Global Streaming Infrastructure
Multi-region deployment serving 200M+ subscribers with auto-scaling infrastructure handling 100x traffic spikes during popular releases.
Real-Time Messaging Platform
WebSocket infrastructure handling millions of concurrent connections with data pipelines processing 25+ billion events daily.
Banking Infrastructure
Secure, compliant cloud infrastructure processing billions in transactions with zero-trust networking and automated compliance.
Booking Platform
Elastic compute infrastructure scaling during peak seasons with cost attribution tracking across 50+ engineering teams.
What AWS Engineers Actually Build
Before you write your job description, understand what AWS work looks like at different companies. Here are real examples from industry leaders:
Streaming & Media
Netflix runs its entire streaming platform on AWS, serving 200+ million subscribers globally. Their AWS engineers handle:
- Auto-scaling infrastructure that handles 100x traffic spikes during popular show releases
- Multi-region deployment across 20+ AWS regions for low-latency streaming
- Cost optimization at massive scale ($400M+ annual AWS spend)
- Chaos engineering tools like Chaos Monkey that randomly terminate instances to ensure resilience
Collaboration & Communication
Slack uses AWS to power real-time messaging for millions of workspaces. Their engineers build:
- WebSocket infrastructure on API Gateway and Lambda handling millions of concurrent connections
- Search indexing with Elasticsearch Service across billions of messages
- Data pipelines processing 25+ billion events daily through Kinesis
Travel & Hospitality
Airbnb runs their booking platform entirely on AWS. Their cloud engineers manage:
- Elastic compute scaling during peak booking seasons
- Multi-region data replication for disaster recovery
- Cost attribution systems tracking spend across 50+ engineering teams
AWS Developer Archetypes
"AWS developer" is broad. Before hiring, clarify which role you actually need:
1. Cloud/Platform Engineer
Focus: Infrastructure as code, developer productivity, self-service platforms
Primary Services: EC2, ECS/EKS, Lambda, CloudFormation, CDK
Daily Work: Building Terraform modules, deployment pipelines, internal developer tooling
Who Needs Them: Companies wanting to standardize infrastructure and empower product teams
2. DevOps/SRE Engineer
Focus: Reliability, monitoring, incident response, operational excellence
Primary Services: CloudWatch, X-Ray, Auto Scaling, Route 53, Systems Manager
Daily Work: SLA management, on-call rotation, runbook creation, capacity planning
Who Needs Them: Companies with production systems requiring 99.9%+ uptime
3. Data Engineer
Focus: Data pipelines, warehousing, analytics infrastructure
Primary Services: S3, Redshift, Glue, Athena, Kinesis, EMR
Daily Work: ETL development, data modeling, query optimization, cost management
Who Needs Them: Companies processing large data volumes for analytics or ML
4. Solutions Architect
Focus: System design, cross-team technical leadership, vendor evaluation
Primary Services: All of them—breadth over depth
Daily Work: Architecture reviews, technical roadmaps, cost optimization strategies
Who Needs Them: Larger organizations needing technical direction across multiple teams
5. Backend Developer with AWS
Focus: Application development using AWS managed services
Primary Services: Lambda, API Gateway, DynamoDB, SQS, SNS, Step Functions
Daily Work: Feature development, serverless functions, API design, event-driven architectures
Who Needs Them: Startups wanting to build quickly without managing infrastructure
Core AWS Competencies
Must Understand for Any AWS Role
1. Identity and Access Management (IAM)
The security foundation of AWS. Strong candidates explain:
- Least privilege principles and why they matter
- Role-based access vs. user-based access
- Cross-account access patterns for multi-account architectures
- Service-linked roles and when to use them
- Why hardcoded credentials are a security and operational nightmare
2. Networking (VPC)
The backbone of any AWS architecture:
- Public vs. private subnets and when to use each
- Security groups vs. NACLs—and why security groups are usually enough
- VPC peering, Transit Gateway, and PrivateLink for service connectivity
- How networking choices impact both security and cost
3. Compute Options Trade-offs
A strong candidate doesn't just know these services—they know when to choose each:
- EC2: Full control, predictable workloads, legacy apps, specific OS requirements
- ECS/EKS: Container orchestration—ECS for AWS-native, EKS for Kubernetes teams
- Lambda: Event-driven, auto-scaling, cold starts are the main trade-off
- Fargate: Serverless containers—simpler than EC2 but less control
4. Cost Awareness
AWS makes it easy to overspend. Good candidates naturally discuss:
- Reserved Instances vs. Spot vs. On-Demand and when to use each
- Right-sizing resources based on actual utilization
- Cost monitoring, budgets, and alerts
- Architecture decisions that affect cost (serverless vs. always-on, data transfer patterns)
AWS vs Azure vs GCP: Does Platform Matter?
