Principal AWS Cloud Engineer

About the role

Raleigh, NC is the preferred location for this role. Remote positions within the United States are considered, with the expectation that the selected individual will work a U.S. eastern time zone schedule.

Responsibilities

• Design, build, and maintain secure, highly available AWS environments optimized for reliability, performance, scalability, and cost efficiency.
• Implement reusable AWS infrastructure patterns across compute, networking, storage, identity, containers, serverless, and database services.
• Develop and maintain Infrastructure as Code modules, templates, and pipelines that support consistent provisioning and deployment practices.
• Develop and maintain internal enablement resources — playbooks, templates, workshops that accelerate team adoption of AI-assisted engineering across the engineering organization.
• Partner with application, security, architecture, and operations teams to modernize workloads and improve cloud-native delivery practices.
• Implement security controls and operational guardrails, including least-privilege IAM, encryption, secrets management, network segmentation, and compliance-aligned practices.
• Improve cloud operations through monitoring, logging, alerting, incident response, runbooks, automated remediation, and continuous reliability improvements.
• Review cloud designs and changes against AWS Well-Architected principles, internal standards, and production readiness expectations.
• Troubleshoot complex cloud, platform, networking, deployment, and performance issues across AWS environments.
• Mentor engineers on AWS, Kubernetes, automation, security, and platform engineering best practices while promoting continuous learning.
• Communicate technical recommendations clearly to engineering partners, product stakeholders, security teams, and leadership.

Requirements

• 10+ years of engineering or IT experience, with 5+ years focused on AWS cloud engineering, automation, platform engineering, or cloud architecture.
• Strong hands-on experience with core AWS services, including EC2, S3, VPC, IAM, Lambda, RDS/Aurora, EKS, CloudWatch, and Route 53.
• Experience leveraging AI-assisted engineering tools (e.g., GitHub Copilot, Claude, Cursor) in day-to-day development, code review, and platform work — and a demonstrated ability to enable and upskill other engineers in their adoption.
• Experience designing and implementing Infrastructure as Code using Terraform, AWS CloudFormation, AWS CDK, or similar tooling.
• Strong scripting or programming skills using Python, Bash, Go, or similar languages to automate cloud operations and integration workflows.
• Knowledge of CI/CD, DevOps, and GitOps practices using tools such as Jenkins, GitHub Actions, Argo CD, Azure DevOps, or comparable platforms.
• Experience with containers and Kubernetes-based deployment patterns, including Docker, EKS, Helm, service networking, and autoscaling concepts.
• Solid understanding of AWS networking concepts, including VPC design, subnets, routing, security groups, load balancing, DNS, and hybrid connectivity patterns.
• Knowledge of cloud security and compliance practices, including IAM least privilege, encryption, secrets management, vulnerability remediation, and policy guardrails.
• Experience with observability and SRE practices, including monitoring, logging, alerting, incident response, runbooks, and operational readiness reviews.
• Experience supporting cloud data services and storage patterns such as RDS/Aurora, DynamoDB, S3, caching, backup, and lifecycle management.
• Strong communication, collaboration, problem-solving, and mentoring skills, with the ability to influence technical decisions across teams.
• Experience with platform engineering Internal Developer Portal (IDE) or self-service cloud development environments that help teams design, provision, deploy, and operate cloud infrastructure through governed workflows.

Qualifications

• AWS Associate or Professional-level certification, Certified Kubernetes Administrator, or comparable cloud/platform certification.
• Experience building reusable Infrastructure as Code modules, golden paths, templates, or self-service provisioning patterns for engineering teams.
• Experience with AWS multi-account, landing zone, or account governance patterns using services such as AWS Organizations, Control Tower, IAM Identity Center, or related guardrail capabilities.
• Experience with serverless and event-driven AWS architectures using services such as Lambda, Step Functions, API Gateway, EventBridge, SQS, SNS, or Kinesis.
• Experience with observability platforms and operational tooling such as CloudWatch, OpenTelemetry, Datadog, Splunk, or comparable monitoring and logging solutions.
• Familiarity with cloud cost optimization, capacity planning, tagging strategies, and FinOps practices.
• Experience supporting data, analytics, AI, or machine learning workloads on AWS is a plus.
• Experience with AWS AI/ML services including Bedrock, SageMaker, or related managed AI services — particularly in designing the infrastructure and operational patterns that support AI workload deployment at scale.

Skills

• AWS Associate or Professional-level certification, Certified Kubernetes Administrator, or comparable cloud/platform certification.
• Experience building reusable Infrastructure as Code modules, golden paths, templates, or self-service provisioning patterns for engineering teams.
• Experience with AWS multi-account, landing zone, or account governance patterns using services such as AWS Organizations, Control Tower, IAM Identity Center, or related guardrail capabilities.
• Experience with serverless and event-driven AWS architectures using services such as Lambda, Step Functions, API Gateway, EventBridge, SQS, SNS, or Kinesis.
• Experience with observability platforms and operational tooling such as CloudWatch, OpenTelemetry, Datadog, Splunk, or comparable monitoring and logging solutions.
• Familiarity with cloud cost optimization, capacity planning, tagging strategies, and FinOps practices.
• Experience supporting data, analytics, AI, or machine learning workloads on AWS is a plus.
• Experience with AWS AI/ML services including Bedrock, SageMaker, or related managed AI services — particularly in designing the infrastructure and operational patterns that support AI workload deployment at scale.

Benefits

We know your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits.
• Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan.
• Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs.
• Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity.
• Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits.
• Health Savings, Health Care, Dependent Care and Commuter Spending Accounts.
• Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice.

Pay

The U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.

Schedule

This job is eligible for an annual incentive bonus.