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 3,708 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 183,507 active postings in every field we track, 15.2% now require AI. Either the role is AI-native or the description calls for AI tools and skills.

40.2% of Engineering jobs now require AI, the most AI-saturated field we track.

Share of jobs requiring AI, by field

Engineering
40.2%
Product
30.7%
Data
25.4%
Marketing
20.2%
Legal
14.8%
Finance
13.5%
People
11.8%
Sales
10.8%
Other
8.9%
Operations
8.5%
Trend: AI requirement across all postings moved from 66.7% (2025-06) to 14.8% (2026-07), 51.9 pts down.

Top AI Tools & Frameworks

Most requested technologies in AI/ML job postings.

Python
1890 (51.0%)
Aws
1103 (29.7%)
Azure
877 (23.7%)
Rag
855 (23.1%)
Gcp
631 (17.0%)
Prompt Engineering
560 (15.1%)
Pytorch
545 (14.7%)
Claude
498 (13.4%)
Kubernetes
441 (11.9%)
Tensorflow
397 (10.7%)
Openai
392 (10.6%)
Langchain
385 (10.4%)
Docker
374 (10.1%)
Typescript
255 (6.9%)
Anthropic
233 (6.3%)
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
2605 (70.3%)
Data Scientist
310 (8.4%)
AI Software Engineer
259 (7.0%)
AI Product Manager
181 (4.9%)
Research Scientist
104 (2.8%)
Research Engineer
65 (1.8%)
AI Architect
47 (1.3%)
AI Agent Developer
37 (1.0%)
Data Engineer
30 (0.8%)
MLOps Engineer
30 (0.8%)
AI Consultant
9 (0.2%)
AI Engineering Manager
9 (0.2%)
Prompt Engineer
8 (0.2%)
AI Safety
8 (0.2%)
LLM Engineer
5 (0.1%)

Remote Work Distribution

Work arrangement preferences in AI roles.

onsite
3180 (85.8%)
remote
508 (13.7%)
hybrid
20 (0.5%)

languages

Python
1890 (51.0%)
Typescript
255 (6.9%)
Javascript
230 (6.2%)
Golang
61 (1.6%)
Rust
55 (1.5%)

Sales_Engagement_Growth

Instantly
12 (0.3%)
Orum
2 (0.1%)
Apollo
2 (0.1%)

CRM_Enterprise

Salesforce
148 (4.0%)
Dynamics 365
14 (0.4%)

BI_Analytics

Power Bi
188 (5.1%)
Tableau
157 (4.2%)
Looker
38 (1.0%)
Mode
3 (0.1%)
Thoughtspot
2 (0.1%)
Domo
2 (0.1%)
Sisense
1 (0.0%)

techniques

Rag
855 (23.1%)
Prompt Engineering
560 (15.1%)
Embeddings
219 (5.9%)
Vector Search
114 (3.1%)
Rlhf
65 (1.8%)
Fine Tuning
24 (0.6%)
Chain Of Thought
2 (0.1%)

infrastructure

Aws
1103 (29.7%)
Azure
877 (23.7%)
Gcp
631 (17.0%)
Kubernetes
441 (11.9%)
Docker
374 (10.1%)
Bedrock
222 (6.0%)
Sagemaker
180 (4.9%)
Vertex Ai
176 (4.7%)
Mlflow
162 (4.4%)
Wandb
2 (0.1%)

llm_providers

Claude
498 (13.4%)
Openai
392 (10.6%)
Anthropic
233 (6.3%)
Gemini
212 (5.7%)
Hugging Face
162 (4.4%)
Llama
49 (1.3%)
Mistral
24 (0.6%)
Cohere
6 (0.2%)

CRM_MidMarket

Hubspot
25 (0.7%)
Copper
4 (0.1%)
Freshsales
4 (0.1%)
Zoho Crm
3 (0.1%)
Pipedrive
1 (0.0%)
Monday Sales
1 (0.0%)

Data_Providers

Seamless Ai
4 (0.1%)
Zoominfo
2 (0.1%)
Contactout
1 (0.0%)

