Frontend vs. Backend in AI Development

William Imoh · Improve this Guide

Many software developers begin their careers by choosing an area of focus: backend or front end development. If you’re an aspiring software developer, understanding the differences between frontend and backend can help you choose a focus for your career path. This guide focuses on the front-end and back-end development for AI.

Frontend vs Backend is a common topic in software engineering and understanding both frontend and backend development is crucial for creating effective and efficient websites. Both are essential for a well-rounded web development process. Both career paths are in high demand.

Front-end development refers to the visual elements that users can directly interact with. It is the user facing side of an application also known as the client side of an application. Back-end development includes everything the user cannot see. It focuses on the application’s overall functionality and business logic.

Despite frontend and backend developers in AI having specific roles in the overall software development life cycle, they work together to design, program, test, and deploy AI applications. They collaborate to ensure AI applications meet quality and security standards. In addition to front-end and back-end developers, there are also full stack developers. Full stack developers work and specialize in both frontend and backend of web development.

The table below presents a comparison of frontend vs backend development AI specializations.

Frontend AI development	Backend AI development
Focuses on the visual aspects of an AI application which is the UI and users directly interact with.	Focuses on the server-side development of an application which has data storage and the user does not directly interact with.
Specializes in the client side of the application.	Not concerned with the client side of web applications.
The front end is about user interface (UI) and user experience (UX).	Focuses on the application’s functionality and business logic.
Uses HTML, CSS and JavaScript as part of the toolbox.	Uses back-end programming languages like Java, C#, Python and so on.

Let’s look at frontend vs backend in detail.

What is frontend development for AI?

Frontend development for AI involves the design and implementation of the visual elements of an AI application. Several AI applications are being used on a daily basis, such as Chatbots, Virtual assistants, face recognition systems, etc. A user interface (UI) enables you to interact with these applications.

An AI frontend developer designs and builds the parts of an AI application that users can directly interact with. For larger projects, front-end developers will work with a digital and web designer who is responsible for creating a graphic design for the web page of the application. Frontend developers are also referred to as web developers.

Frontends are also built on other platforms asides the web, such as mobile apps for Android and iOS, or desktop apps.

The next section presents who a front-end developer is and the tools they use for building applications for the web.

Who is a frontend developer?

A frontend developer builds the visual part of an application, which includes the parts users see and directly interact with, such as the graphical user interface (GUI) and the command line, including the design, navigation menus, texts, images, videos, etc. A page or screen a user sees with several UI components is called a document object model (DOM).

Frontend developers build these visual parts using front end programming languages such as:

• HTML (Hypertext Markup Language)
• CSS
• JavaScript

HTML (Hypertext Markup Language):

The basic building block of an application. It defines the markup of the language.

CSS (Cascading Style Sheets)

Builds upon HTML and defines the layout and style of an application.

JavaScript

The front-end programming language that adds logic to an application. It can be used for both the frontend and backend (NodeJs, ExpressJs, NestJS).

HTML, CSS, and JavaScript are fundamental tools in a frontend developer’s toolkit and are used to determine the look and functionality of the client side of an application.

In addition to these languages, there are frontend frameworks, libraries, and CSS preprocessors that help to create websites and applications efficiently. Some of the popular ones are React, Vue, Angular, and SASS.

Front end developers responsibilities for AI

The core responsibilities of AI front end developers include:

• Designing and developing dashboards
• Developing graphs and charts for data visualization
• Integrating with AI services
• Testing and validating the integrated AI services
• Optimizing the user experience of AI applications

Designing and developing dashboards

A dashboard conveys different but related information in an understandable format. Frontend developers are responsible for designing and developing dashboards that convey different AI data and metrics. They use design programs to lay out a dashboard prototype and ensure that the dashboards are implemented according to specifications.

Developing graphs and charts for data visualization

Data visualization is an important process in AI that presents data in visual formats such as graphs and charts. Frontend AI developers use libraries such as Chart.js, Plotly, and D3.js to create graphs and charts to visualize and interpret data.

Integrating with AI services

AI front end developers connect frontend applications to AI services via Application Programming Interfaces (APIs) to fetch data and predict or perform certain actions. For example, a weather application’s frontend connects to weather prediction services through API endpoints or other means of communication and displays the information users interact with.

