The tech world rewards people who can adapt—and even more so, people who can communicate their value while adapting. Are you one of them? And how can you get into the best paid fields in tech? Let’s have a look, shall we?
Santosh asked, “Where should I focus on IT today?”
Santosh, like many professionals in the tech world, wants to know where to invest his time and energy next. Should he double down on cloud computing? Learn about AI? Or pivot toward cybersecurity?
It’s a fair question—tech is moving fast, and while there’s no shortage of headlines declaring which skill is “the next big thing,” making smart decisions about your career should not be based on trends. Focus on where value and opportunity meet you. Let’s start with what’s hot—and profitable—right now.
Here’s what’s actually in demand
Despite economic shifts and layoffs in certain corners of tech, some areas continue to grow rapidly and command high salaries:
- AI and Machine Learning: With generative AI booming, demand for AI engineers, ML researchers, and prompt engineers is skyrocketing. Professionals in this space can easily command big salaries, especially with experience in NLP, computer vision, or reinforcement learning.
- Cybersecurity: As data breaches become more frequent and sophisticated, companies are heavily investing in security. Roles like Security Engineer, SOC Analyst, and CISO are highly paid and in short supply.
- Cloud Architecture and DevOps: The need for scalable infrastructure hasn’t gone away, and DevOps/Cloud Engineers who can streamline deployment and manage cloud systems efficiently are critical to business operations.
- Data Engineering: With companies collecting more data than ever, there’s a growing need for professionals who can store, clean, and pipeline that data to make it useful. Data Engineers are the unsung heroes behind any good AI or analytics team.
- Product Management in Tech: Technical PMs—those who can speak both engineering and business—are uniquely valuable. They drive product decisions and align tech efforts with user needs and revenue.
- Cybersecurity: As data breaches become more frequent and sophisticated, companies are heavily investing in security. Roles like Security Engineer, SOC Analyst, and CISO are highly paid and in short supply.
- Cloud Architecture and DevOps: The need for scalable infrastructure hasn’t gone away, and DevOps/Cloud Engineers who can streamline deployment and manage cloud systems efficiently are critical to business operations.
- Data Engineering: With companies collecting more data than ever, there’s a growing need for professionals who can store, clean, and pipeline that data to make it useful. Data Engineers are the unsung heroes behind any good AI or analytics team.
- Product Management in Tech: Technical PMs—those who can speak both engineering and business—are uniquely valuable. They drive product decisions and align tech efforts with user needs and revenue
Positioning is what turns a job into a career—and a career into a brand.
How tech professionals can pivot without burning everything down
Switching fields can be intimidating. But you don’t have to start from scratch to make a meaningful change. Whether you’re a QA tester wanting to get into DevOps, or a backend developer curious about AI, focus on leverage.
Here’s how to pivot strategically:
- Find your transferable skills: For example, if you’re in QA, you likely understand deployment pipelines, debugging, and system integration—skills that are useful in DevOps and SRE roles.
- Start small and build projects: Don’t wait for permission. Want to work in data science? Start a personal project with public datasets. Learning cloud? Deploy your personal site using AWS or GCP.
- Upskill on the side: Online courses, certifications, and bootcamps can help.
- Network strategically: Connect with people already in your target role. Ask for informational interviews. Join Slack groups, Discord servers, or LinkedIn communities where people discuss real problems in that space.
Tell a better story: When you’re ready to apply, frame your pivot in terms of growth, not lack of experience. “I’ve spent 3 years optimizing SQL performance and now I’m transitioning into data engineering to apply that expertise at scale” sounds much stronger than “I want to try something new.”
