Artificial intelligence (AI) and software engineering are two of the most in-demand fields in technology today. As AI continues to evolve, companies across industries are looking for experts who can develop and implement machine learning models. At the same time, software engineers remain essential for designing and maintaining applications that power businesses and everyday life.
As the demand for AI-driven solutions and software development continues to grow, many professionals are weighing the differences between AI engineering and software engineering when considering engineering jobs. While both roles require strong programming skills and problem-solving abilities, they differ in their focus, required expertise, and job opportunities.
What Is an AI Engineer?
An AI engineer is a technology professional who specializes in developing artificial intelligence systems, machine learning models, and automation tools. These engineers build AI-powered applications that can process data, recognize patterns, and make intelligent decisions without human intervention. To become an AI engineer, professionals typically need a strong foundation in machine learning, deep learning, and data science, along with experience in AI frameworks such as TensorFlow and PyTorch.
Key Responsibilities of an AI Engineer
- Designing and training machine learning models and neural networks.
- Developing algorithms for natural language processing (NLP), computer vision, and predictive analytics.
- Integrating AI models into software applications and cloud-based platforms.
- Optimizing AI performance and ensuring ethical AI implementation.
- Collaborating with data scientists, software engineers, and business teams to deploy AI-driven solutions.
Industries Hiring AI Engineers
AI engineers work across a variety of industries, including:
- Healthcare – AI applications in medical imaging, diagnostics, and personalized treatment plans.
- Finance – Fraud detection, algorithmic trading, and risk assessment.
- Autonomous Systems – Robotics, self-driving vehicles, and smart infrastructure.
- E-commerce & Marketing – Recommendation systems, chatbots, and customer analytics.
- Cybersecurity – AI-driven threat detection and security automation.
AI engineering is a rapidly growing field, driven by advancements in deep learning, big data, and computational power. Professionals in this role work at the intersection of data science and software development, making AI more accessible and efficient for real-world applications.
What Is a Software Engineer?
A software engineer is a professional who designs, develops, tests, and maintains software applications, systems, and frameworks. Unlike AI engineers, who focus on machine learning models and automation, a software engineer designs, develops, and maintains software applications across a variety of industries, from finance to healthcare to gaming.
Key Responsibilities of a Software Engineer
- Writing, testing, and debugging software code using programming languages such as Python, Java, C++, and JavaScript.
- Developing applications for web, mobile, and desktop environments.
- Designing software architecture and ensuring scalability and performance.
- Maintaining and updating existing software to improve functionality and security.
- Collaborating with teams including UI/UX designers, AI specialists, and database administrators.
Industries Hiring Software Engineers
Software engineers are in high demand across multiple industries, including:
- Technology & IT Services – Developing software platforms, cloud applications, and enterprise solutions.
- Finance & Banking – Creating secure online banking systems and financial applications.
- Healthcare – Building electronic health record (EHR) systems and telemedicine platforms.
- Cybersecurity – Developing encryption, authentication, and security protocols for digital safety.
- Gaming & Entertainment – Designing video games, streaming platforms, and interactive media.
Software engineering is one of the most versatile career paths in technology. While AI engineering is a specialized field, software engineers can work in a broader range of industries and roles, making it a flexible and dynamic profession.
AI Engineer vs. Software Engineer: Key Similarities
Although AI engineering and software engineering are distinct fields, they share several fundamental similarities. Both roles require strong programming skills, analytical thinking, and collaboration with cross-functional teams.
Overlapping Skills and Responsibilities
- Programming Expertise – Both AI engineers and software engineers work with languages such as Python, Java, and C++.
- Algorithm Development – AI engineers create machine learning algorithms, while software engineers build algorithms for general software applications.
- Problem-Solving – Both careers involve debugging, optimizing code, and troubleshooting issues to improve software functionality.
- Industry Versatility – Both professionals are employed in a wide range of industries, including healthcare, finance, and cybersecurity.
