Everyone tells you to get AWS certified. Nobody tells you that half of these certifications won't actually help you get hired — and some will waste months of your time.
I hold multiple AWS certifications including the Solutions Architect Professional. Through my academy I've helped more than 700 IT professionals and career switchers break into cloud. Here's every AWS certification ranked honestly, S tier to F tier, based on four criteria:
- Career ROI — will it actually help you land a job or get promoted?
- Market demand — are companies actively hiring for this?
- Difficulty vs payoff — is the time investment worth it?
- Who it's actually for — because a cert that's perfect for a beginner might be pointless for a senior engineer
The Full Tier List at a Glance
| Tier | Certifications |
|---|---|
| S | Solutions Architect Associate, Solutions Architect Professional, Security Specialty, Machine Learning Specialty |
| A | Generative AI Developer Professional, Advanced Networking Specialty, Machine Learning Engineer Associate |
| B | Cloud Practitioner, AI Practitioner, DevOps Engineer Professional |
| C | Data Engineer Associate |
| D | Developer Associate |
| F | CloudOps Engineer Associate |
Foundational Level
AWS Cloud Practitioner — B Tier
The most foundational AWS certification. Covers the business case for cloud, shared responsibility model, basic service awareness. Definitely the easiest AWS exam to pass.
Here's the bonus most people miss: when you pass any AWS certification, you get a 50% discount voucher for your next exam. Cloud Practitioner at $100 can save you $75 on your SAA or $150 on a Professional or Specialty exam. That alone makes it worth considering as your entry point.
For complete beginners with no tech background — don't skip it. It builds the foundation everything else sits on.
For people already in IT wanting to pivot to cloud — you could skip it, but it's an easy win and the voucher is real money.
It won't get you hired on its own. But the ROI for the time spent is solid. B tier.
AWS AI Practitioner — B Tier
Covers AI and machine learning services on AWS — SageMaker, Comprehend, Rekognition, Bedrock. You're not building anything. This is theoretical knowledge for existing IT professionals who want to stay relevant as companies scramble to operationalise AI.
Companies have mountains of data sitting in the cloud. They want predictions, recommendations, automations. They don't know how to get there. This certification is a genuine entry point for understanding how to integrate AI into cloud infrastructure.
Getting this early positions you ahead of everyone still ignoring the AI wave. Same tier logic as Cloud Practitioner though — foundational, not a hiring trigger on its own. B tier.
Associate Level
AWS Developer Associate — D Tier
Validates your ability to develop, test, deploy, and debug AWS applications. The problem: it's too narrow.
If you want to become a cloud engineer, companies want architecture thinking — the ability to design systems, make trade-offs, understand the bigger picture. Developer Associate doesn't test that.
If you're a software engineer, this gives you formal AWS validation, but you're better off building real projects.
If you're trying to break into cloud from a non-technical background, there's a better option coming.
Developer Associate speaks to a specific audience: software engineers who want formal AWS validation for development roles specifically. For everyone else it's the wrong starting point. D tier.
AWS Solutions Architect Associate — S Tier
The most popular AWS certification — and people dismiss it for exactly that reason. If everyone has it, how does it help me stand out?
Here's what those people miss: this certification fundamentally changes how you think about AWS.
Before SAA, you think in individual services. After SAA, you think in complete systems.
The exam puts you in realistic scenarios you'll actually face as a cloud engineer. A startup needs to handle unpredictable traffic spikes without overspending — what's the optimal approach? It tests your ability to make trade-offs and design solutions that fit real business constraints.
For beginners, this is the certification that actually opens doors. It appears in a huge percentage of cloud engineering job descriptions. It gets you past HR filters. It gets hiring managers to call you back.
For existing IT professionals, it validates your thinking at a systems level.
Best ROI in terms of time invested versus career impact, at any experience level. S tier.
CloudOps Engineer Associate — F Tier
Covers deploying, managing, and operating workloads on AWS. Can unlock entry-level positions like cloud support engineer and migration specialist.
Here's my honest take: if you design systems correctly, operations should run like clockwork. The goal of good operations is to make itself invisible.
And AWS knows this. They just released their own DevOps agent — an AI that handles deployments, monitoring, and incident response 24/7. They keep releasing tools that automate exactly what CloudOps engineers do.
Do you see the pattern? AWS is actively engineering away the need for as many operational people.
For existing sysadmins who need a quick stepping stone — it's fine. But for anyone choosing where to invest their time: don't build your career on work that's being automated away.
The market is moving from pure operations toward architecture and specialisation. F tier.
Machine Learning Engineer Associate — A Tier
Tests your ability to build and deploy machine learning models on AWS — data engineering for ML, model building with SageMaker, deployment, monitoring, optimisation.
Most people in tech right now do not understand machine learning. If you can demonstrate theoretical knowledge here, you stand out immediately.
