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 4,317 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 195,452 active postings in every field we track, 16.9% now require AI. Either the role is AI-native or the description calls for AI tools and skills.

43.5% of Engineering jobs now require AI, the most AI-saturated field we track.

Share of jobs requiring AI, by field

Engineering
43.5%
Product
33.4%
Data
27.0%
Marketing
22.7%
Finance
15.1%
Legal
14.1%
People
12.3%
Sales
11.5%
Other
10.3%
Operations
9.0%
Trend: AI requirement across all postings moved from 5.9% (2025-07) to 16.4% (2026-08), 10.5 pts up.

Top AI Tools & Frameworks

Most requested technologies in AI/ML job postings.

Python
2249 (52.1%)
Aws
1224 (28.4%)
Azure
938 (21.7%)
Rag
915 (21.2%)
Gcp
660 (15.3%)
Pytorch
640 (14.8%)
Prompt Engineering
624 (14.5%)
Kubernetes
559 (12.9%)
Tensorflow
510 (11.8%)
Claude
497 (11.5%)
Docker
451 (10.4%)
Openai
421 (9.8%)
Langchain
372 (8.6%)
Typescript
308 (7.1%)
Embeddings
296 (6.9%)
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
3004 (69.6%)
Data Scientist
345 (8.0%)
AI Software Engineer
309 (7.2%)
AI Product Manager
183 (4.2%)
Research Scientist
169 (3.9%)
Research Engineer
82 (1.9%)
Data Engineer
49 (1.1%)
AI Agent Developer
44 (1.0%)
AI Architect
41 (0.9%)
MLOps Engineer
41 (0.9%)
AI Engineering Manager
19 (0.4%)
AI Safety
11 (0.3%)
LLM Engineer
10 (0.2%)
Prompt Engineer
5 (0.1%)
AI Consultant
5 (0.1%)

Remote Work Distribution

Work arrangement preferences in AI roles.

onsite
3657 (84.7%)
remote
635 (14.7%)
hybrid
25 (0.6%)

llm_providers

Claude
497 (11.5%)
Openai
421 (9.8%)
Anthropic
239 (5.5%)
Gemini
199 (4.6%)
Hugging Face
132 (3.1%)
Llama
66 (1.5%)
Mistral
39 (0.9%)
Cohere
11 (0.3%)

techniques

Rag
915 (21.2%)
Prompt Engineering
624 (14.5%)
Embeddings
296 (6.9%)
Vector Search
156 (3.6%)
Rlhf
56 (1.3%)
Fine Tuning
24 (0.6%)
Chain Of Thought
2 (0.0%)

languages

Python
2249 (52.1%)
Typescript
308 (7.1%)
Javascript
267 (6.2%)
Rust
52 (1.2%)
Golang
36 (0.8%)

Intent_Data

Foundry Intent
1 (0.0%)

ml_frameworks

Pytorch
640 (14.8%)
Tensorflow
510 (11.8%)
Transformers
111 (2.6%)
Jax
93 (2.2%)
Keras
39 (0.9%)

infrastructure

Aws
1224 (28.4%)
Azure
938 (21.7%)
Gcp
660 (15.3%)
Kubernetes
559 (12.9%)
Docker
451 (10.4%)
Bedrock
263 (6.1%)
Sagemaker
194 (4.5%)
Vertex Ai
187 (4.3%)
Mlflow
184 (4.3%)

Lead_Routing

Workato
15 (0.3%)
Distribution Engine
1 (0.0%)

Integration_iPaaS

N8N
50 (1.2%)
Zapier
37 (0.9%)
Mulesoft
16 (0.4%)
Workato Ipaas
15 (0.3%)
Boomi
7 (0.2%)
Make
3 (0.1%)
Tray
2 (0.0%)
Snaplogic
1 (0.0%)
Celigo
1 (0.0%)

CRM_Enterprise

Salesforce
149 (3.5%)
Dynamics 365
24 (0.6%)

CRM_MidMarket

Hubspot
28 (0.6%)
Copper
3 (0.1%)
Keap
1 (0.0%)
Freshsales
1 (0.0%)
Monday Sales
1 (0.0%)
Zoho Crm
1 (0.0%)
Pipedrive
1 (0.0%)
Streak
1 (0.0%)