- Software Development Processes – AI engineers and software engineers follow similar development methodologies, such as Agile and DevOps.
While these similarities highlight the technical overlap between the two careers, their core responsibilities and areas of expertise remain distinct.
AI Engineer vs. Software Engineer: Key Differences
While AI engineers and software engineers share foundational skills, their areas of expertise and career paths differ significantly. AI engineers focus on machine learning and automation, whereas software engineers specialize in building applications and system architectures.
AI Engineer vs. Software Engineer Job Description
- AI Engineer – Specializes in developing and optimizing AI models, including machine learning, deep learning, and neural networks. Their work often involves training models, improving algorithms, and integrating AI into real-world applications.
- Software Engineer – Focuses on designing, developing, and maintaining software applications, frameworks, and infrastructure. Their primary goal is to create efficient, scalable, and user-friendly software solutions.
Skills and Educational Background
- AI Engineers typically need expertise in:
- Machine learning and deep learning algorithms.
- Neural networks and natural language processing (NLP).
- Data science and big data analysis.
- Cloud computing for AI model deployment.
- Software Engineers typically specialize in:
- Object-oriented programming and software development.
- Database management and backend development.
- Frontend technologies and UI/UX design principles.
- System architecture and DevOps methodologies.
Work Focus and Application Areas
- AI Engineers work primarily on AI-driven technologies, such as self-learning algorithms, robotics, and predictive analytics.
- Software Engineers develop applications for web, mobile, and enterprise systems, ensuring functionality and user experience.
These differences highlight how AI engineers are at the forefront of AI innovation, while software engineers provide the foundation for software systems used in everyday applications.
Education Path and Accreditation
Both AI engineers and software engineers typically begin their careers with a degree in a related field. While a bachelor’s degree is the most common entry point, some professionals pursue advanced degrees to specialize further. Certifications can also enhance credentials and career prospects.
Bachelor’s Degrees
A bachelor’s degree provides foundational knowledge in programming, algorithms, and system design. The choice of major depends on whether an individual wants to specialize in AI or broader software development.
AI Engineers often pursue degrees in:
- Computer Science
- Data Science
- Artificial Intelligence
- Electrical Engineering
Software Engineers typically earn degrees in:
- Software Engineering
- Computer Science
- Information Technology
Earning a software engineering bachelor’s degree is often the first step toward becoming a software engineer, providing essential programming and development skills.
Master’s Degrees (Optional but Recommended)
A master’s degree can provide deeper expertise and open doors to advanced roles in research, development, or leadership positions.
AI Engineers may choose to specialize further with a master’s degree in:
- Artificial Intelligence
- Machine Learning
- Data Science
- Computer Science
Software Engineers can advance their careers by earning a master’s degree in software engineering, which can open doors to leadership roles and specialized areas such as cybersecurity and cloud computing.
Online Degree Programs
Online programs offer flexibility for students and professionals looking to earn degrees while balancing work and other responsibilities. Many accredited institutions now offer fully online or hybrid options for engineering and AI-related fields.
Online AI and Software Engineering Degrees:
- Online bachelor’s programs in computer science and software engineering provide foundational knowledge remotely.
- Online master’s degrees in AI, machine learning, and software engineering allow professionals to upskill without disrupting their careers.
Benefits of Online Programs:
- Flexibility to learn at your own pace.
- Opportunities to engage with industry professionals globally.
- Access to cutting-edge coursework and virtual labs.
Online education options, including the best online engineering degrees, allow students to gain technical expertise in a flexible format. When selecting an online program, it’s important to choose an online ABET-accredited engineering program to ensure that the degree meets industry standards and licensing requirements.
Certifications
Earning professional certifications can strengthen credentials and demonstrate specialized expertise.
AI Engineers:
- TensorFlow Developer Certificate
- AWS Certified Machine Learning
- Google AI Certification
Software Engineers:
- AWS Certified Developer
- Microsoft Certified: Azure Solutions Architect
- Certified Scrum Developer
Accreditation
- Software Engineering Programs: Many programs are accredited by ABET (Accreditation Board for Engineering and Technology), ensuring they meet industry standards.
