Principal AWS Cloud Engineer

About the Team

Lexis Nexis Legal & Professional serves customers in over 150 countries with 11,800 employees globally. We are part of RELX, a provider of information‑based analytics and decision tools for professional and business customers. Our company leads in deploying AI and advanced technologies to the legal market, enhancing productivity and transforming the business and practice of law. We use ethical and powerful generative AI solutions with a flexible approach, prioritizing the best model for each legal use case.

Please note that Raleigh, NC would be the preferred location for this role. We are open to hiring on a remote basis in the United States, with the understanding that the selected individual will work a U.S. eastern time zone schedule. As a Consulting Principal AWS Cloud Engineer, you will design, build, and guide secure, scalable AWS cloud platforms and cloud‑native solutions.

You will partner with engineering, security, architecture, and product teams to implement infrastructure automation, Kubernetes and serverless patterns, observability, and resilient operating practices. This role combines hands‑on cloud engineering with technical leadership, mentoring, and practical architectural guidance that supports business agility, reliability, and cost‑effective innovation.

• 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, Cloud Watch, and Route
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• Experience leveraging AI‑assisted engineering tools (e.g., Git Hub 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 Cloud Formation, 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, Dev Ops, and Git Ops practices using tools such as Jenkins, Git Hub Actions, ArgoCD, Azure Dev Ops, 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.

• 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.
• Build and support Kubernetes and container‑based workloads on AWS, including EKS deployment patterns, Helm‑based releases, ingress, autoscaling, and observability integrations.
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