NLP Engineer vs Cloud Security Engineer: Which Pays More?
Side-by-side salary comparison by city, experience level, and career growth outlook. Data reflects current market rates.
NLP Engineer
Build natural language processing systems and text AI models.
Cloud Security Engineer
Secure cloud infrastructure against threats and ensure regulatory compliance.
Cloud Security Engineer earns more on average — the national median is $8,950/year (7%) higher than a NLP Engineer. However, salaries vary significantly by city, employer, and experience level — see the city-by-city breakdown below.
NLP Engineer vs Cloud Security Engineer — Salary by City
National median figures in USD across top cities.
| City | NLP Engineer | Cloud Security Engineer | Difference |
|---|---|---|---|
| San Francisco, CA | $175,055 | $190,858 | NLP $15,803 |
| New York, NY | $135,980 | $140,470 | NLP $4,490 |
| Seattle, WA | $174,364 | $183,462 | NLP $9,098 |
| Austin, TX | $137,212 | $141,862 | NLP $4,650 |
| Chicago, IL | $129,954 | $142,690 | NLP $12,736 |
| Boston, MA | $156,119 | $169,112 | NLP $12,993 |
| London, UK | £94,915 | £99,649 | NLP $4,734 |
| Toronto, Canada | CA$156,823 | CA$167,154 | NLP $10,331 |
Frequently Asked Questions
Does a NLP Engineer or Cloud Security Engineer earn more?+
A Cloud Security Engineer earns more on average. The national median salary for a NLP Engineer is $120,230/year, compared to $129,180/year for a Cloud Security Engineer — a difference of $8,950 (7%).
Which has better career growth — NLP Engineer or Cloud Security Engineer?+
NLP Engineer roles are growing at 42% YoY while Cloud Security Engineer demand is growing at 36% YoY. NLP Engineer has stronger near-term demand growth.
Can you switch from NLP Engineer to Cloud Security Engineer?+
Yes. Many professionals transition between these roles, especially since both are in the same category. Shared skills include: analytical thinking, communication, and industry knowledge.
Which is harder to automate — NLP Engineer or Cloud Security Engineer?+
NLP Engineer has a lower AI automation risk (20% vs 28%). Based on Oxford Martin School and McKinsey 2023 analysis.