Top 10 Most In-Demand AI Skills and Salary Ranges in 2026

By Elton Chan, Co-Founder September 11, 2026 9 min read

Most In-Demand AI Skills and Salary Ranges. Top 10 Most In-Demand AI Skills and Salary Ranges in 2026, by Second Talent.

TL;DR: Agent orchestration is the best-paid AI skill in 2026: US developers who build with LangGraph earn a median $209,500, against $154,765 for all US developers in Stack Overflow's 2025 survey. LLM app development, managed cloud AI platforms and vector search follow, each at $190,000 or more.

US developers whose job title is AI/ML engineer earn a median $189,000, about $34,000 more than the average American developer, with four fewer years of experience.

Demand is still climbing: Lightcast counts 2.5% of US job postings asking for AI skills, up 55% in a year.

Top 10 Most In-Demand AI Skills and Their Salaries (2026)

Rank	Skill	Tool measured	US median pay	US respondents
1	Agent orchestration	LangGraph	$209,500	58
2	LLM app development	LangChain	$200,000	149
3	Managed cloud AI platforms	Amazon Bedrock Agents	$200,000	83
4	Vector search	pgvector	$191,500	80
5	Data platforms for AI	Snowflake	$190,000	280
6	AI coding agents	Claude Code	$183,500	446
7	MLOps and model infrastructure	Kubernetes	$180,000	1,032
8	Open-weight models	Ollama	$176,800	183
9	Python	Python	$160,000	2,254
10	Data science	Data scientist job title	$137,000	54

Our calculation from Stack Overflow’s 2025 survey response data: employed US professional developers who worked with each tool in the past year. All US developers: $154,765.

How the list is built. Each skill is backed by job-posting or usage data, and priced from the public response data of the 2025 Stack Overflow Developer Survey: the median pay of US developers who work with its main tool. People using these tools tend to be more experienced, so the figures show where pay is highest, not what learning a tool adds.

Key takeaways

1Jobs that require AI skills pay a 62% wage premium, according to PwC’s 2026 study of more than a billion job ads.
2Singapore has the highest share of job postings asking for AI skills, at 4.77%, ahead of Hong Kong and the US.
3US developers who use AI agents daily earn $175,000, against $141,000 for those with no plans to, and the gap holds among seniors.
4Data scientists are the one AI role that earns less than the average US developer.

The 10 AI Skills, Ranked by Pay

1. Agent orchestration

$209,500 US median, LangGraph0.23% of US job postings280% growth in a year

Agentic AI skills went from 0.06% of US job postings in 2024 to 0.23% in 2025, nearly 90,000 postings, in Lightcast’s data for the Stanford AI Index 2026. Lightcast added agentic AI as its tenth AI skill cluster this year.

The work is building systems where a model plans steps, calls tools and hands tasks to other agents.

Developers who use LangGraph, the agent framework from the LangChain team, earn a median $209,500 in the US, and the middle half earn $160,000 to $271,250, the highest band in the list.

Range chart of the middle half of US developer pay, 25th to 75th percentile, by AI skill, from Stack Overflow 2025 survey data: agent orchestration $160K to $271K, LLM app development $150K to $250K, cloud AI platforms $133K to $250K, vector search $140K to $250K, data platforms $150K to $245K, AI coding agents $140K to $250K, MLOps $144K to $230K, open-weight models $137K to $233K, Python $118K to $210K, data science $103K to $198K.

The skill is still rare. Only 13% of AI/ML engineers in the survey use LangGraph, and Microsoft’s AutoGen and CrewAI have too few US users to price, at 38 and 22.

It also pays without seniority. LangGraph users have a median of 12 years’ experience, three fewer than LangChain users, yet they earn $9,500 more.

Agents also need a way to reach company data, and 1,456 respondents already use GitHub’s MCP server, which connects agents to GitHub through the Model Context Protocol. Its US users earn a median $180,000.

2. LLM app development

$200,000 US median, LangChain4x LLM job postings in 202420% of AI/ML engineers use LangChain

US job postings asking for large language modeling rose from 5,000 in 2023 to 20,000 in 2024, and generative AI postings from 16,000 to more than 66,000, according to Lightcast’s figures for the 2025 AI Index.

