The AI job market in 2026 is maturing but still growing. After the explosive demand of 2023-2024 driven by ChatGPT and generative AI, the market has shifted from experimentation to production deployment. Companies are hiring not just for AI research, but for the infrastructure, operations, and product skills needed to ship AI products at scale.

AI Pulse analyzes 11,024 active job postings to surface the signals that matter: which skills are growing, which roles are emerging, and where compensation is heading. Our data comes from Indeed, LinkedIn, Greenhouse, Lever, and direct company career pages, refreshed weekly to reflect current market conditions.

What We Track

AI market intelligence showing trends, funding, and hiring velocity

Our market intelligence covers several dimensions: skills and tools (which technologies appear most frequently in job requirements), role distribution (the balance between different AI job categories), work arrangements (remote vs. hybrid vs. on-site), and salary trends (how compensation is moving across roles and locations).

Unlike salary surveys that rely on self-reported data from months ago, our insights come directly from active job postings. This gives you a real-time view of what employers are looking for and willing to pay, not what they were hiring for last quarter.

How Much of the Job Market Now Requires AI

Across 151,881 active postings in every field we track, 18.7% now require AI. Either the role is AI-native or the description calls for AI tools and skills.

45.1% of Engineering jobs now require AI, the most AI-saturated field we track.

Share of jobs requiring AI, by field

Engineering
45.1%
Product
37.1%
Data
33.6%
Marketing
22.1%
Legal
18.9%
Finance
15.2%
People
14.5%
Other
11.8%
Sales
11.8%
Operations
10.6%
Trend: AI requirement across all postings moved from 16.7% (2025-10) to 16.9% (2026-10), 0.2 pts up.

Top AI Tools & Frameworks

Most requested technologies in AI/ML job postings.

Python
2117 (19.2%)
Aws
1138 (10.3%)
Azure
920 (8.3%)
Rag
816 (7.4%)
Gcp
679 (6.2%)
Pytorch
592 (5.4%)
Kubernetes
507 (4.6%)
Claude
503 (4.6%)
Prompt Engineering
450 (4.1%)
Tensorflow
417 (3.8%)
Docker
400 (3.6%)
Openai
379 (3.4%)
Langchain
340 (3.1%)
Typescript
334 (3.0%)
Embeddings
259 (2.3%)
Key Insight: Python and PyTorch dominate, with LangChain emerging as the top LLM framework.

Job Categories

Distribution of AI roles by category.

AI/ML Engineer
8347 (75.7%)
AI Software Engineer
542 (4.9%)
AI Product Manager
505 (4.6%)
Data Scientist
443 (4.0%)
Research Engineer
254 (2.3%)
Research Scientist
217 (2.0%)
MLOps Engineer
172 (1.6%)
AI Architect
165 (1.5%)
AI Agent Developer
138 (1.3%)
Data Engineer
86 (0.8%)
AI Safety
51 (0.5%)
Prompt Engineer
42 (0.4%)
LLM Engineer
23 (0.2%)
AI Engineering Manager
23 (0.2%)
AI Consultant
15 (0.1%)

Remote Work Distribution

Work arrangement preferences in AI roles.

onsite
10244 (92.9%)
remote
687 (6.2%)
hybrid
93 (0.8%)

llm_providers

Claude
503 (4.6%)
Openai
379 (3.4%)
Gemini
232 (2.1%)
Anthropic
205 (1.9%)
Hugging Face
139 (1.3%)
Llama
58 (0.5%)
Mistral
20 (0.2%)
Cohere
6 (0.1%)

Proposals

Docusign
11 (0.1%)
Ironclad
4 (0.0%)
Signnow
1 (0.0%)
Concord
1 (0.0%)

Web_Personalization

Instapage
2 (0.0%)
Optimizely
1 (0.0%)

infrastructure

Aws
1138 (10.3%)
Azure
920 (8.3%)
Gcp
679 (6.2%)
Kubernetes
507 (4.6%)
Docker
400 (3.6%)
Bedrock
243 (2.2%)
Mlflow
170 (1.5%)
Vertex Ai
140 (1.3%)
Sagemaker
139 (1.3%)
Wandb
1 (0.0%)

languages

Python
2117 (19.2%)
Typescript
334 (3.0%)
Javascript
255 (2.3%)
Rust
70 (0.6%)
Golang
44 (0.4%)

techniques

Rag
816 (7.4%)
Prompt Engineering
450 (4.1%)
Embeddings
259 (2.3%)
Vector Search
135 (1.2%)
Rlhf
47 (0.4%)
Fine Tuning
19 (0.2%)
Chain Of Thought
1 (0.0%)

Product_Analytics

Amplitude
8 (0.1%)
Mixpanel
4 (0.0%)
Posthog
3 (0.0%)
Pendo
1 (0.0%)
Heap
1 (0.0%)

BI_Analytics

Power Bi
192 (1.7%)
Tableau
126 (1.1%)
Looker
33 (0.3%)
Metabase
1 (0.0%)

CRM_MidMarket

Hubspot
35 (0.3%)
Streak
3 (0.0%)
Copper
2 (0.0%)
Zoho Crm
2 (0.0%)
Pipedrive
2 (0.0%)
Nutshell
1 (0.0%)

CRM_Enterprise

Salesforce
166 (1.5%)
Dynamics 365
23 (0.2%)
Oracle Cx
1 (0.0%)

