes deeper on that role.
When one engineer is not enough
If both sides need depth, for example, a real-time dashboard on top of an API with heavy integrations, we would rather propose two engineers than stretch one across both. Because you can hire flexibly, the second person doesn't have to start on day one: you can begin with one engineer on the riskier side and add the other once the first release shows where the load is.
Six JavaScript codebases, six different jobs
Each card is an engineer from our network, with a link to the profile behind the work.
A staged AngularJS to Angular migration
Oleksandra K. moved a live ad-management platform from AngularJS to modern Angular in stages, keeping legacy modules working, and tuned data grids for 10,000+ rows.
Full-stack JavaScript from prototype to deploy
Tural M. led full-stack work on a recruiting SaaS in Node.js, Express and Angular, from prototype to deployment, and refactored legacy code on a cloud contact-center product.
Node.js on a trading platform
Samuel O. led a team building web and mobile apps for a fintech startup, working as lead and back-end developer in JavaScript and Node.js on a crypto and gift-card trading platform.
React and Next.js tested to near-total coverage
Nataliia N. built campaign management and statistics screens with role-based access and real-time updates in React and Next.js, testing to close to 100% coverage.
Angular to React 18 without a release freeze
Nazarii B. led the move of a video marketing SaaS from legacy Angular to React 18 and TypeScript in shippable increments, then switched its build to rsbuild for 5 to 10 times faster builds, as lead of a 12-person core team.
OpenAI inside an Angular and NestJS product
Mikayel G. worked full stack in Angular and NestJS on 42smm.ai, an AI social media tool that generates, schedules and publishes posts automatically in more than 80 languages.
One front-end architecture for 25 white-label brands
The largest front-end job in our JavaScript network so far is a marketplace platform that had to serve one product and more than 25 white-label brands, with over 1.5 million users. Mykhailo Y. led the front-end architecture: Angular portals and admin CRMs on one side, React and Next.js server-rendered apps on a shared design system on the other.
Two decisions carried most of the result. He moved legacy Angular and Ionic apps into an Nx monorepo, which cut pull-request volume by up to half and shortened deployment builds from about 20 minutes to between 10 and 14. On the Next.js side, server-side rendering on Vercel brought PageSpeed scores to between 95 and 100.
In a codebase that serves many apps, most of the cost sits in the fiftieth pull request and the twentieth build, not in the first feature. Briefs where several products share one front end are the ones where we match on this kind of experience first.
JavaScript in our network, as of September 2026
- 215
- delivered projects with JavaScript in our network
- 78%
- engineers covers US CET time overlap
- 38%
- of those projects also use TypeScript
Does TypeScript or AI tooling change who you should hire?
TypeScript changes less than the headlines suggest. In Stack Overflow's 2025 survey, 43.6% of respondents used TypeScript, so plain JavaScript still runs a large share of the code we are asked to maintain. For a new build, we usually recommend TypeScript. The failure to watch for is a typed codebase full of loose any declarations, where the compiler signs off on bugs it cannot see. If TypeScript is the core of your brief, our TypeScript developers page is the better starting point.
AI coding assistants shorten the repetitive parts of JavaScript work: component boilerplate, test scaffolds, converting a callback API to promises. They do not decide whether state belongs in a store or in the URL, and they do not notice that a generated data-fetching hook runs twice. 13 engineers in our network list Claude Code on their JavaScript projects. Our position is that generated code gets the same senior review as any other pull request.
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