Fine-tuning and RAG frequently appear together in AI job postings, with 287 current openings requiring both skills. The most common role for this combination is AI/ML Engineer. Jobs requiring both skills pay up to $226K on average. Below you'll find detailed salary data, hiring companies, and related skill combinations.
The LLM ecosystem increasingly requires combining tools like Fine-tuning and RAG. As AI applications grow more complex — multi-model pipelines, agent frameworks, and retrieval-augmented systems — engineers need fluency across multiple LLM tools. The 287 postings requiring both reflect this growing complexity.
Top Roles Requiring Fine-tuning + RAG
AI/ML Engineer115 jobs
AI Product Manager61 jobs
Research Scientist40 jobs
Prompt Engineer26 jobs
AI Software Engineer13 jobs
LLM Engineer12 jobs
Career Impact
Professionals who combine Fine-tuning and RAG earn a median salary ceiling of
$226K, compared to $228K for Fine-tuning alone and
$224K for RAG alone. This 0% discount
reflects the salary ceiling is roughly equivalent whether you specialize in one skill or combine both, suggesting the market values either path equally.
Based on our analysis of current AI job postings, 287 positions require both Fine-tuning and RAG skills. The most common role for this combination is AI/ML Engineer.
Jobs requiring both Fine-tuning and RAG pay an average of $140K to $226K based on 250 postings with disclosed compensation.
Jobs requiring both Fine-tuning and RAG pay $226K on average (max), compared to $228K for Fine-tuning alone and $224K for RAG alone. That represents a 0% discount for having both skills.
The most common roles requiring both Fine-tuning and RAG are: AI/ML Engineer, AI Product Manager, Research Scientist, Prompt Engineer. These positions typically involve building production AI systems that leverage both technologies.
Data Source: Analysis based on 1,969 AI job postings collected and verified by AI Market Pulse. Data reflects active job listings as of March 2026. Salary figures represent posted compensation ranges and may not include equity, bonuses, or other benefits.
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Methodology
Skill co-occurrence data is derived from 287 job postings that list both Fine-tuning and RAG
as required or preferred skills. Salary data includes only postings with disclosed compensation ranges.
Data is updated weekly from major job boards and company career pages.