The learning curve is steeper than any other associate-level certification. That difficulty is exactly what makes it valuable — not everyone can get it, so those who do carry more weight.
For engineers who want to position themselves for the AI wave, this is a strong move. The barrier to entry is higher but so is the payoff. A tier.
AWS Data Engineer Associate — C Tier
Covers data modelling, data lifecycle management, and data quality on services like Glue, Redshift, Athena, and data pipeline architecture.
Controversial take: data engineering as a career path has real automation risk. Querying, transforming, aggregating data — this is exactly what AI excels at.
That said: if your goal is to move into machine learning, data engineering is a natural stepping stone. You can't build ML models without clean data pipelines feeding them.
If you're in a data role and want to formalise your AWS knowledge while positioning toward machine learning — this path makes sense.
If you're starting from scratch with no data background — go to Solutions Architect Associate first. C tier.
Professional Level
DevOps Engineer Professional — B Tier
Covers CI/CD pipelines, automation, monitoring, and infrastructure as code. Significant depth and real weight in the market.
The honest concern: entry-level DevOps roles are disappearing. Companies want senior engineers with four to five years of experience minimum. And AWS released their own 24/7 DevOps agent. Pure DevOps is fragmenting into platform engineering and cloud architecture.
If you're already in this space and want to formalise your knowledge for senior roles — this certification carries real weight.
For beginners trying to break in — focus on SAA first. DevOps Professional is a second or third certification, not a starting point. B tier.
Solutions Architect Professional — S Tier
I hold this certification. It is one of the most valuable in the entire AWS ecosystem — and only a tiny percentage of certified professionals have it.
The exam tests genuine enterprise complexity: hybrid architectures, migration strategies, advanced networking, disaster recovery. You get scenarios like: a financial services company wants to migrate their entire data centre to AWS with strict compliance requirements and zero downtime. Design the migration strategy.
There's no tutorial for this. No simple answer. You need real depth across the entire AWS platform and the ability to connect cloud technology to business requirements.
For engineers who want senior and architecture roles — this gets your foot in the door for positions most people can't even interview for.
For beginners — build up to this. Get Cloud Practitioner, then SAA, get real experience, then come back. S tier.
Generative AI
Generative AI Developer Professional — A Tier
Focused on building production-level GenAI applications using Amazon Bedrock and related services. New territory — the market is still figuring out what GenAI roles actually look like.
The uncertainty is both the risk and the opportunity. Every company wants to figure out GenAI. Most have no idea how to implement it. Engineers who can take AI from concept to production are rare.
The bet: GenAI becomes fundamental to how software is built. Based on everything happening in the market right now, that bet looks solid.
Still needs more role certainty to hit S tier. But the potential upside is massive. A tier.
Specialty Level
Advanced Networking Specialty — A Tier
Covers complex networking scenarios: hybrid connectivity, VPCs, Direct Connect, Transit Gateway. Engineers who truly understand AWS networking at this level are rare — and rare skills command premium salaries.
When companies do complex migrations or build serious infrastructure, they need someone who can handle networking without breaking everything. That person commands serious compensation.
Not a starting point — too complex if you're new to cloud. But for engineers already working in cloud or networking, this is completely underrated. A tier.
Security Specialty — S Tier
Covers IAM, data protection, encryption, incident response, and compliance frameworks.
Cloud security is the number one most in-demand skill among cybersecurity professionals. Demand is high. Supply is limited. And AI isn't replacing this anytime soon — security requires constant human judgment and adaptation to new threats.
Don't let it delay you from getting into roles though. Get SAA, get your foot in the door, then pursue this once you're working in cloud. S tier.
Machine Learning Specialty — S Tier
Deep dive into building, training, and deploying machine learning models on AWS. Companies understand AI's potential but most don't know how to implement it. Engineers who can take ML from concept to production are commanding some of the highest salaries in tech.
Like Security Specialty — genuinely hard, requires deep knowledge on top of your AWS fundamentals. That difficulty is exactly why it's valuable.
Get SAA first. Build real experience. Then come back to this. S tier.
The Strategy: What to Actually Do
If you're a complete beginner or existing IT professional (sysadmin, network engineer, cybersecurity): Cloud Practitioner → Solutions Architect Associate → Solutions Architect Professional
If you're already in cloud and want to level up: Solutions Architect Professional or Security Specialty
If you want to ride the AI wave: Layer in Machine Learning Engineer Associate or Machine Learning Specialty after SAA
The Truth Nobody Wants to Hear
Certifications get you past HR filters. They get hiring managers to call you back.
But when it comes to interviews and actually getting hired — you need to prove you can do the work. That means designing and building solutions that actually work. Hands-on projects. Breaking things. Fixing them. Understanding why, not just memorising what.
Certifications open doors. Projects get you through them.
Pick your certification strategically based on where you are and where you want to go — then make sure your study method gets you there as fast as possible.