Artificial Intelligence Engineer
BoomingBuilding software systems that incorporate AI capabilities into products and workflows
Artificial Intelligence Engineer Salary
United Kingdom
£60,000 – £110,000
United States
$120,000 – $190,000
Varies by location, sector, and experience. Last updated: 2025.
What Is an Artificial Intelligence Engineer?
An Artificial Intelligence Engineer designs and builds software systems that incorporate AI capabilities — from recommendation engines and classification systems to LLM-powered applications and computer vision pipelines. The role sits between software engineering and machine learning, applying existing AI models and techniques to solve specific product and business problems rather than conducting original research.
Where an AI Research Scientist advances the science of AI and an ML Engineer focuses on production infrastructure for model training and serving, an AI Engineer focuses on integration and application — connecting AI capabilities to products, workflows, and user-facing features. The role has expanded significantly with the rise of foundation models and LLM APIs, making it more accessible to engineers from software development backgrounds who develop AI integration skills. Strong programming ability, a working understanding of modern AI models, and product thinking are the core requirements.
What Does a Artificial Intelligence Engineer Do?
- Design and build AI-powered features and applications using foundation models, APIs, and orchestration frameworks
- Integrate large language models, vision models, and other AI capabilities into product and internal business workflows
- Build and maintain prompt engineering systems, automated evaluation frameworks, and structured output pipelines
- Evaluate AI model performance across accuracy, latency, and cost dimensions and select appropriate models per use case
- Implement guardrails, output monitoring, and human feedback loops to maintain AI system reliability in production
- Track the evolving AI model landscape and assess newly released capabilities against existing product and workflow needs
Artificial Intelligence Engineer Skills
Hard Skills
- Machine Learning
- Natural Language Processing
- Deep Learning
- REST API Design
- Prompt Engineering
- Model Evaluation
- Feature Engineering
- Software Architecture
- Python
- Cloud Architecture
Soft Skills
- Analytical ThinkingEvaluating AI model suitability for specific problems
- Product ThinkingConnecting AI capabilities to user and business value
- CollaborationWorking across ML, software, and product teams
- CommunicationExplaining AI behaviour and limitations to non-technical teams
- Problem SolvingDiagnosing integration failures in AI-powered systems
- AdaptabilitySpanning foundation models, APIs, and custom ML pipelines
Artificial Intelligence Engineer Tools & Software
How to Become a Artificial Intelligence Engineer
Typical Route
Most AI Engineers hold a Bachelor's in Computer Science, Software Engineering, or Mathematics. Unlike an AI Research Scientist, a PhD is not expected — the role rewards engineering ability and practical implementation over research credentials. Programs at Carnegie Mellon, the University of Washington, and Georgia Tech offer strong machine learning foundations. Large ABET-accredited Computer Science programs at public universities — UC San Diego, UIUC, UT Austin — are well-established pipelines. An MS in AI or Computer Science supports progression into specialised roles.
Alternative Route
AWS Machine Learning Specialty and Google Professional Machine Learning Engineer are the primary credentials for platform-specific progression and are common preparation targets. DeepLearning.AI's AI Engineering certificates on Coursera provide structured learning pathways for building applied AI skills. Bootcamps including Springboard's AI/ML track and Fullstack Academy offer structured entry for software engineers transitioning into the field. Project portfolios — LLM integrations, RAG systems, open-source AI contributions — consistently outweigh formal certifications in US hiring.
A Day in the Life of an Artificial Intelligence Engineer
Morning
Afternoon
Artificial Intelligence Engineer Career Path
Software / ML Engineer
0–3 yrs
AI Engineer
3–5 yrs
Senior AI Engineer
5–7 yrs
Staff / Principal AI Engineer
7–9 yrs
Head of AI / VP Engineering
9+ yrs
Artificial Intelligence Engineer Job Outlook
AI Engineering is one of the fastest-growing roles in technology. The widespread availability of foundation model APIs has made AI integration a core engineering discipline rather than a specialist niche. Demand is accelerating across every sector as organisations embed AI capabilities into products and internal workflows. Engineers who can build reliable, evaluated, production-grade AI systems are in exceptionally high demand.