BI_Analytics

Power Bi
195 (4.5%)
Tableau
146 (3.4%)
Looker
55 (1.3%)
Domo
5 (0.1%)
Mode
3 (0.1%)
Thoughtspot
2 (0.0%)
Metabase
2 (0.0%)

llm_frameworks

Langchain
372 (8.6%)
Llamaindex
140 (3.2%)
Crewai
129 (3.0%)
Autogen
116 (2.7%)
Semantic Kernel
87 (2.0%)
Dspy
8 (0.2%)
Haystack
2 (0.0%)

vector_databases

Pinecone
97 (2.2%)
Weaviate
68 (1.6%)
Pgvector
62 (1.4%)
Faiss
33 (0.8%)
Milvus
32 (0.7%)
Qdrant
21 (0.5%)
Chroma
13 (0.3%)

Marketing_Automation_Growth

Mailchimp
8 (0.2%)
Braze
6 (0.1%)
Klaviyo
3 (0.1%)
Customer Io
1 (0.0%)
Iterable
1 (0.0%)
Activecampaign
1 (0.0%)

Partner_Channel

Reveal
26 (0.6%)
Partnerstack
1 (0.0%)
Impartner
1 (0.0%)

Customer_Success

Catalyst
37 (0.9%)
Gainsight
5 (0.1%)
Planhat
1 (0.0%)

RevOps_Data_Quality

Demandtools
22 (0.5%)
Openprise
1 (0.0%)

ABM_Platforms

6Sense
4 (0.1%)
Demandbase
2 (0.0%)

Data_Providers

Seamless Ai
4 (0.1%)
Zoominfo
2 (0.0%)
Linkedin Sales Navigator
1 (0.0%)

Chatbots

Drift Ai
75 (1.7%)

Product_Analytics

Mixpanel
6 (0.1%)
Amplitude
4 (0.1%)
Posthog
2 (0.0%)
Pendo
1 (0.0%)

Data_Enrichment

Clay
9 (0.2%)

ABM_Signals

Common Room
1 (0.0%)

Marketing_Automation_Enterprise

Salesforce Marketing Cloud
9 (0.2%)
Marketo
8 (0.2%)
Hubspot Marketing
7 (0.2%)
Eloqua
2 (0.0%)

Video_Prospecting

Loom
4 (0.1%)

Competitive_Intel

Semrush
10 (0.2%)

Reverse_ETL

Fivetran
7 (0.2%)
Census Data
2 (0.0%)
Airbyte
2 (0.0%)
Hightouch
2 (0.0%)

Conversational_B2B

Intercom
3 (0.1%)
Hubspot Conversations
1 (0.0%)

Revenue_Intelligence

Gong
10 (0.2%)
Fathom
10 (0.2%)
Fireflies
9 (0.2%)
Otter Ai
9 (0.2%)
Clari
4 (0.1%)

Sales_Training

Second Nature Training
3 (0.1%)
Mindtickle Training
2 (0.0%)

Sales_Engagement_Growth

Instantly
10 (0.2%)
Apollo
4 (0.1%)
Reply Io
1 (0.0%)

Revenue_Operations

Atrium
1 (0.0%)
Aviso
1 (0.0%)

Sales_Enablement_Enterprise

Seismic
4 (0.1%)
Mindtickle
2 (0.0%)
Highspot
2 (0.0%)
Showpad
1 (0.0%)

Review_Platforms

G2
10 (0.2%)
Trustradius
1 (0.0%)

Demo_Automation

Walnut
11 (0.3%)
Arcade
4 (0.1%)

Proposals

Docusign
6 (0.1%)
Ironclad
2 (0.0%)
Concord
2 (0.0%)

Digital_Sales_Rooms

Aligned
2 (0.0%)

Gifting_Direct_Mail

Postal
7 (0.2%)

PLG_Tools

Walkme
3 (0.1%)
Chameleon
2 (0.0%)
Pendo Plg
1 (0.0%)

ABM_Advertising

Linkedin Marketing
1 (0.0%)

Visitor_Identification

Warmly
1 (0.0%)

Meeting_Scheduling

Calendly
1 (0.0%)

Sales_Compensation

Captivateiq
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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