Functional discipline.
AI Operations Roles.
Where AI meets production.
Source.
Most AI products fail in production, not in a notebook. AI operations is the discipline that keeps models reliable, fast, and not-bankrupting-the-company. MLOps, LLMOps, AIOps, AI platform, AI infrastructure, observability, vector and retrieval engineering, GPU capacity planning. Compensation tracks operational impact: when the model goes down, the company goes down. Engineers who have actually run a real AI system at scale are scarce in 2026 and expensive. Roles below are sorted by base salary.
Roles in ai operations roles.
Top cities.
Median ai operations roles salary across the top U.S. metros for AI compensation. Multiplier reflects local cost of living relative to the national median.
San Francisco, CA
$180K
+35% vs. national
New York, NY
$170K
+28% vs. national
Seattle, WA
$165K
+24% vs. national
Boston, MA
$162K
+22% vs. national
Austin, TX
$137K
+3% vs. national
Denver, CO
$144K
+8% vs. national
Los Angeles, CA
$157K
+18% vs. national
Chicago, IL
$142K
+7% vs. national
Atlanta, GA
$136K
+2% vs. national
Washington DC, DC
$166K
+25% vs. national
Common questions.
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Where AI meets law and policy.
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Where AI meets adversaries.
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Where AI meets the physical world.
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Where AI meets the consumer.
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Where AI meets craft.
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Where AI meets the C-suite.
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Where AI meets the frontier.
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Where AI meets the roadmap.
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Where AI meets the interface.
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Where AI meets the codebase.
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