Software Engineers Vs AI Engineers: Which Career Has Better Growth?
Posted inBusiness

Software Engineers Vs AI Engineers: Which Career Has Better Growth?

Posted inBusiness

Introduction

Software engineering has long been one of the most established technology careers in the UK. AI engineering, meanwhile, is becoming increasingly important as businesses adopt machine learning, generative AI and automation. This raises a practical question for students, graduates and experienced developers: which career offers better long-term growth? The answer depends on your skills, interests and career goals. Both paths have strong potential, but they require different technical strengths and offer different opportunities.

What Does A Software Engineer Do?

Software engineering focuses on designing, developing, testing and maintaining digital products and systems.

You may work on websites, mobile applications, cloud platforms, business software or large-scale enterprise systems. Your work can involve programming languages such as Python, Java, JavaScript, C and C++, alongside databases, APIs, testing tools and cloud services.

Software engineering remains a broad career because almost every industry relies on software. In the UK, you could find opportunities across financial services, healthcare, retail, manufacturing, government and technology companies.

Where Software Engineering Can Lead

The career path can develop in several directions:

  • Technical Specialisation: You can specialise in areas such as cloud engineering, cybersecurity, DevOps, backend development or mobile development.
  • Technical Leadership: With experience, you can progress towards senior engineer, technical lead, principal engineer or software architect positions.
  • Product-Focused Roles: Software engineers can also move towards engineering management, product development or technical consulting.

This flexibility makes software engineering a strong foundation even if you later decide to move into AI.

What Does An AI Engineer Do?

AI engineering focuses on building and deploying systems that use artificial intelligence. The role sits between traditional software development, data and machine learning.

An AI engineer might develop machine learning applications, integrate large language models into products, build recommendation systems or create AI-powered automation. The role can also involve evaluating models, managing data pipelines and ensuring AI systems work reliably in production.

The UK government’s recent labour market research indicates that demand for AI-related skills is expected to increase significantly. Its projections suggest that jobs involving core AI activities could reach around 3.9 million by 2035, although this includes a broad range of roles rather than AI engineers alone.

Skills You May Need

AI engineering usually requires a combination of software and analytical skills:

  • Programming: Python is widely used alongside frameworks and tools for developing AI applications.
  • Machine Learning: You need to understand concepts such as model training, evaluation and optimisation.
  • Data Skills: Working with structured and unstructured data is an important part of many AI projects.
  • Deployment: AI models need to be integrated into real applications, which makes software engineering and cloud knowledge valuable.

The UK’s AI Labour Market Survey also highlights a significant skills gap. In its 2025 findings, 97% of respondents identified at least one AI skills gap while 57% reported a technical skills gap.

Software Engineering Vs AI Engineering: Which Has Better Growth?

There is no single winner because the two careers are increasingly connected.

Area

Software Engineering

AI Engineering

Demand

Broad across most industries

Growing rapidly across AI-adopting sectors

Core skills

Programming, systems, architecture

Programming, AI, data and machine learning

Career flexibility

Very high

High but more specialised

Entry barrier

Generally more accessible

Often requires additional AI knowledge

Future relevance

Strong as digital systems expand

Strong as AI adoption increases

For someone starting out, software engineering can provide a wider foundation. For an experienced developer who enjoys data, automation and machine learning, AI engineering can offer a natural next step.

Why Combining Both Skills May Be The Strongest Option

The distinction between software engineers and AI engineers is becoming less rigid. Modern AI products still need reliable software, APIs, cloud infrastructure, testing and security.

If you are already a developer, adding AI skills can therefore expand your career options without requiring you to abandon your existing experience. This is particularly relevant when considering tech recruitment london, where employers may look for professionals who can combine strong software development knowledge with practical AI capabilities.

The UK government has also identified AI upskilling as a workforce priority, with its AI Skills Boost programme aiming to help 10 million UK workers develop AI skills by 2030.

How Should You Choose?

Your decision should be based on the type of work you want to do rather than the popularity of a job title.

Choose software engineering if you enjoy building applications, solving programming problems and working across different technology areas. Choose AI engineering if you are particularly interested in machine learning, data-driven systems and developing AI-powered products.

If you are already working as a software engineer, you do not necessarily need to make an immediate career switch. Learning Python, machine learning fundamentals, AI APIs, model evaluation and cloud-based AI deployment can help you gradually move towards AI-focused positions.

Conclusion

Software engineering offers breadth, flexibility and a strong foundation across the UK technology sector. AI engineering offers growing opportunities as organisations invest in AI products and automation. Neither career is guaranteed to provide better growth for everyone.

For many professionals, the most practical approach is to combine software engineering fundamentals with relevant AI skills. This can help you remain adaptable as technology and employer requirements continue to change.

FAQs

  • Is AI Engineering Better Than Software Engineering?

Not necessarily. AI engineering is growing quickly but is more specialised. Software engineering offers broader opportunities across industries and can provide a strong foundation for moving into AI later.

  • Can A Software Engineer Become An AI Engineer?

Yes. Software engineering experience is highly relevant to AI engineering. You can build on programming, system design and development skills by learning machine learning, data handling and AI deployment.

  • Is AI Engineering A Good Career In The UK?

AI engineering has strong potential in the UK as businesses increasingly adopt AI. Government research also identifies significant AI skills shortages, suggesting continued demand for relevant technical capabilities.

  • Should Students Learn AI Or Software Engineering First?

Software engineering fundamentals can provide a useful foundation because AI applications still require programming, testing, deployment and system design. Students can then add AI and machine learning skills as their interests develop.