Technology

Software Engineer

🇺🇸 US 🇬🇧 UK 🇦🇺 AU 🇨🇦 CA

Live job postings

134,032

as of 29 Jun 2026

Demand index

2.44%

% of all job postings

Median salary

$140k

$140,000

Salary range

$120k – $140k

$120,000 – $140,000

Trend analysis & outlook

The software engineer job market in the US shows a clear seasonal peak in spring 2026 (over 164,000 postings in May), followed by a sharp drop to 130,630 in June, likely reflecting normal graduation-driven hiring cycles and mid-year budget resets. The hot index surged from 71 to 100 between July 2025 and February 2026, indicating intense competition for talent that has since cooled to 62 in May 2026, suggesting market normalization. Median salary sits at $140,000, which is healthy but pressured by the rise of AI tools that could reduce demand for entry-level coding. The recent news about Nvidia's AI laptop chips and OpenAI's Codex on Bedrock signals a near-term shift requiring engineers to master AI integration and hardware-aware development. Over the next 6–12 months, hiring will likely stabilize around 150,000–160,000 monthly postings, with the largest demand for senior engineers skilled in AI/ML pipeline construction and system design, while junior generalists may face stiffer competition.

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Salary distribution

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Core skills employers ask for

System DesignCloud Computing (AWS/Azure/GCP)AI/ML Integration & Prompt EngineeringPythonJavaScript/TypeScriptCI/CD & DevOps PracticesDatabase Management (SQL & NoSQL)RESTful & GraphQL API DesignJava (for enterprise environments)Cybersecurity FundamentalsContainerization (Docker/Kubernetes)Agile/Scrum Methodologies

AI impact on this career

AI is rapidly automating code generation, testing, and debugging, shifting the software engineer's role from writing routine code to designing system architectures and curating AI outputs. Engineers who master integrating AI coding agents like Codex into their workflows will be more productive, but junior roles focused on basic implementation are shrinking. The launch of specialized AI chips (e.g., Nvidia's laptop chips) means engineers must understand hardware-aware software optimization, especially for edge AI deployment. Early-career workers are being advised to gain broad exposure across companies and tools, as specialization in a single stack is riskier when AI can rapidly acquire that knowledge. Overall, AI is compressing the time from concept to deployment, placing a premium on problem definition, prompt engineering, and ethical oversight.

What's happening in the market

Hardware advances like Nvidia's new Windows laptop chip will drive demand for software engineers who can optimize for on-device AI, shifting focus from pure cloud to hybrid edge strategies. The availability of OpenAI's GPT-5.5, GPT-5.4, and Codex on Amazon Bedrock means engineers are expected to integrate powerful AI coding agents into their pipelines, amplifying productivity and changing skill requirements toward prompt engineering and architecture. Ongoing Java ecosystem updates (JDK 27, Quarkus, Hibernate) indicate that enterprise Java remains relevant, but engineers must continuously update their core language knowledge to stay current.

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