An AI engineer builds products and tools on top of existing AI models. That means connecting large language models to a company’s data, building chatbots and AI agents, and making sure they work reliably at scale. It’s usually not about inventing new models. LinkedIn has ranked AI engineer as the fastest-growing job title for young workers two years in a row.
What does an AI engineer do day to day?
Think of it this way: researchers build the engine, and AI engineers build the car around it.
Most AI engineers take models that already exist and make them useful inside a real business. A typical week might include:
- Connecting a model to company data, so a chatbot can answer questions about internal policies or product docs
- Building AI agents that complete multistep tasks, like pulling data, summarizing it, and drafting a report
- Testing and evaluating outputs to catch wrong answers before customers see them
- Making it fast and affordable to run, since every model call costs money
- Working with non-technical teams to figure out which problems AI should actually solve
One expert described the role to Dice as covering everything from heavy API work to business consulting around bots. The title is broad, so read the job description closely.
How is an AI engineer different from a machine learning engineer or data scientist?
The lines blur, but here’s the general split:
- AI engineer: builds applications using existing models. Heavy on software engineering and integration.
- Machine learning engineer: trains, tunes, and deploys models, often working closer to the math and the data. LinkedIn sometimes groups the two titles together.
- Data scientist: analyzes data to answer business questions, often using statistics and modeling. Less focused on shipping products.
Is AI engineering an entry-level job?
Increasingly, yes. LinkedIn added 639,000 AI-related job postings in the U.S. between 2023 and 2025, and 75,000 of those were AI engineer roles. Entry-level AI engineer listings now come from consulting firms, financial services, defense contractors, and universities, not just tech companies.
Here’s the honest part, though. As AI handles more routine coding and data-cleaning tasks, the bar for entry-level roles goes up. Employers want to see that you’ve built something real, not just taken a class. That’s actually good news if you’re willing to build.
What skills do AI engineers need?
According to LinkedIn, the most common skills among AI engineers include LangChain, retrieval-augmented generation (RAG), and PyTorch. In plain English:
- Python: the default language for AI work
- Working with model APIs: sending prompts, handling responses, managing costs
- RAG: connecting a model to outside data so it gives accurate, specific answers
- Agent frameworks like LangChain for building multistep AI workflows
- Software basics: version control, testing, and deploying code
What other new AI job titles should new grads know?
AI engineer gets the headlines, but it’s not the only door in. A few others worth knowing:
- AI consultant or strategist: helps companies figure out where AI fits. LinkedIn ranks it as the second-fastest-growing role, though it often leans more experienced.
- Forward-deployed engineer: works directly with customers to plug AI into their real processes. Great for people who like both code and conversation.
- Agentic AI engineer: specializes in AI agents that complete tasks on their own.
- MLOps engineer: keeps AI systems running, monitored, and scalable.
- AI trainer or data annotator: reviews and labels data that teaches models. A good entry point for non-CS majors with strong subject knowledge.
Do you need a computer science degree to become an AI engineer?
It helps, but it’s not the only path. Plenty of AI engineers come from math, physics, engineering, or self-taught backgrounds. What matters most is proof you can build.
If you’re not a CS major, roles like AI consultant, AI trainer, or AI product operations can be a way in. Over time, you can build the technical skills to move closer to engineering.
How do you get started as a new grad?
Build one project from start to finish. For example: a chatbot that answers questions using a public dataset, like your city’s open data or a set of research papers. Put the code on GitHub, write a short explanation of what you built and what you’d improve, and link it on your resume.
That single project shows you can work with models, handle data, and ship something. That’s exactly what entry-level hiring managers are looking for.
If you’re a CS or computer engineering grad, this matters even more. Those majors have some of the highest unemployment rates right now, according to the New York Fed. AI skills are one of the clearest ways to stand out.
FAQ
Is prompt engineering still a job? Fewer postings use it as a standalone title now. The skill has mostly been folded into broader roles like AI engineer.
How much do AI engineers make? Pay varies widely by company, location, and experience. Check the salary range on real postings, since many states now require them.
Will AI replace AI engineers? AI tools are changing how AI engineers work, but someone still has to decide what to build, connect systems, and check the results. That’s the job.
Which industries hire entry-level AI engineers? Beyond tech, financial services, consulting, defense, and higher education are all hiring for the role.