Testing and validating integrated AI services

After integrating AI services into an application, frontend AI developers also test and validate that these services function properly and provide accurate and efficient data. Testing and validation are important for identifying and resolving technical issues that might come up and for addressing optimization requirements.

Optimizing the user experience of AI applications

Frontend AI developers focus on improving the user experience of software and other mobile applications by optimizing UI elements and adding features like hovering effects or tooltips, navigation flows, and application interactions. They also iterate on designs and features with UI/UX experts based on user feedback to enhance user satisfaction and produce a responsive web design.

Frontend developer skills for AI

To be a frontend AI developer, you need a combination of soft and technical skills. Some of the skills you require to be a frontend AI developer include:

• Deep understanding of HTML, CSS, and JavaScript/TypeScript.
• Knowledge of at least one web application framework or library, e.g., React, Vue, and Angular.
• Knowledge of data visualization libraries. e.g., Chart.js, Plotly.
• Basic understanding of machine learning and machine learning models. e.g., linear regression, random forest, etc.
• Collaboration and communication skills.
• Problem-solving skills.

What is back end development for AI?

Back end development for AI is the design and implementation of the server side of an AI application. As opposed to frontend development, which involves the visual and interactive elements of an application, backend development involves the part of an application a user cannot directly interact with. The next section goes into detail about who a back-end developer is and their role in the software development process and lifecycle.

Who is a back-end developer?

A back-end developer specializes in the server-side development of an AI application that users cannot see and directly interact with. A back-end developer manages the behind-the-scenes part of an application, such as the servers, databases, and machine learning models that power AI applications.

AI back end developers use server-side programming languages such as C#, Java, Python, and Rust and frameworks such as Spring Boot, ASP.NET core, Django, and Ruby on Rails to develop the backend of AI applications.

Back end developers responsibilities for AI

The responsibilities of AI back end developers include:

• Database design and management
• AI model development
• Application Programming Interface design and development
• Performance optimization

Database design and management

Data is stored and retrieved from databases. AI deals with a large amount of data, which can be structured or unstructured. Back end developers are responsible for setting up these databases to save AI data. Two common types of databases are:

• Relational databases /Structured Query Language (SQL) e.g., PostgreSQL, Microsoft SQL Server
• NoSQL databases, e.g., MongoDB.

AI model development

AI models are computer programs that recognize patterns in data and make predictions. They rely heavily on trained and untrained data, and each model is suitable for different cases. Examples of AI models include:

• Classification models, e.g., random forest, K-nearest neighbor, naive bayes
• Regression models, e.g., linear regression, decision trees

Backend AI developers use tools and frameworks such as Pandas, Numpy, Scikit-Learn, PyTorch, and so on to develop AI these AI models.

API design and development

A backend AI developer designs and develops APIs that are consumed by the frontend of an AI application or other services. API development involves creating endpoints that provide data that users can visualize and interact with. Backend AI developers use different tools to design and document APIs; a common one is Swagger.

Performance optimization

Backend AI developers are constantly optimizing the performance of AI applications. They do this by scaling applications to ensure the backend can handle large volumes of requests. The performance optimization involves code refactoring, optimizing database queries, adding caching, and load balancing.

Backend developer skills for AI

Some of the job-ready skills needed to excel as a backend AI developer include:

• In-depth knowledge of at least one back-end programming language.
• Knowledge of database systems.
• Basic knowledge of web servers.
• Basic knowledge of how to deploy applications on cloud services or on-premise.
• Knowledge of machine learning models.
• Knowledge of data structures and algorithm
• Knowledge of web application frameworks
• Problem-solving and logical reasoning skills.
• Collaboration and communication skills.

Which should I go for - frontend vs backend?

As you’ve seen in the frontend vs backend comparison, frontend and backend developers who specialize in AI perform different responsibilities and require various skill sets.

If you like user interfaces, keen on sound design, and like the visual aspects of creating apps, then perhaps you would be most interested in becoming a front end software developer. If you are more interested in servers, databases, and how systems work behind the scenes, then you should consider backend development.

You can begin your frontend or backend engineering career by obtaining a bachelor’s degree in computer science degree from a college.

roadmap.sh provides you with step-by-step guidance on how to become a frontend developer and backend developer. You can also explore the full stack developer roadmap if you are interested in learning full stack development, which is a combination of frontend and backend development. Signing up on roadmap.sh makes it easy to track your progress and also share it on your profile. You can also draw up your personalized roadmap or work with AI to generate new roadmaps.