AI is shaking up engineering jobs—entry-level roles feel the squeeze, but experienced engineers who team up with AI are finding smarter, faster ways to get things done.
AI is reshaping entry-level jobs
Many people assume young engineers will automatically benefit from AI skills. But according to Adzuna’s research , entry-level jobs are actually declining due to AI. This trend isn’t limited to generic roles—it’s starting to show up in DevOps as well.
Since ChatGPT’s launch in late 2022, AI coding tools like GitHub Copilot, Claude Code, and Cursor IDE have evolved far beyond simple autocomplete. They can now generate full code snippets, debug, explain logic, and even handle small autonomous coding tasks.
For a fresh graduate DevOps engineer, this can be tricky. Imagine a junior engineer relying on AI to write a CI/CD pipeline. The pipeline may work flawlessly, but if it’s automating the wrong business process—say deploying test builds to production—they may not even realize the mistake. AI can produce technically correct results that don’t actually match the business goal.
This is why human oversight remains crucial. Experienced engineers bring the context and domain knowledge to ensure AI-generated solutions actually make sense.
The takeaway? Entry-level engineers who pair domain knowledge and critical thinking with AI tools will stand out. Simply relying on AI to complete tasks without understanding the underlying systems leaves you vulnerable to being replaced by AI itself.
Working alongside AI
The shift isn’t just about cutting costs—it’s also about increasing productivity. Mid-level engineers are now expected to use AI effectively in their daily workflows.
For example, a DevOps engineer can use AI to:
- Write unit tests automatically for new scripts or pipelines
- Generate clearer documentation for complex deployment flows
- Analyze system performance and suggest optimizations
However, engineers who haven’t updated their skills in years may find themselves at risk. Those who remain at a junior level despite mid-level experience might be “overtaken” by AI-assisted workflows.
The good news? AI is also creating new opportunities. There’s demand for engineers who can:
- Develop AI-enhanced tools for existing systems
- Build custom AI applications for internal DevOps processes
- Create intelligent monitoring and alerting systems using AI
In short, the key isn’t avoiding AI—it’s learning to work alongside it. Engineers who can combine technical expertise, domain knowledge, and AI-assisted productivity will not just survive—they’ll thrive.