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Cloud hiring spans AI, software, security, infrastructure, data, reliability, and cost management—not one standardized job ladder. A 2026 survey reported that 36% of companies had added AI/ML engineers as part of cloud investments, but that figure is a share of surveyed companies, not a share of job openings or an occupation growth rate. The 20 roles below are a practical map of the work and skills involved, with that distinction kept clear.
How to read the role-demand figures
CIO’s August 27, 2026 feature attributes the percentages below to Foundry’s 2026 Cloud Computing Study. Each percentage is the share of surveyed companies reporting that they added the role as part of cloud investments. It does not show the portion of all vacancies held by that role, the rate of occupational growth, or how many openings exist. The reviewed feature does not provide the survey’s sample size or full methodology, so treat the figures as a directional survey finding rather than a universal hiring ranking. Role titles and scope also vary by employer.
The percentages are ordered from highest to lowest as reported by CIO. CIO’s role feature is the source for these descriptions and figures.
AI, application development, and product roles
1. AI/ML engineer — 36%
Designs and implements machine-learning systems and oversees their operation. Relevant skills include programming, machine learning, data science, data engineering, and building AI systems that use APIs. The 36% figure is the share of companies in Foundry’s 2026 study, as reported by CIO, that said they added this role as part of cloud investments.
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2. AI platform engineer — 27%
Builds and runs internal systems that teams use to develop and scale AI tools. The work sits close to cloud infrastructure and platform operations; useful skills include programming, Kubernetes, and Docker.
3. Cloud software engineer — 20%
Develops and maintains scalable applications running on cloud platforms. Employers may look for programming, microservices, serverless computing, APIs, DevOps, and cybersecurity experience.
4. Cloud developer — 20%
Designs, creates, and deploys cloud applications, with an emphasis on scalable, reliable, cost-conscious solutions. Common skill areas include programming, cloud platforms, microservices, databases, APIs, containers, and orchestration. Its title can overlap with cloud software engineer, so compare the actual duties in a posting.
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5. Cloud product manager — 16%
Turns stakeholder needs into requirements and roadmaps for cloud services, then uses user and quality feedback to guide improvements. Product management, communication, collaboration, user experience, and enough technical knowledge to work effectively with engineering teams are relevant.
6. Prompt engineer/AI application developer — 14%
CIO groups prompt-instruction design with building software systems and interfaces for AI-enabled services. The listed skills include programming, databases, API integration, and software engineering. Because employers can use this combined title differently, inspect whether a particular job emphasizes model interaction, application development, or both.
Architecture, consulting, and governance
7. Cloud architect — 21%
Helps design and maintain cloud environments and guides implementation. The work can involve application architecture, automation, IT service management, governance, security, and leadership. The title often signals broad design responsibility, but seniority and decision-making authority depend on the employer.
8. Cloud consultant — 16%
Advises organizations on how cloud technology can meet business needs. Solution design, DevOps, automation, project management, compliance, and migration knowledge can all matter; the balance depends on whether the engagement is strategic, technical, or implementation-focused.
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9. Security architect — 16%
Designs security approaches for cloud infrastructure, applications, and data. Relevant areas include security architecture, governance, incident response, encryption, identity and access management, and DevSecOps.
10. Cloud governance/compliance manager — 16%
Helps oversee risk, policy, regulation, and secure cloud operations. The CIO feature names GDPR, HIPAA, PCI DSS, and governance tools as relevant knowledge areas. A job’s actual regulatory requirements will depend on the organization and jurisdictions it operates in.
Security, networks, and platform operations
11. Security engineer — 19%
Protects systems, networks, and data, including cloud-hosted services and applications. Typical skill areas include network security, identity and access management, encryption, vulnerability management, and cloud security.
12. Cloud network engineer — 15%
Designs and manages cloud networks, including hybrid or multicloud integration. Networking, virtualization, security, automation, and scripting are relevant skills.
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Builds and maintains the tools and shared platforms developers use, such as automation, self-service portals, and deployment foundations. Infrastructure as code, containers, orchestration, scripting, Linux, and networking are among the listed skills.
14. Cloud sysadmin — 13%
Maintains cloud infrastructure, policies, patches, and performance. The CIO feature describes this as likely the most entry-level-friendly role on its list and names Azure, AWS, and Google Cloud among relevant tools. That is a relative description of this role list, not a guarantee that a particular opening has no experience requirements.
15. DevOps engineer — 11%
Connects software development and operations through automated deployment and infrastructure maintenance. Automation, Linux, testing, security, containers, and programming are relevant. Employers may draw the boundary between DevOps and platform engineering differently, so check whether the role centers on delivery pipelines, shared developer platforms, or both.