Lead_Routing

Workato
7 (0.1%)

Integration_iPaaS

N8N
44 (0.4%)
Zapier
32 (0.3%)
Mulesoft
12 (0.1%)
Boomi
5 (0.0%)
Make
2 (0.0%)
Celigo
1 (0.0%)

ml_frameworks

Pytorch
592 (5.4%)
Tensorflow
417 (3.8%)
Transformers
103 (0.9%)
Jax
83 (0.8%)
Keras
52 (0.5%)

llm_frameworks

Langchain
340 (3.1%)
Llamaindex
128 (1.2%)
Crewai
92 (0.8%)
Semantic Kernel
91 (0.8%)
Autogen
83 (0.8%)
Haystack
7 (0.1%)
Dspy
5 (0.0%)

RevOps_Data_Quality

Demandtools
23 (0.2%)

vector_databases

Pinecone
73 (0.7%)
Pgvector
50 (0.5%)
Weaviate
45 (0.4%)
Faiss
34 (0.3%)
Qdrant
20 (0.2%)
Milvus
19 (0.2%)
Chroma
10 (0.1%)

CPQ

Salesforce Cpq
2 (0.0%)
Dealhub Cpq
1 (0.0%)

Sales_Engagement_Growth

Instantly
10 (0.1%)
Apollo
9 (0.1%)
Smartlead
2 (0.0%)

Data_Providers

Zoominfo
8 (0.1%)
Linkedin Sales Navigator
6 (0.1%)
Seamless Ai
4 (0.0%)
Bombora
2 (0.0%)
Clearbit
1 (0.0%)

Data_Enrichment

Clay
12 (0.1%)

ABM_Platforms

6Sense
4 (0.0%)

Customer_Success

Catalyst
39 (0.4%)
Gainsight
3 (0.0%)
Churnzero
1 (0.0%)

Meeting_Scheduling

Calendly
2 (0.0%)
Acuity
1 (0.0%)

Sales_Enablement_Enterprise

Seismic
6 (0.1%)
Mindtickle
1 (0.0%)
Highspot
1 (0.0%)

Competitive_Intel

Semrush
15 (0.1%)

PLG_Tools

Appcues
1 (0.0%)
Walkme
1 (0.0%)

Demo_Automation

Walnut
11 (0.1%)
Arcade
1 (0.0%)

Revenue_Intelligence

Gong
7 (0.1%)
Clari
2 (0.0%)

Gifting_Direct_Mail

Postal
5 (0.0%)

Marketing_Automation_Enterprise

Marketo
5 (0.0%)
Eloqua
2 (0.0%)
Salesforce Marketing Cloud
1 (0.0%)

Marketing_Automation_Growth

Braze
2 (0.0%)
Klaviyo
2 (0.0%)
Iterable
2 (0.0%)
Mailchimp
1 (0.0%)

Review_Platforms

G2
10 (0.1%)
Capterra
2 (0.0%)

Sales_Engagement_Enterprise

Salesloft
3 (0.0%)

Partner_Channel

Reveal
23 (0.2%)

Visitor_Identification

Warmly
6 (0.1%)

Video_Prospecting

Loom
5 (0.0%)

Conversational_B2B

Chili Piper
1 (0.0%)
Intercom
1 (0.0%)

Chatbots

Cognigy
3 (0.0%)
Ada Support
1 (0.0%)

ABM_Advertising

Linkedin Marketing
1 (0.0%)
Influ2
1 (0.0%)

Reverse_ETL

Airbyte
2 (0.0%)
Fivetran
2 (0.0%)

SDR

Artisan
1 (0.0%)

ABM_Signals

Mutiny
1 (0.0%)
Common Room
1 (0.0%)

Digital_Sales_Rooms

Aligned
1 (0.0%)

Revenue_Operations

Aviso
1 (0.0%)

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How to Use This Data

Market intelligence is only valuable if you act on it. Here's how AI professionals use our data: Career planning: identify which skills to develop based on growing demand, not hype. Salary negotiations: use real benchmarks to anchor compensation discussions. Job search strategy: focus on roles and locations where demand exceeds supply.

2026 Market Outlook

Several trends are shaping the AI job market this year. Production over research: Companies that experimented with AI in 2023-2024 are now hiring for deployment and operations. MLOps, platform engineering, and AI infrastructure roles are growing faster than pure research positions. Specialization matters: Generalist "AI Engineer" roles are giving way to specialists like Prompt Engineers, LLM Engineers, ML Infrastructure Engineers, and AI Product Managers with distinct skill requirements.

Remote remains strong: Despite some companies pushing return-to-office, AI roles maintain higher remote availability than the broader tech market. Our data shows remote AI positions often pay within 5-10% of equivalent on-site roles in major metros. The tools stack is consolidating: After a period of framework proliferation, the market is converging on standard stacks. PyTorch for ML, LangChain for LLM orchestration, and cloud-native deployment.

Our Methodology

We aggregate job postings from Indeed, LinkedIn, Greenhouse, Lever, and company career pages. Each posting is enriched with structured data: job category, required skills, experience level, salary range (when disclosed), location, and remote work type. We update our dataset weekly and filter out duplicates, expired postings, and outliers. Our skill extraction uses both keyword matching and semantic analysis to capture tool mentions accurately.

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