Senior Cloud Reliability Engineer — AWS Automation

LexisNexis Risk Solutions; México; Presencial; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

LexisNexis Risk Solutions is seeking an experienced backend engineer to architect and develop backend services and infrastructure tooling. You will leverage AWS cloud capabilities to improve deployment practices, reliability, and incident response, while strengthening the overall engineering culture.

The role emphasizes ownership of services, automation, and collaboration with Support, Product, and Engineering teams. Strong focus on observability and scalable design.

Formación

• Hands-on expertise with AWS cloud services (Lambda, Step Functions, DynamoDB, S3, CloudWatch).
• Strong proficiency in Node.js and Python for backend services.
• Experience implementing observability and reliability patterns; familiarity with CI/CD.

Responsabilidades

• Backend & Infrastructure Ownership: design, build, and maintain backend tools and platforms.
• Service Reliability & Automation: implement automation for incident triage and runbooks.
• Cloud-First Engineering: leverage AWS to build scalable, cost-efficient systems.
• Cross-Team Collaboration: partner with Support, Product, and Engineering teams.
• Engineering Culture: promote code quality, reviews, and deployment best practices.
• Reliability Practices: participate in on-call rotations and post-incident reviews.

Conocimientos

AWS

Node.js

Python

Observability

Reliability

Herramientas

Terraform

CloudFormation

Datadog

Grafana

GitHub Actions

Descripción del empleo

LexisNexis Risk Solutions is seeking an experienced backend engineer to architect and develop backend services and infrastructure tooling. You will leverage AWS cloud capabilities to improve deployment practices, reliability, and incident response, while strengthening the overall engineering culture.

The role emphasizes ownership of services, automation, and collaboration with Support, Product, and Engineering teams. Strong focus on observability and scalable design.