AI Engineer: What they do and how to become one
AI Engineers play a vital role in developing and implementing AI systems. They work across data science, data engineering, and subject-matter expertise to make sure these solutions are scalable, reliable, and follow ethical standards.
How to become an AI engineer (step by step guide)
In a fast-changing job market, businesses need AI engineers to harness artificial intelligence for a competitive advantage.
To get started in this in-demand career, you need a varied skill set that includes programming, machine learning and an understanding of AI governance frameworks. These are the steps you can take to secure yourself a career in AI engineering:
1. Develop essential skills in machine learning and programming
A role as an AI engineer requires several essential technical skills, including experience of programming languages like Python and R, and core understanding of data science and machine learning principles.
It's equally important for AI engineers to pair technical knowledge with an understanding of AI governance, ethics and compliance frameworks.
2. Build vital soft skills
As with many technical roles, communication is key. AI engineers need more than just technical prowess; they need to be able to convey complex ideas and show a willingness to adapt to the varied challenges that they will face as AI evolves over time.
3. Explore an AI engineering apprenticeship
For career changers, or career starters, an AI apprenticeship is a great option. A programme like the Digital AI Support Level 3 will give learners the perfect starting point for building foundational AI skills and introducing AI principles into their role.
For more experienced data and development professionals, or those with relevant degrees, the AI Engineer Level 6 apprenticeship is a course designed to kickstart a career in AI engineering.
4. Build AI skills with a course or certification
Work towards a role in AI engineering by taking a relevant course or certification. Training in topics like agentic AI, large language models, prompt engineering and data science will help to build the critical skills that are needed to succeed as an AI engineer.
What are the top skills needed to become an AI engineer?
To succeed in their role, an AI engineer needs a blend of technical and soft skills, including:
-
Programming languages (Python, R, Java and C++)
-
AI governance and compliance
-
Data science and machine learning
-
Mathematics and statistics
-
Creativity and critical thinking
-
Natural language processing
-
Cloud computing (AWS, Azure and GCP)
-
DevOps
-
Database management
-
Deep learning
AI engineer role - all you need to know
What is AI engineering?
AI engineering is the practice of designing, developing, and deploying AI systems. It combines principles from software engineering, data science, and AI to build scalable, reliable, and ethical solutions that address real-world problems.
What does an AI engineer do?
AI engineers design, build, and put AI systems into practice. They integrate AI models with software applications to create intelligent solutions that can process information, understand and generate content, make predictions, assist in decision-making, and automate complex tasks.
What are the responsibilities of an AI engineer?
AI engineers support businesses in adopting artificial intelligence for a competitive advantage. This adoption allows companies to innovate faster, run operations more efficiently, offer personalised experiences, and keep humans involved in key decisions. They are responsible for developing AI strategies that improve efficiency, scalability, and growth.
Their day to day role involves designing, building and putting AI systems into practice. They integrate AI models with software applications to create intelligent solutions that can process information, understand and generate content, make predictions, assist in decision-making, and automate complex tasks.
They also work across data science, data engineering, and subject-matter expertise to make sure these solutions are scalable, reliable, and follow ethical standards.
How much do AI engineers earn?
The average salary for an AI engineer in the UK is £56k[1], although in some sectors they can earn over £100k.
Do I need a degree to become an AI engineer?
Although a degree in computer science, mathematics or data science would be beneficial[2], it is not a necessity. It is possible to become an AI engineer through self-paced learning, certification courses and training programmes, such as an apprenticeship.
Can I do an AI engineering apprenticeship?
Yes, you can become an AI engineer through the Level 6 AI Engineer programme. Learn more about AI Apprenticeships.
What are the best courses for AI engineers?
We offer a range of courses to help AI engineers develop their skills and future-proof their careers. Here are some of the best courses suited to this ever-important role:
- Text Analysis and LLMs in Python
- Agentic AI Foundations
- Gen AI Engineering with Databricks
- Certified AI Governance Professional
- Explore more AI Engineering courses
All of our courses are taught by experts with real-world AI experience and include hands-on labs, exam practice and course materials.
This article was written by QA's team of accredited AI experts.
Sources
AI engineer learning paths
Whether you're new to Gen AI, or ready to deliver agentic AI services, our programmes can be tailored to developers and engineers of all experience levels.
1. Starting your Gen AI engineering journey
Generative AI Essentials
Gain the skills you need to make the most of generative AI through real-world applications – and how to use it in a safe and ethical way.
Data Handling in Python
This three day course is perfect for engineers wishing to learn how to use Python to tune and develop machine learning and AI models.
2. Working with text data and LLMs
Text Analysis with LLMs with Python
This 3 day course provides an in-depth exploration of Large Language Models (LLMs) and their applications and covers key Generative AI skills expected of AI Engineers.
3. Creating Agentic AI Services
Building AI agents with python
Learn to design, build, and govern safe, ethical multi-agent AI systems using LangGraph, integrating real-world tools and completing a hands-on project to showcase within your organisation.
Interested in AI engineering training?
Let's talk
Start your digital transformation journey today
Contact us today via the form or give us a call