Among AI/ML engineers in the survey, LangChain is the most-used framework for building LLM apps. Its US users earn a median $200,000, with the middle half at $150,000 to $250,000, and LlamaIndex users earn $174,000.

The everyday stack still comes first:

Bar chart of the share of 278 employed AI/ML engineers worldwide who work with each tool, from Stack Overflow 2025 survey data: Python 89%, Docker 71%, AWS 47%, Kubernetes 33%, Google Cloud 29%, LangChain 20%, Ollama 15%, LangGraph 13%, ChromaDB 10%, pgvector 9%.

Prompt engineering on its own is a smaller market. Postings that named it rose from 1,400 to about 6,300 over the same year, under a third of the demand for large language modeling.

3. Managed cloud AI platforms

$200,000 Amazon Bedrock Agents$181,954 Google Vertex AI47% of AI/ML engineers use AWS

Developers who build on Amazon Bedrock Agents earn a median $200,000 in the US, level with LangChain, and Google Vertex AI users earn $181,954. Bedrock’s band starts lower, at $132,500, and Vertex AI’s runs from $130,000 to $250,000.

OpenRouter, which sends requests to whichever model provider fits, has 61 US users earning a median $185,000.

AWS is the cloud AI/ML engineers use most, at 47%, with Google Cloud at 29% and Microsoft Azure at 23%.

Azure users as a whole earn less, a median $145,500 in the US, but that figure covers all Azure developers, not only those building with its AI services.

4. Vector search

$191,500 US median, pgvector611 pgvector users vs 380 for Pinecone10% of AI/ML engineers use ChromaDB

The vector store developers reach for most is one that lives inside Postgres. pgvector, a Postgres extension, has 611 users in the survey against 380 for Pinecone, a standalone vector database.

Vector search is how an AI system finds the right documents before it answers, the retrieval step in retrieval-augmented generation. US developers using pgvector earn a median $191,500, and the middle half $140,000 to $250,000.

Among AI/ML engineers, ChromaDB (10%) and pgvector (9%) lead, while Pinecone, Qdrant and Weaviate have too few US users to price.

5. Data platforms for AI

$190,000 Snowflake and Databricks$180,000 BigQuery$160,000 data engineers overall

Snowflake and Databricks users earn the same US median, $190,000, which is $30,000 above data engineers as a group. BigQuery users earn $180,000, and Amazon Redshift users the same.

The faster analytical engines pay more still: Clickhouse users earn a median $198,000 and DuckDB users $185,000, though both samples are smaller, at 79 and 129.

Models are only as useful as the data pipelines behind them, and these platforms are where companies keep the data they train on and retrieve from.

Databricks has the higher floor: its middle half starts at $155,500, against $150,000 for Snowflake. Among AI/ML engineers, 13% work with BigQuery and 10% with Databricks.

6. AI coding agents

$183,500 US median, Claude Code$34,000 daily-use gap446 US respondents

US developers who use AI agents at work every day earn a median $175,000. Those with no plans to use them earn $141,000.

Column chart of median US developer pay by how often they use AI agents at work, from Stack Overflow 2025 survey data: no plans $141K, plan to $160K, autocomplete only $160K, monthly or less $165K, weekly $175K, daily $175K.

Experience explains part of that, since agent users are more senior. Among US developers with ten or more years, the gap narrows but holds: $187,000 for daily users against $156,000 for non-users.

By tool, Claude Code users earn $183,500, Cursor users $180,000 and GitHub Copilot agent users $175,000.

AI/ML engineers adopted agents faster than other developers:

Stacked bar chart of AI agent use at work in 2025, from Stack Overflow survey data: AI/ML engineers 47% use agents, 17% autocomplete only, 36% not yet; all professional developers 32% use agents, 14% autocomplete only, 54% not yet.

A quarter of AI/ML engineers use agents daily, against 15% of professional developers overall. Our comparison of AI coding agents covers the tools themselves.