The Short Answer
Cloud skills transfer 70-80% between providers. An experienced AWS engineer can become productive on Azure or GCP in 2-4 weeks. However, deep expertise in your specific provider matters for:
- Architecture decisions that leverage provider-specific strengths
- Cost optimization (each provider bills differently)
- Operational excellence (each has different monitoring and tooling)
When to Be Flexible
- Startups with small cloud footprints
- Teams just getting started with cloud
- Roles focused on application development (serverless, databases)
When Provider Experience Matters
- Large-scale infrastructure ($100K+/month spend)
- Multi-region, high-availability architectures
- Compliance-heavy industries (healthcare, finance) where you need provider-specific certifications
- Migrations between clouds (need source and target expertise)
Market Reality
AWS has 32% market share, Azure 23%, GCP 10%. This means more AWS talent exists, but also more competition for that talent. Azure expertise is increasingly valuable as enterprises adopt Microsoft's cloud.
Certification vs. Experience: The Recruiter's Guide
What Certifications Signal
✅ Baseline knowledge of AWS services
✅ Ability to pass structured exams
✅ Investment in learning and career growth
✅ Vocabulary familiarity for technical conversations
What Certifications Don't Guarantee
❌ Production architecture experience
❌ Debugging skills under pressure
❌ Cost optimization intuition
❌ Security best practices in real environments
❌ Ability to make architecture trade-offs
The Certification Hierarchy
| Level | Certification | What It Means |
|---|---|---|
| Foundational | Cloud Practitioner | Knows AWS exists—not technical |
| Associate | Solutions Architect, Developer, SysOps | Can work with guidance |
| Professional | Solutions Architect Pro, DevOps Pro | Can architect complex systems |
| Specialty | Security, Database, ML, etc. | Deep expertise in specific domain |
Hiring Guidance
- Don't require certification for experienced candidates—production experience trumps exams
- Do value certification for career changers or junior candidates—shows commitment
- Be skeptical of multiple certifications without production experience
- Professional-level certs with experience are the sweet spot for senior roles
Recruiter's Cheat Sheet
Technical Terms to Know
| Term | What It Means | Why It Matters |
|---|---|---|
| EC2 | Virtual servers in the cloud | The original AWS service, still foundational |
| S3 | Object storage for files | Where everyone stores data—99.999999999% durability |
| Lambda | Serverless computing (code without servers) | Modern apps use this heavily |
| EKS/ECS | Container orchestration services | How companies run Docker containers |
| IAM | Identity and Access Management | Security—who can do what |
| VPC | Virtual Private Cloud | Networking—how resources connect |
| Terraform | Infrastructure as Code tool (not AWS-specific) | The industry standard for managing cloud |
| CDK | AWS Cloud Development Kit | AWS's IaC tool using programming languages |
| CloudFormation | AWS's native IaC (YAML/JSON) | The original AWS automation tool |
Conversation Starters That Reveal Skill Level
| Question | Junior Answer | Senior Answer |
|---|---|---|
| "What's your approach to AWS security?" | "We use IAM users" | "Least privilege roles, no long-lived credentials, automated policy auditing" |
| "How do you manage infrastructure?" | "Through the console" | "Everything in Terraform/CDK with code review and automated testing" |
| "Tell me about a cost optimization project" | Generic or vague | Specific: "Reduced spend 40% by moving to Graviton and implementing Spot" |
Resume Signals That Matter
✅ Look for:
- Specific AWS services they've used (not just "AWS experience")
- Scale indicators ("managed 500+ EC2 instances", "$200K monthly spend")
- Infrastructure as Code tools (Terraform, CDK, Pulumi)
- Mentions of multi-account or multi-region architectures
🚫 Be skeptical of:
- Listing 50+ AWS services as "known" (no one uses all of them)
- Console-only experience with no IaC
- Certifications without production experience
- "AWS expert" with no specific examples
Common Hiring Mistakes
1. Over-indexing on Certifications
A developer with Solutions Architect Professional cert but no production experience will struggle with real architecture decisions, cost optimization, and incident response. Prioritize hands-on experience over credentials.
2. Testing Console Knowledge
Clicking through the AWS console is different from writing Terraform. Modern infrastructure is code. Ask about IaC tools and practices—"How do you test infrastructure changes before deploying?"
3. Ignoring Cost Awareness
AWS makes it easy to overspend. Candidates who've never thought about cost optimization may rack up bills. Ask about their cost management experience and how they've optimized spend.
4. Hiring Generalists When You Need Specialists
An EC2/ECS expert may not know Redshift deeply. A Lambda specialist may never have touched VPC networking. Clarify which services matter for your use case and hire accordingly.
5. Requiring All Three Clouds
"Must know AWS, Azure, AND GCP" signals confusion. Pick your cloud and hire for it. Multi-cloud expertise is rare and expensive—and often unnecessary.