The rapid growth of generative AI, combined with broader economic uncertainty and the demographic shift in the workforce, is causing employers to recategorize tech roles and realign pay structures at a rapid pace, according to David Foote, chief analyst and research officer for Foote Partners LLC, a firm that tracks, analyzes and reports on tech workforce trends and compensation practices.
“In short, we continue to see demand for generalists and specialists, but what companies really want are versatilists,” Foote said. Versatilists, like generalists, are capable in many areas—but they possess deep knowledge in one or more specific domains and can switch to another role or widening scope of situations with ease.
Given the ongoing changes in job structures, Foote estimates that experienced tech pros have about12 months to successfully reposition their careers by learning new skills.
Here’s a look at how recent changes in AI and other technologies, the workforce and the broader economy have already transformed roles, skills and pay.
Emerging Roles for Versatilists
While AI's advancements are automating and potentially eliminating some jobs, it's also creating new opportunities that require a mix of experience and human decision-making. Research from the World Economic Forum confirms this hybrid trend.
Versatilists routinely earn robust salaries and higher-than-average cash pay premiums—not because of any one or two skills, but because of how they synthesize and apply them, Foote said. Here are some examples of emerging roles for versatilists across various disciplines.
In today’s interconnected risk, security, and privacy ecosystem, versatilists aren’t just nice to
have—they’re essential. For instance, they can assist in developing and implementing comprehensive cybersecurity strategies, deploy advanced threat detection systems, conduct audits and train staff in best practices. Some key positions include:
- GRC-Cybersecurity Hybrid
- Privacy Engineer
- Security Ops-Audit Crossover
Software Engineering
A versatilist in software engineering not only designs microservices in Go or Node.js (for example) but also understands the cloud infrastructure they run on. They integrate observability and contribute to data governance discussions when building user-facing analytics. Moreover, they can communicate with product managers, data scientists and site reliability engineers—and be respected by all. Here are some “evolved” roles in this context:
- Software Engineer and Platform Integrator
- Engineering Lead and Security Champion
- DevOps-Enabled Software Engineer
Cloud Engineering
A versatilist in cloud engineering might automate cross-cloud deployments with Terraform, design serverless solutions, optimize FinOps, and also contribute to platform security. They collaborate across teams to architect scalable systems—not just deploy them.
- Cloud Platform Engineer
- Multi-Cloud Infrastructure Strategist
- Cloud Reliability and Resilience Engineer
Big Data and Analytics
A versatilist in big data and analytics collaborates with data scientists on feature engineering, manages data quality, and understands business KPIs well enough to contribute to data product decisions. They bridge engineering, analytics and the business.
- Data Platform Engineer
- Analytics Engineer and Data Governance Liaison
- Data Engineer and ML Platform Enabler
AI Engineering
A versatilist in AI engineering understands not only model design, but also MLOps, data labeling pipelines, cloud deployment strategies, and ethical AI considerations. They don’t just train models—they deliver AI solutions that scale and comply with governance policies.
- AI Engineer and MLOps Lead
- AI Product Engineer
- Responsible AI Engineer
Networking
A versatilist in the networking field might be an architect who understands SDN, cloud-native networking, edge computing, and can collaborate with cloud teams, DevOps, and InfoSec to build secure, high-performance environments. They understand networking not as plumbing—but as strategic infrastructure. Some example roles might include:
- Network and Cloud Connectivity Architect
- Cloud Network Security Architect
- SD-WAN and Observability Engineer
Skills Earning High Pay and Still Growing in Value Over the Last Six Months
What are the skills that employers value most, given the current and future impact of generative AI?
“What we’ve learned over the last six months, is that certifications may no longer be a superpower, unless you’re a specialist,” Foote said. For instance, of the highest-paying certifications, half are in cybersecurity. For other professionals, adding AI integration skills, practical knowledge about Large Language Models (LLMs) as well as human skills to a solid tech foundation will be the best way to move your career forward in the near term.
IT Certifications Earning Highest Pay and Still Growing In Market Value (six-month data through April 1, 2025)
SAS Certified Professional: AI and Machine Learning
Average Pay Premium: 12 percent of base salary equivalent
Market Value Increase: 33.3 percent
Artificial Intelligence Engineer (AIE - all tracks)
Cisco Certified Network Professional - Security
EC-Council Certified Chief Information Security Officer (CCISCO)
Offensive Security Certified Expert
Oracle Cloud Platform Application Integration Certified Professional
Average Pay Premium: 11 percent of base salary equivalent
Market Value Increase: 10 percent
Certified in Risk and Information Systems Control (CRISC)
EC-Council Certified Ethical Hacker (CEH)
Offensive Security Certified Professional (OSCP)
Offensive Security Web Expert (OSWE)
PMI Portfolio Management Professional (PfMP)
Average Pay Premium: 10 percent of base salary equivalent
Market Value Increase: 11.1 percent
Non-Certified Skills Earning Highest Pay and Still Growing In Market Value (six-month data through April 1, 2025)
AWS DevOps
Average Pay Premium: 23 percent of base salary equivalent
Market Value Increase: 21.1 percent
Large Language Model/LLM tuning
Average Pay Premium: 23 percent of base salary equivalent
Market Value Increase: 15 percent
Smart Contracts
Average Pay Premium: 22 percent of base salary equivalent
Market Value Increase: 15.8 percent
Convolutional Neural Network
Site Reliability Engineering
Average Pay Premium: 22 percent of base salary equivalent
Market Value Increase: 4.8 percent
Blockchain
Average Pay Premium: 21 percent of base salary equivalent
Market Value Increase: 23.5 percent
Identity Access Management
Average Pay Premium: 21 percent of base salary equivalent
Market Value Increase: 16.7 percent
Ethereum
Average Pay Premium: 21 percent of base salary equivalent
Market Value Increase: 10.5 percent
Neural Networks
Average Pay Premium: 21 percent of base salary equivalent
Market Value Increase: 5 percent
Azure Machine Learning
Security Testing
Average Pay Premium: 20 percent of base salary equivalent
Market Value Increase: 25 percent
Data Engineering
Threat Detection/Modelling/Management
Average Pay Premium: 20 percent of base salary equivalent
Market Value Increase: 11.1 percent
Most Valuable Soft Skills
Some of the most highly valuable soft skills that garner premium pay according to Foote include:
- Communicate to collaborate (verbal/non-verbal)
- Competitive dynamics
- Financial acumen
- Motivation and self-awareness
- Ability to inspire others
- Authenticity & integrity
- Curiosity and critical thinking
- Resiliency, flexibility and agility
- Attention to detail
- Discipline and consistency
- Solid work ethic
Foote categorizes soft skills as those that you’re born with, those that can be taught, and those that are difficult (but not impossible) to acquire. That’s good news for tech pros looking to stay relevant and earn premium pay by becoming versatilists.