- AI-Specific Programs: AI degrees do not yet have a universal accrediting body, but students should look for programs affiliated with recognized universities and institutions.
Educational choices, whether through traditional or online pathways, impact long-term career growth and specialization in AI or software engineering.
AI Engineer vs. Software Engineer Salary Comparison
According to industry data, both AI and software engineers are considered high-paying engineering jobs, particularly for those with specialized expertise in artificial intelligence or cloud computing. As salaries vary by industry and specialization, professionals should research current engineer salary trends to determine earning potential in their chosen field.
While the U.S. Bureau of Labor Statistics (BLS) does not have a dedicated category for AI engineers, their work closely aligns with Computer and Information Research Scientists, who had a median annual wage of $145,080 in 2023. AI engineers, particularly those specializing in machine learning, automation, and deep learning, often earn salaries in this range, especially in industries like healthcare, finance, and autonomous systems.
AI Engineer vs. Software Engineer Salary Data
For software engineers, the best BLS comparison is Software Developers, Quality Assurance Analysts, and Testers, who earned a median annual wage of $130,160 in 2023. Software engineers working in high-demand fields such as cybersecurity, enterprise software, and cloud computing often earn at the higher end of this range.
Another relevant category is Data Scientists, as AI engineers frequently work with data science methodologies. Data scientists had a median annual wage of $108,020 in 2023, and their roles overlap significantly with AI engineering, particularly in data analytics and machine learning model development.
Finally, for AI engineers who specialize in AI hardware acceleration (such as designing chips for machine learning applications), Computer Hardware Engineers are a relevant comparison. These professionals earned a median annual wage of $138,080 in 2023, reflecting the high demand for expertise in AI-specific hardware optimization.
Factors Affecting Salary
Several factors contribute to salary variations between AI and software engineers:
- Industry and Work Setting – AI engineers typically command higher salaries in industries like finance, defense, and autonomous systems. Software engineers see strong earnings in sectors such as enterprise software, mobile applications, and gaming.
- Education and Specialization – AI engineers often require a master’s degree or higher, contributing to their higher earning potential. The BLS notes that most Computer and Information Research Scientists (closely related to AI engineers) hold a master’s degree. In contrast, software engineers can often enter the field with a bachelor’s degree.
- Experience Level – Senior AI engineers with expertise in deep learning or natural language processing (NLP) tend to earn significantly more than entry-level engineers. Similarly, software engineers who specialize in highly scalable systems or take on leadership roles can surpass the median salary range.
- Geographic Location – Salaries for both careers are highest in major tech hubs such as California, Washington, and New York, where demand for AI and software engineering expertise is highest.
Job Growth and Demand
Both AI and software engineering are among the fastest-growing fields:
- Employment of Computer and Information Research Scientists (including AI engineers) is projected to grow 26% from 2023 to 2033, much faster than the average for all occupations.
- Employment of Software Developers, Quality Assurance Analysts, and Testers is expected to grow 17% during the same period, reflecting the increasing reliance on software-driven solutions.
- The Data Scientist field, which overlaps with AI engineering, is projected to grow 36%, one of the fastest rates of any occupation.
- Employment of Computer Hardware Engineers is projected to grow 7%, reflecting demand for hardware designed for AI and high-performance computing.
With rapid advancements in artificial intelligence, automation, and cloud computing, demand for both AI and software engineers is expected to remain strong for years to come.
Which Career Path Is Right for You?
Choosing between AI engineering and software engineering depends on your interests, career goals, and preferred work style. Both fields offer strong earning potential and job security, but they require different skill sets and areas of expertise.
Questions to Consider
If you’re deciding between becoming an AI engineer or a software engineer, ask yourself:
- Do you enjoy working with data, algorithms, and automation?
