Job ads now list platform names. Azure AI, AWS, Vertex AI show up more. Recruiters want clear evidence of skills. Certifications offer proof.
Recent data shows AI job postings grew sharply. Lightcast found postings for generative AI skills jumped from 55 in January 2021 to nearly 10,000 by May 2025. Lightcast Autodesk tracked mentions of AI in job listings. These mentions rose by 56.1% in the US through early 2025. Autodesk News Recruiters see this growth and they adjust what they trust.
What Are Vendor-Specific vs Platform-Agnostic Certs
Vendor-specific certs tie you to a single cloud or tool. Examples: AWS AI Practitioner, Microsoft Azure AI Engineer, Google ML Engineer. They test your skills on that vendor’s platform.
Platform-agnostic (neutral) certs teach broad AI theory, math, models, ethics. These apply across clouds and tools.
What Job-Ad Data Tells Us
Analysis of over 3,000 AI engineering job postings from April to June 2025 showed strong demand for engineers who can deploy real models. Flex.ai These postings often list specific tools and platforms. They mention AWS, Azure, GCP by name. Few mention generic AI certification alone.
AI & ML job postings grew 89% in June 2025 vs January. Top skills: Python, TensorFlow, PyTorch. Certs from vendors like AWS appeared. Neutral certs appeared less. Public Insight Data suggests recruiters value tool fluency.
What Recruiters Say
Recruiters ask: does the candidate know the tools we use? They trust certs that match their platform stack.
Neutral certs help for roles that cross many platforms. Strategy, product management, roles in AI governance lean neutral. Deep engineering work steeped in AWS/GCP often favors vendor certs.
Recruiters want evidence of impact. Theory is fine. Projects matter. If candidate shows solution built with a tool, recruiter trusts more.
Advantages & Limits of Vendor-Specific Certs
Pros:
Cert shows you know a tool deeply.
Employers using that vendor see you ready.
Faster learning path; many vendor-study materials.
Cons:
If your employer uses another cloud, cert loses value.
Tools and APIs change; cert may need renewal.
Cert may limit choices between jobs in different stacks.
Advantages & Limits of Platform-Agnostic Certs
Pros:
Broad theory works across platforms.
Greater flexibility if shifting clouds or companies.
Good for roles not tied to one tech stack.
Cons:
May lack hands-on experience with real tools.
Hiring manager may doubt you can use their vendor tools.
Sometimes viewed as less “practical” for platform-heavy roles.
Sample Method That Shows What Recruiters Mention
Researchers pulled 3,000 engineering job listings (April-June 2025). They counted mentions of vendor tools. They saw vendor names in 70%+ of tool-required roles. Neutral AI certification mention was much lower. Flex.ai They also measured salary ranges. Vendor tool roles often list higher minimums.
Advice for Candidates
Pick one vendor cert that matches targets. Also get one neutral cert. Show both on your CV.
Build projects. Use tools from the vendor you certify in. Show what you built.
Update certs or take new ones when tools change.
Read this post from ONLC: Best AI Certifications in 2025 to see vendor and neutral certs compared. That helps you choose wisely.
How Recruiters Will Likely Shift
Certs that combine vendor-tool skills and theory will gain trust. Roles in AI safety and governance will value neutral certs more.
Hybrid certs will emerge. Certs with hands-on labs, cross-cloud projects, ethics, and theory.
Certs with proof of impact (projects, code, metrics) will outrank mere certificate names.
Key Findings
Job ads use vendor platform names more often than neutral cert keywords.
Vendor certs shine when tool use matters.
Neutral certs work better for cross-role, theory, governance, and non-tool focal jobs.
Best strategy: combine both. One vendor cert and one neutral.
Projects and hands-on proof matter more than paper alone.
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