Customer_Success

Catalyst
46 (1.2%)
Gainsight
3 (0.1%)
Totango
1 (0.0%)

llm_frameworks

Langchain
385 (10.4%)
Llamaindex
147 (4.0%)
Autogen
121 (3.3%)
Crewai
119 (3.2%)
Semantic Kernel
105 (2.8%)
Haystack
14 (0.4%)
Dspy
9 (0.2%)

Marketing_Automation_Enterprise

Marketo
5 (0.1%)
Hubspot Marketing
4 (0.1%)
Eloqua
2 (0.1%)
Salesforce Marketing Cloud
1 (0.0%)

vector_databases

Pinecone
73 (2.0%)
Weaviate
50 (1.3%)
Pgvector
40 (1.1%)
Faiss
37 (1.0%)
Milvus
21 (0.6%)
Chroma
18 (0.5%)
Qdrant
16 (0.4%)

Chatbots

Drift Ai
65 (1.8%)
Intercom Fin
1 (0.0%)
Cognigy
1 (0.0%)

ml_frameworks

Pytorch
545 (14.7%)
Tensorflow
397 (10.7%)
Transformers
88 (2.4%)
Jax
75 (2.0%)
Keras
28 (0.8%)

Integration_iPaaS

N8N
43 (1.2%)
Zapier
41 (1.1%)
Mulesoft
16 (0.4%)
Workato Ipaas
13 (0.4%)
Make
5 (0.1%)
Boomi
2 (0.1%)
Snaplogic
1 (0.0%)
Tray
1 (0.0%)

Video_Prospecting

Loom
10 (0.3%)

Sales_Enablement_Enterprise

Seismic
4 (0.1%)
Highspot
2 (0.1%)

Competitive_Intel

Semrush
6 (0.2%)
Crayon
2 (0.1%)

Proposals

Docusign
5 (0.1%)
Ironclad
4 (0.1%)
Concord
1 (0.0%)
Adobe Sign
1 (0.0%)
Pandadoc
1 (0.0%)
Signnow
1 (0.0%)

RevOps_Data_Quality

Demandtools
20 (0.5%)

Gifting_Direct_Mail

Postal
5 (0.1%)

Reverse_ETL

Fivetran
8 (0.2%)
Airbyte
3 (0.1%)

Product_Analytics

Amplitude
6 (0.2%)
Mixpanel
2 (0.1%)
Pendo
2 (0.1%)
Logrocket
2 (0.1%)
Posthog
1 (0.0%)
Heap
1 (0.0%)
Fullstory
1 (0.0%)

Digital_Sales_Rooms

Aligned
1 (0.0%)

Marketing_Automation_Growth

Braze
6 (0.2%)
Mailchimp
3 (0.1%)
Drip
2 (0.1%)
Klaviyo
1 (0.0%)
Customer Io
1 (0.0%)

Review_Platforms

G2
13 (0.4%)
Trustpilot
1 (0.0%)

Lead_Routing

Workato
13 (0.4%)
Tray Io
1 (0.0%)

Conversational_B2B

Default Gtm
2 (0.1%)
Intercom
2 (0.1%)
Qualified
1 (0.0%)

Partner_Channel

Reveal
38 (1.0%)

Revenue_Intelligence

Gong
6 (0.2%)
Clari
2 (0.1%)

Sales_Training

Second Nature Training
1 (0.0%)

PLG_Tools

Pendo Plg
2 (0.1%)
Chameleon
2 (0.1%)

Data_Enrichment

Clay
2 (0.1%)

Demo_Automation

Walnut
11 (0.3%)

Revenue_Operations

Clari Forecast
2 (0.1%)

Visitor_Identification

Warmly
5 (0.1%)

Web_Personalization

Optimizely
3 (0.1%)
Instapage
1 (0.0%)

ABM_Advertising

Linkedin Marketing
1 (0.0%)

CPQ

Salesforce Cpq
1 (0.0%)

ABM_Platforms

6Sense
1 (0.0%)

Sales_Engagement_Enterprise

Outreach Io
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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