- AI engineers focus heavily on machine learning, deep learning, and AI-driven automation. If you enjoy analyzing large datasets, optimizing AI models, and working with neural networks, AI engineering may be a better fit.
- Are you interested in building software applications, tools, and systems?
- Software engineers primarily develop software for various industries, including web applications, enterprise systems, and mobile development. If you enjoy designing, coding, and testing software, this path may be more appealing.
- How much education are you willing to pursue?
- AI engineers often hold advanced degrees, such as a master’s in artificial intelligence, machine learning, or data science. Software engineers can typically enter the field with a bachelor’s degree in computer science or software engineering.
- Would you prefer to work in research and innovation or practical software development?
- AI engineers frequently work on cutting-edge research, developing new AI algorithms and improving automation. Software engineers focus on creating functional, scalable applications for real-world use.
Market Demand and Future Trends
Both AI engineering and software engineering are high-demand careers, but AI-related fields are expected to grow even faster due to the expansion of automation, robotics, and data-driven decision-making. Some key trends include:
- AI and Automation: Many industries are rapidly adopting AI, increasing demand for AI engineers in fields like healthcare, finance, and autonomous systems.
- Cloud Computing and Cybersecurity: Software engineers specializing in cloud-based development and cybersecurity are seeing strong job growth.
- Cross-Disciplinary Roles: Some professionals bridge both fields, such as AI engineers working in software development or software engineers integrating AI features into applications.
If you are passionate about artificial intelligence, automation, and big data, AI engineering may be the right choice. If you enjoy designing, building, and optimizing software solutions, software engineering offers a more traditional and widely accessible career path.
No matter which path you choose, both careers provide excellent job opportunities, competitive salaries, and long-term growth potential in the evolving tech landscape.
FAQ: AI Engineer vs. Software Engineer
Is AI engineering harder than software engineering?
AI engineering tends to be more mathematically intensive, requiring knowledge of linear algebra, statistics, and machine learning algorithms. Software engineering, while also challenging, focuses more on coding, system architecture, and software development methodologies. The difficulty depends on your strengths and interests—those with a strong background in mathematics and data science may find AI engineering more accessible, while those who enjoy coding and software design may prefer software engineering.
Can a software engineer become an AI engineer?
Yes. Many AI engineers start as software engineers and transition into AI roles by learning machine learning, deep learning, and data science concepts. Taking online courses, earning certifications (such as TensorFlow Developer or AWS Certified Machine Learning), and working on AI-related projects can help software engineers move into AI roles.
Which field offers better job security and career growth?
Both AI engineering and software engineering offer strong job security and growth potential. AI engineering is experiencing rapid expansion due to advancements in automation, robotics, and data-driven decision-making. Software engineering remains a high-demand career, with opportunities in nearly every industry. AI roles may see faster job growth, but software engineering offers a broader range of job opportunities.
Do AI engineers need a PhD?
No, a PhD is not required to become an AI engineer. While advanced research roles in AI may require a doctorate, most AI engineers enter the field with a bachelor’s or master’s degree in computer science, AI, or data science. Industry certifications and hands-on experience with AI tools and frameworks are often sufficient for securing a job.
Is AI replacing software engineering jobs?
AI is transforming software engineering but not eliminating jobs. AI can automate certain coding tasks and improve software development efficiency, but skilled software engineers are still needed to design, build, and maintain complex applications. Instead of replacing software engineering, AI is becoming an integrated tool within software development processes.
Final Thoughts: Choosing Between AI and Software Engineering
AI engineering and software engineering are both rewarding career paths with strong job prospects and high earning potential. The best choice depends on your interests, skills, and career goals. If you are passionate about machine learning, automation, and data-driven problem-solving, AI engineering may be the right fit. If you prefer designing, developing, and maintaining software applications, software engineering offers a broader range of opportunities.
Regardless of the path you choose, gaining relevant experience, pursuing specialized education, and staying up to date with industry trends will help you build a successful career in either field. Explore educational programs, certifications, and hands-on projects to determine which discipline aligns best with your goals.