Global insights on Software Engineering, AI and Devops job openings - May 2026
Total: 119,717, Remote: 10,232, On-site: 109,485.
Specializations
The job market for tech professionals displays strong demand across core software disciplines, with business software applications and general software engineering roles leading the field. While specialized areas such as machine learning and AI engineering, as well as full-stack and backend development, offer significant opportunities, they have lower but still substantial representation. Java remains a prominent specialization, both in general software engineering and particularly in backend development. Roles in software quality assurance and solution architecture are also well represented, reflecting the continued need for high standards in software delivery and robust system design. In terms of specializations, candidates with expertise in Java, machine learning, full-stack, and backend engineering will find a broad but slightly more focused range of opportunities compared to the larger pools in general business and software engineering. Demand for both engineering and QA/testing talent is high, indicating that organizations are prioritizing both innovation and reliable software performance.
- business-software-applications: 28,213
- software-engineering: 22,621
- machine-learning-and-ai-engineering: 10,387
- full-stack-software-engineering: 7,939
- backend-engineer: 7,592
- java-software-engineering: 6,923
- frontend-software-engineering: 5,845
- software-quality-assurance-and-testing: 5,836
- solution-architecture: 5,296
- java-backend-development: 4,886
In Demand Skills
The most in-demand skills for tech roles are centered around continuous integration and deployment practices, cloud platforms, modern programming languages, DevOps, and container orchestration tools. CI/CD stands out as the top requirement, closely followed by expertise in Python and leading cloud providers such as AWS and Azure. Kubernetes and Docker signal a strong emphasis on scalable, cloud-native infrastructure, while Java, JavaScript, and React reflect the ongoing need for versatile application development capabilities. Employers also place a premium on familiarity with modern development methodologies (like microservices), infrastructure-as-code (Terraform), and proficiency in both relational databases (SQL) and distributed systems, highlighting the multidisciplinary nature expected of today’s engineers.
- CI/CD: 21,887
- Spring: 4,787
- Python: 18,582
- PostgreSQL: 4,517
- AWS: 17,150
- Node.js: 4,087
- DevOps: 14,796
- Angular: 4,030
- Java: 14,490
- .NET: 3,932
- Azure: 13,513
- Android: 3,785
- Kubernetes: 12,023
- SRE: 3,661
- SQL: 11,753
- Kafka: 3,636
- GCP: 11,693
- CSS: 3,525
- React: 9,514
- iOS: 3,396
- JavaScript: 9,495
- Spring Boot: 3,348
- Docker: 8,941
- HTML: 3,325
- TypeScript: 7,542
- System Design: 3,168
- Microservices: 7,311
- PyTorch: 3,137
- Linux: 7,257
- GitHub Actions: 2,991
- REST API: 6,477
- Ansible: 2,785
- Terraform: 6,054
- NoSQL: 2,630
- Distributed Systems: 5,750
- TensorFlow: 2,309
- Jenkins: 5,691
- MySQL: 2,239
- Data Analysis: 5,353
- Bash: 2,174
Ai Skill Signals
AI skill signals in the job market are robust, with generic AI expertise being highly prevalent across roles. Interest and demand are rapidly growing for specialized skills such as LLMs and generative AI, reflecting industry momentum. Knowledge of emerging domains like RAG and agentic frameworks, along with hands-on familiarity with tools such as Copilot, Claude, and Cursor, distinguish competitive candidates. The prominence of prompt engineering and proficiency with platforms like OpenAI are further indicative of a shift toward applied, practical AI implementation in workflows. Altogether, the landscape signals strong value for both foundational AI knowledge and specialized expertise in the latest generative and agentic technologies.
- AI (generic): 33,427
- LLMs: 7,282
- Generative AI: 5,306
- RAG: 2,085
- Copilot: 1,653
- Prompt engineering: 1,540
- Claude: 1,473
- OpenAI: 1,371
- Agentic frameworks: 1,081
- Cursor: 927
Seniority Levels
The job market data indicates a strong emphasis on mid and senior level positions, suggesting that employers are primarily seeking candidates with significant experience and expertise. Opportunities for entry level and intern roles are comparatively limited, which may present challenges for recent graduates or those just starting their careers. This distribution reflects a current demand for seasoned professionals who can immediately contribute to organizational goals.
- Mid Level: 55,519
- Senior: 50,245
- Entry Level: 9,964
- Intern: 3,989
Geographic Hotspots
Bengaluru stands out as the premier geographic hotspot, boasting the highest concentration of roles, followed by major Indian cities like Pune and Hyderabad. In the United States, remote opportunities are abundant, competing closely with the San Francisco Bay Area and New York Metro as the leading talent magnets. Other global cities with significant demand include London and Toronto. The continued dominance of US tech metros such as Seattle, Washington DC, Dallas-Fort Worth, and Boston illustrates their enduring status as key hubs, but the rapid rise of Indian cities signals a shift in the global landscape for opportunities. Overall, both remote and urban clusters remain intensely competitive, with a particularly strong surge seen across India and established strongholds in North America and the UK.
- Bengaluru, 19, IN: 7,419
- United States, 00, US: 6,641
- Pune, 16, IN: 4,030
- Hyderabad, 40, IN: 3,014
- New York City, NY, US: 2,544
- San Francisco, CA, US: 2,334
- London, ENG, GB: 1,900
- Chennai, 25, IN: 1,593
- Toronto, 08, CA: 1,494
- Republic of India, 00, IN: 1,417
US Metro Totals
- San Francisco Bay Area: 7,046
- New York Metro: 2,867
- Washington DC Metro: 1,584
- Seattle Metro: 1,515
- Dallas-Fort Worth Metro: 1,189
- Boston Metro: 1,031
- Los Angeles Metro: 928
- Austin Metro: 870
- Chicago Metro: 861
- Atlanta Metro: 723