Searching for entry-level engineering jobs but keep seeing “experience required”? Looking for AI jobs for beginners and hitting the same wall?
If “entry-level” still feels hard to break into, you’re not alone. For years, hiring focused heavily on credentials and prior experience. But that’s changing: 64.8% of employers report using skills-based hiring for new entry-level hires (NACE Job Outlook 2025).
Translation: to get hired, you need proof you can do the work—not just a list of classes. This article shows you a practical path to build that proof.
In this article, “engineering” refers to software engineering roles, including coding, systems design, and AI-driven technical work.
Why Entry Level Software Engineering & AI Jobs Feel Out of Reach
Students searching for how to get engineering experience as a student, no experience engineering jobs, or how to get into AI without experience run into the same frustration.
Most entry level engineering jobs still expect applied skills.
Employers want proof that you can solve problems, evaluate outputs, and work within real constraints.
What Engineering and AI Teams Actually Look For
Modern engineering, especially in AI-driven environments, is less about memorizing tools and more about aptitude.
Engineering teams look for:
• Problem-solving under constraints
• Ability to evaluate AI outputs
• Clear, structured reasoning
Many AI jobs for beginners focus on reviewing outputs, refining workflows, and improving systems rather than building complex models from scratch.
If you’re unsure whether this type of work fits you, explore our AI career guide or take one of our quick career quizzes to assess your strengths.
A Practical Path to Software Engineering & AI Experience
If you’re aiming for entry level engineering jobs but starting from zero, think in two phases:
- Build proof you can do the work
- Use that proof to qualify for paid opportunities
Here’s how to do that without guessing what employers want.
Step 1: Build Applied Experience with Software Engineering & AI Simulations
One practical way to build experience is through software engineering and AI simulations that mirror real-world projects. Instead of just learning concepts, you work through realistic tasks that reflect how technical teams actually operate. For example:
- Wells Fargo – Software Engineering Simulation
Practice backend logic and technical problem-solving in a real-world banking context. - BCG – Gen AI Simulation
Work through applied generative AI use cases and output evaluation. - Forage – Data Labeling Simulation
Gain hands-on experience evaluating AI outputs and improving model quality.
Each simulation helps you build tangible, applied experience, which the employers look for in entry-level software engineering & AI roles.
You can also explore the full catalog of software engineering & AI simulations here.
Step 2: Explore Paid Projects When You’re Ready
Once you’ve built foundational readiness, you can explore paid engineering and AI project opportunities through Mercor.
Opportunities are remote, flexible, and project-based. Roles span applied AI evaluation, engineering support, workflow optimization, and technical problem-solving.
If you don’t see a role that fits today, check back. New projects are added regularly as companies’ needs evolve!
How This Builds a Real Engineering & AI Portfolio
When you complete simulations and participate in Mercor projects, you build applied problem-solving examples, gain AI system evaluation experience, contribute to real workflow improvements, and develop resume-ready project work.
That’s far stronger than listing tools on a resume. It shows how you think and how you work, and that’s exactly what employers hiring for entry level engineering jobs care about.
Pick Your Path
Not sure where to begin? Start with the area that interests you most:
You don’t need to wait until you feel fully qualified. You need to start demonstrating aptitude. That’s how you move from searching for entry level engineering jobs to actually landing one.
Ready to start? Begin with a simulation here.
FAQs
Start with applied simulations that mirror real engineering work. Then move into paid, project-based opportunities through Mercor to build real experience.
Yes. Many AI roles focus on evaluating outputs, refining workflows, and supporting systems. You don’t always need advanced degrees, but you do need demonstrated aptitude.
Yes. Mercor offers remote, flexible engineering and AI projects that allow students and early-career professionals to gain paid experience.
Requirements vary by project. Many opportunities prioritize analytical ability and applied thinking over formal credentials.