Data, machine-learning operations, and reliability
16. Data architect — 14%
Structures organizational data so it can be accessed, secured, stored, and used for business needs. Relevant work includes data warehousing, performance, governance, migration, and hybrid cloud.
17. MLOps engineer/AI operations engineer — 13%
Connects machine learning with IT operations and works across data science, development, operations, and stakeholder teams. Programming, DevOps, cloud tools, containers, orchestration, and machine-learning tools are useful skills.
18. Site reliability engineer — 8%
Improves service reliability and scalability through infrastructure automation, monitoring, and incident response. The role is generally centered on how services behave in production rather than only on building application features.
Cloud cost and investment decisions
19. FinOps/cloud cost optimization practitioner — 9%
Brings finance, technology, and business perspectives together to inform cloud-investment decisions. The CIO feature names AWS, Azure, GCP, and FinOps platforms as relevant tools or knowledge areas.
Rank #4
20. FinOps lead/FinOps manager — 6%
Bridges engineering, finance, and business teams to improve cost visibility and budget decisions. Relevant skills include cloud platform knowledge, basic coding, and data analytics. The distinction from an individual practitioner is often one of organizational scope and leadership, but employers do not use titles uniformly.
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For a separate hiring signal, O*NET’s employer-based skills page reports Lightcast data for U.S. Computer Systems Engineers/Architects postings from January 1 through December 31, 2025. Its percentages are the share of unique postings linked to that occupation that mention each skill—not shares across all cloud jobs or all countries.
| Skill | Share of U.S. postings for this occupation mentioning it |
|---|---|
| Python | 31% |
| AWS | 31% |
| Microsoft Azure | 26% |
| Terraform | 18% |
| Kubernetes | 17% |
| Linux | 14% |
| Docker | 12% |
| SQL | 12% |
These figures can help identify skills associated with one U.S. occupation, but they should not be applied as a universal checklist for all 20 roles. See O*NET’s Computer Systems Engineers/Architects skills data for the occupation-specific measure.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the broader hiring context says—and does not say
McKinsey’s Technology Trends Outlook 2025 describes cloud and edge job postings as fluctuating between 2021 and 2024. It says postings for senior software engineers, software developers, and technical architects peaked in 2022, then declined in 2024 to near 2021 levels. It also reports that demand for product managers, data engineers, and data scientists grew over the preceding year. These are historical trends through 2024, not a count of 2026 vacancies.
That report also describes uneven skill availability: AWS talent was especially scarce relative to demand, while DevOps, Kubernetes, and Python faced shortages; Linux and database skills were more readily available. This is contextual evidence, not proof that any one skill guarantees employment now. Read the McKinsey Technology Trends Outlook with its period and scope in mind.
How to choose a role to pursue
- Start with the work you want to do. Choose among application development, architecture, security, networking, platform operations, data and AI, reliability, or cost governance. Several roles share tools but differ in the problems they own.
- Compare responsibilities, not title alone. Look for the deliverables and boundaries in a job description: designing systems, writing application code, managing identity and risk, operating a platform, handling incidents, or analyzing spend.
- Check required skills against the role’s focus. Python, cloud platforms, containers, networking, databases, automation, and security can recur across jobs, but no single set applies equally to every role. The O*NET percentages above are specifically for U.S. Computer Systems Engineers/Architects postings in 2025.
- Assess level and scope. Check experience requirements, ownership, stakeholder expectations, and whether the job is individual-contributor or leadership work. Titles do not standardize seniority across employers.
- Read demand claims with their context. Confirm whether a figure measures company-reported role additions, job postings, a particular occupation, a country, and a time period. Those measures answer different questions.
Workforce planning also involves developing existing staff, not only recruiting. A March 24, 2025 GAO report describes 18 private-sector companies identified as innovation leaders that reported practices such as assessing cloud-related skill gaps, reviewing recruiting and retention strategies, and ensuring staff have the training, time, and tools to operate cloud systems. GAO states that the sample is nongeneralizable, so it should not be treated as representative of all employers. The report is useful context for why training and workforce development accompany cloud role planning: GAO’s cloud adoption practices report.
Quick Recap
What the available figures cannot establish
- They do not establish a global ranking of current vacancies or prove that one role is best for every job seeker.
- They do not provide comparable salary or seniority data across all 20 roles.
- The Foundry company-addition percentages and O*NET posting percentages measure different things and should not be compared as if they were the same statistic.
- Employer titles can overlap; the role’s stated responsibilities, required skills, geography, and date are more useful than title alone.
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