Cloud Infrastructure Engineer

Cloud Infrastructure Engineers work on the layer of cloud that every application in the organization depends on. When a developer deploys a containerized service, they're deploying into network infrastructure, compute platforms, and shared services that the infrastructure engineer built and maintains. When that service has a latency problem, it might be in the application — or it might be in the service mesh, the DNS resolution, or the subnet routing that the infrastructure engineer owns.

The scope of this role is wider and deeper than application-focused engineering. On a given week, a Cloud Infrastructure Engineer might be provisioning a new AWS account for a product team using the organization's standard landing zone template, debugging an asymmetric routing problem across a transit gateway, reviewing a security group audit finding from the CSPM tool, and planning a Kubernetes version upgrade for the shared cluster.

Infrastructure as code is the dominant work pattern. Everything the team builds should be in Terraform or equivalent — not because it's policy, but because infrastructure that isn't in code is infrastructure that can't be reliably reproduced, audited, or changed safely. Writing good Terraform modules — ones that are flexible enough to serve multiple teams but constrained enough to enforce organizational standards — is a real craft that takes years to develop.

Multi-account AWS or Azure environments are the norm at companies above a few hundred engineers. Infrastructure engineers working in these environments need to understand Organizations, Service Control Policies, permission boundaries, and cross-account access patterns that don't exist in single-account setups. The operational complexity of keeping dozens or hundreds of accounts well-governed requires systematic tooling and process.

Security is built into the role, not bolted on. IAM design, network segmentation, encryption key management, and cloud posture monitoring are infrastructure concerns that infrastructure engineers own directly.

Education:

• Bachelor's degree in computer science, computer engineering, or information systems
• Self-taught engineers with strong open source infrastructure contributions or project portfolios are regularly hired
• Certifications in cloud platforms and Kubernetes are often treated as equivalent to academic credentials

Experience benchmarks:

• Entry-level: 2–4 years, often transitioning from sysadmin, network engineering, or software development
• Mid-level: 4–8 years with production multi-account cloud ownership and Kubernetes operations experience
• Senior: 8+ years with cross-organizational infrastructure impact and architecture decision authority

Required technical skills:

• Cloud platform depth: AWS (VPC, Transit Gateway, IAM, EKS, RDS, Organizations, Control Tower) or Azure/GCP equivalent
• Infrastructure as code: Terraform with module design, state management, workspace strategy, and CI/CD integration
• Networking: VPC design, subnetting, BGP basics, NAT, VPN, Private Link/PrivateLink, network ACL vs. security group behavior
• Kubernetes: cluster administration, networking CNI plugins, RBAC, persistent storage, cluster upgrades
• Observability: CloudWatch, Prometheus, Grafana, distributed tracing, centralized log aggregation
• Security: IAM at depth, CSPM tools (Wiz, Prisma Cloud), KMS key management, SSM and Secrets Manager

Soft skills:

• Systematic diagnosis: ability to trace a problem through multiple infrastructure layers without a clear starting point
• Documentation discipline: producing clear architecture documentation and runbooks consistently
• Cross-team communication: explaining infrastructure constraints to application engineers without being dismissive

Certifications valued:

• AWS Solutions Architect Professional
• Certified Kubernetes Administrator (CKA)
• HashiCorp Terraform Associate or Professional

Cloud Infrastructure Engineers are in sustained, strong demand. Cloud market growth shows no sign of plateauing, and the foundational infrastructure layer — which every cloud workload depends on — requires engineers with deep platform expertise that takes years to develop and is genuinely hard to offshore or automate entirely.

The maturation of cloud environments at large organizations is creating a second wave of infrastructure work. Organizations that moved to cloud in 2018–2022 often did so with architectures that made sense at small scale but are now showing strain: flat account structures with permission sprawl, ad hoc VPC designs with overlapping CIDRs, logging gaps, and inconsistent security baselines. Infrastructure engineers who specialize in cloud environment remediation and modernization are finding significant demand.

Kubernetes operations have stabilized as a core skill requirement. The initial container adoption wave has settled into an ongoing operational reality, and organizations need engineers who can maintain production cluster health, perform major version upgrades, and support the developers building on top of Kubernetes rather than still setting it up for the first time.

AI infrastructure is a high-growth specialty within this role category. GPU cluster provisioning, high-performance networking for distributed model training, vector database deployment, and inference serving platform design all require cloud infrastructure engineering skills applied to new workload types. Engineers who develop this specialty are in acute supply shortage.

Career progression runs from Infrastructure Engineer → Senior Infrastructure Engineer → Staff/Principal Engineer → Cloud Architect or Engineering Manager. Senior individual contributors at large tech companies can achieve $200K–$350K+ in total compensation. The principal/staff IC track offers architectural scope comparable to management without the people management component.

Dear Hiring Manager,

I'm applying for the Cloud Infrastructure Engineer position at [Company]. I've spent five years as an infrastructure engineer at [Current Company], where I own the AWS account architecture and shared platform services for a 500-engineer organization running workloads across 40 accounts.

The project I'm most proud of this past year is a Transit Gateway redesign we completed in Q3. Our original hub-and-spoke architecture had grown to the point where we were routing traffic through unnecessary hops, creating latency issues for services in adjacent VPCs. I redesigned the routing tables and propagation configurations to create direct connectivity between accounts that need it, which cut cross-VPC latency for our highest-traffic service from 4ms to 0.8ms. The work required coordinating planned network change windows across 12 product teams — not technically complex, but organizationally demanding.

I've also built out our Terraform module library from near-zero. We had Terraform in use but no consistent module structure — every team wrote configurations differently and shared nothing. I defined a module versioning standard, wrote 22 modules covering our most common infrastructure patterns, and ran adoption sessions with each product team. Module adoption is now at 85% of new infrastructure created in the last six months.

I'm interested in [Company]'s infrastructure challenges specifically because of your Kubernetes platform — you're running at a scale where CNI plugin choice, cluster networking, and namespace isolation patterns matter, and that's where I want to develop deeper expertise.

[Your Name]