AI Developer Career Guide and Roadmap

Artificial intelligence (AI) is an expansive field in information technology encompassing various technologies, including natural language processing and machine learning, which allow machines to "learn" and act in human-like ways. Although the definitions vary as AI technology continues growing, experts often define it in two ways:

• Narrow, sometimes referred to as "weak," AI tends to offer efficiency-focused capabilities. Examples include digital assistants like Amazon Alexa or Google Home.

• General AI, sometimes called "strong," refers to technologies that transform computers and digital devices into machines that can think using creative and abstract processes — technology that doesn’t exist just yet. 

Market growth for AI is strong and continues to rise. According to data from Statista, the sector will grow exponentially by up to $2 trillion between 2020 and 2030 [1]. This growth suggests a promising job outlook in the field, which is good news for anyone considering a career as an AI developer. Read on to learn about the role, including everyday tasks, how it differs from similar positions, and the average salary you can anticipate with this AI developer roadmap. 

Read more: What Is Artificial Intelligence? Definition, Uses, and Types

What is an AI developer?

AI developers use programming languages like Python and R to integrate AI algorithms into software applications. In this role, you'll write code, test it, and deploy it, in addition to converting machine learning (ML) application programming interfaces and making them accessible to existing software. Often, you'll also work with AI models, neural networking, and machine learning algorithms.

Read more: What Is Machine Learning? Definition, Types, and Examples

What does an AI developer do? 

Before deciding if this is a suitable career path, it helps to have a general idea of this job's day-to-day tasks and responsibilities. Although what you’ll do as an AI developer will depend on your employer, you can anticipate general duties such as:

• Work as part of the IT team: Collaboration with other parts of the team is a significant part of the job. You'll likely participate in strategy and design meetings, collaborate on planning, and post-project reviews.

• Code: You'll spend time coding AI programs and working with AI models and algorithms. As an AI developer, you may build algorithms, test and deploy them, and develop AI-based systems. Ultimately, you aim to create AI solutions to solve specific business or consumer needs.

• Help others understand and use AI: You'll likely lead others to use the solutions you create. You will explain AI software, applications, and programs to other team members, application users, and company leaders. You may also train other employees on AI system implementation.

Continue to learn how this job differs from similar positions. Below, we explore the differences between AI developers and AI engineers, software developers, and data scientists. 

Read more: 6 Artificial Intelligence (AI) Jobs to Consider

AI developer vs. AI engineer

AI developers need strong programming skills to create algorithms and AI applications. They frequently collaborate with others, including data scientists, to build solutions to specific business concerns. AI engineers, on the other hand, focus on engineering and deployment, which requires a robust foundation in system infrastructure and architecture. AI engineers also should be familiar with scaling models to support their endeavors in deploying and optimizing models, ensuring they provide optimal performance.

Read more: What Is an AI Engineer? (And How to Become One)

AI developer vs. software developer

Although there is some overlap, the differences between AI and software developers can be summed up in one word: focus. Software developers may work with AI technologies, but they work on a broader range of applications and systems. AI developers work specifically on AI solutions, including models, algorithms, and applications. 

Read more: What Does a Software Developer Do? Career Overview + Outlook

AI developer vs. data scientist or analyst

Data scientists and architects play roles both within AI and outside the field. While data scientists can help develop algorithms, their larger task is collecting data, identifying patterns, and gaining insight from it. Data analysts focus primarily on gaining insights from data and presenting them to those who need them to understand issues or make decisions. 

What are essential skills for an AI developer?

You’ll need to develop a robust skill set to become an AI developer. Although requirements vary by employers, the primary skills to focus on include the following mix of technical and workplace skills.

Technical skills

One critical skill you’ll need is familiarity and proficiency with various scripting languages. Python offers an excellent starting point because of its powerful data analysis capabilities, ease of learning, and substantial community support. Familiarity with other AI languages like Julia, Java, R, and Javascript can help you advance your career. 

Additional technical skills include: 

• Proficiency in working with deep learning, neural networks, and machine learning

• Knowledge of data structures and algorithms

• Ability to collect, organize, and interpret data to guide decisions

• Knowledge of cloud platforms like Google Cloud and Amazon Web Services (AWS)

• Robust understanding of mathematics and working knowledge of data cleaning

Workplace skills

Workplace skills like leadership and critical thinking complement technical skills and help you succeed. These skills are called transferable skills, which can go with you across various jobs, employers, and sectors. Examples of workplace skills helpful for a career in AI development include:

• Problem-solving

• Creativity

• Critical thinking

• Verbal and written communication

• Effective collaboration

AI developer salary and job outlook

Although the US Bureau of Labor Statistics (BLS) doesn’t offer data specifically for AI developers, it projects job growth in all computer and information technology careers to grow at an above-average pace in the decade leading up to 2032. BLS projects a 25 percent growth between 2022 and 2032 for similar jobs, like software developers [2].

In addition to solid job growth, AI developers enjoy higher earning potential. According to Glassdoor, an AI developer in the US earns an annual base salary of $113,282 [3]. Factors like your experience level and the industry you work in may impact your specific salary. 

Typical AI developer career path

Becoming an AI developer can offer an exciting entry into the technology sector. Although you’ll find more than one path available, the typical roadmap includes earning a bachelor’s degree, getting some experience, and considering relevant certifications. 

Let’s look closer at the three major steps along this career path.

1. Consider getting a degree. 

Although it’s possible to become an AI developer without a degree, employers often look for candidates with a bachelor’s at a minimum. Data from online recruitment company Zippia shows that more than 63 percent of people have a bachelor's degree, and another 17 percent have a master's [4]. Popular majors include computer science, statistics, AI, or another related field. 

2. Gain experience in AI and related fields.

Working with AI to build your skills is crucial to learning more about this field. Professional experience is invaluable for broadening your skill set. It can also help develop your professional network, which will help you along your career path and add details to your resume and portfolio.  

If you want to move up from entry-level AI jobs, it's essential to continue building your coding skills and stay updated on industry trends and news.

Read more: 5 Benefits of AI to Know (+ 3 Risks to Watch Out For)

3. Consider certifications.

Becoming certified shows employers tangible evidence of your skills and position as an AI subject matter expert. A few to consider include the following:

• Certified Artificial Intelligence Scientist (CAIS): This credential from the United States Artificial Intelligence Institute is a self-paced program that can help you learn more about strategy, workflow, and implementation of AI.

• Artificial Intelligence Engineer (AiE): This qualification from the Artificial Intelligence Board of America requires comprehensive knowledge of AI applications and systems.

• Microsoft Certified Azure AI Engineer Associate: This technology-specific certification demonstrates your proficiency in working with Azure AI, developing AI solutions, and building AI applications.

Read more: 5 Popular Machine Learning Certifications: Your Guide

Taking the next steps with Coursera

In addition to getting a degree, experience, and certifications, you can also take courses and complete Professional Certificates to add to your resume and sharpen your AI development skills. For example, the beginner-friendly IBM AI Foundations for Business Specialization can help you explore AI and begin building your knowledge base, or you can develop your data analysis abilities with the Google Data Analytics Professional Certificate. You’ll find these programs and so much more on Coursera.