7. MLOps and model infrastructure

$180,000 US median, Kubernetes71% of AI/ML engineers use Docker$195,500 cloud infrastructure engineers

Seven in ten AI/ML engineers use Docker and a third use Kubernetes, which makes deployment the most widespread skill in the list after Python.

Getting a model into production, keeping it running and scaling it is the job of an MLOps engineer.

Kubernetes users earn a median $180,000 in the US, Terraform users $181,000 and Datadog users $188,500.

The infrastructure job titles pay even more: cloud infrastructure engineers earn a median $195,500, the best-paid job title in our role comparison, and DevOps engineers $166,000.

Watching models in production is the newest part of the job. General monitoring tools are well established, with Grafana and Prometheus users earning $182,500.

LLM-specific observability tools are still small: LangSmith has 337 users in the survey and Langfuse 239, too few in the US to price.

8. Open-weight models

$176,800 US median, Ollama1,921 Ollama users, most of any agent tool32% of AI/ML engineers use Llama

Ollama, which runs open models on a developer’s own machine, is the most-used agent tool in the survey. It has 1,921 users, against 1,239 for LangChain.

Running models on a company’s own hardware matters where data cannot leave the building or API costs add up. US Ollama users earn a median $176,800.

Among AI/ML engineers, 32% have worked with Meta’s Llama models, 25% with DeepSeek’s reasoning models and 16% with Mistral’s.

9. Python

258,674 US job postings89% of AI/ML engineers$160,000 US median

Python was the most in-demand specialized skill in Lightcast’s 2026 data, appearing in 258,674 US job postings, up nearly 30% on 2024. Nine in ten AI/ML engineers use it.

That ubiquity is why it pays the least of the tools in this list. US Python developers earn a median $160,000, only about $5,000 above developers as a whole, because Python also runs scripts, web back ends and data analysis.

It is the entry requirement for AI work, and the premium comes from the tools developers add on top of it.

The languages around AI infrastructure pay more than Python does. US developers who write Go earn a median $180,000, Rust developers $173,500 and developers using Scala, the language Apache Spark is written in, $200,000.

10. Data science

$137,000 US data scientists$52,000 below AI/ML engineers$143,000 R users

Data scientists are the one AI-adjacent role that earns less than the average US developer, a median $137,000 against $154,765. AI/ML engineers, who build and ship models rather than analyze data, earn $189,000.

Dot plot of median developer pay by role in the United States and worldwide, from Stack Overflow 2025 survey data: cloud infrastructure engineer $196K and $108K, AI/ML engineer $189K and $89K, data engineer $160K and $81K, all developers $155K and $80K, data scientist $137K and $87K.

The US data scientist band is wide, from $103,130 to $197,500, and its median experience is nine years, the same as AI/ML engineers.

The gap is a US one. Worldwide, AI/ML engineers and data scientists earn almost the same, $88,960 and $87,011.

Classic tooling follows the same pattern in the US: R users earn $143,000 and Jupyter users $165,000, both below every tool in entries one to eight.

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FAQs

Do AI skills raise pay outside tech jobs?

Yes. In Lightcast’s 2025 study of 1.3 billion postings, jobs listing AI skills offered 28% more, nearly $18,000, and 51% of them were outside IT.

Why do PwC and Lightcast report different AI pay premiums?

They use different samples and years. PwC’s 62% comes from job ads in 27 countries, published in June 2026, and Lightcast’s 28% from 1.3 billion postings in 2025. Neither tells you what one new skill adds to one person’s pay.

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Written by

Elton Chan

Elton Chan is the Co-Founder of Second Talent, a solution that connects global tech leaders with top-tier tech talent across Asia. He specializes in talent solutions and has led Second Talent’s rapid growth since 2024, helping scale its network to over 100,000 pre-vetted developers and earning industry recognition as the #1 in the Global Hiring category on G2. A long-time entrepreneur with deep roots in digital transformation, Elton previously co-founded Branch8, a Y Combinator–backed e-commerce technology firm, and served as the Founding Chairman of HKEBA, a leading Asia-focused business association driving innovation, digital education, and cross-border collaboration. His work bridges technology, talent, and business strategy to shape how companies scale in an increasingly remote and digital world.