• Own SLOs, SLIs, and error budgets for all production services; drive error budget discipline across engineering • Design reliability patterns for AI agent pipelines: LLM observability, tool-use tracking, failure detection, and graceful degradation • Architect for blast radius containment — agent failures must have bounded customer impact through isolation, circuit breaking, and rapid recovery • Mature our Canada Central/West active-active architecture toward 24-hour RTO with full regional failover • Lead incident response and post-incident reviews that produce durable fixes; maintain DR procedures through regular testing • Serve as the primary reliability liaison to Software and AI Engineering, translating requirements into actionable standards • Partner with AI Engineering on compute provisioning, model serving, inference latency, and workload isolation • Own CI/CD pipeline strategy (Bitbucket Pipelines, GitHub Actions) — set standards, optimize deployment frequency, and ensure teams can ship confidently • Drive IDP adoption and enable teams on SRE practices: on-call readiness, SLO definition, runbook development, and self-service tooling • Represent reliability in architectural discussions; surface risk before it's committed to design • Own the service catalog — a living inventory of all services, AI agents, dependencies, ownership, and SLOs • Operate Datadog as the single pane of glass for service health, infrastructure, and agentic pipeline telemetry • Extend observability to AI workloads: LLM latency, token consumption, agent completion rates, and pipeline throughput • Build golden path templates in Backstage and/or Atlassian Compass so teams ship reliably without routine SRE involvement • Apply AIOps in Datadog to automate anomaly detection, incident triage, and remediation recommendations • Own infrastructure as code via Terraform and GitOps; enforce IaC policy in partnership with Trust Assurance • Own FinOps visibility into AWS cost segments; model cloud cost impact as AI/ML workloads scale • Formally mentor junior and intermediate SRE engineers, with accountability for their technical growth and career progression • Build AI-assisted automation to progressively reduce toil and scale the team's operational capacity

• Búsqueda del perfil de un Ingeniero/a DevOps para el equipo de mainframe en un cliente del sector bancario. • Proyecto en modalidad full-remote.

• Support deployment and maintenance of scalable infrastructure in AWS and hybrid cloud environments. • Assist in managing infrastructure-as-code (IaC) using Terraform, CloudFormation, or similar tools. • Help maintain Linux-based environments. • Contribute to containerization efforts using Docker and orchestration via Kubernetes. • Work on the design, deployment and management of AI agent workloads. • Monitor AI API consumption and infrastructure costs, implementing alerting and controls. • Manage monitoring and observability efforts using tools such as Prometheus, Grafana, and the ELK stack. • Develop and execute strategies for improving system reliability, performance, and uptime. • Build, maintain, and optimize CI/CD pipelines using tools such as Jenkins, BitBucket CI/CD, or similar. • Follow secure DevOps practices and assist in implementing security controls.

Role Description Buscamos un(a) Ingeniero DevOps con entre 3 y 5 años de experiencia, con perfil generalista de TI y sólidos conocimientos en automatización, administración de sistemas, infraestructura on-premise y cloud, bases de datos, observabilidad y soporte al ciclo de entrega de software. Este rol será clave para construir, operar y evolucionar plataformas escalables, seguras y automatizadas. - Diseñar y mantener plataformas de infraestructura como servicio. - Implementar soluciones de CI/CD para múltiples entornos. - Automatizar despliegues y aprovisionamiento con Infraestructura como Código. - Administrar contenedores y clústeres de Kubernetes. - Monitorear, optimizar y fortalecer el rendimiento de la plataforma. - Implementar políticas de seguridad, gestión de secretos y certificados. - Coordinar con equipos de desarrollo para facilitar el delivery. - Gestionar integraciones con herramientas DevOps y ejecutar troubleshooting en producción. - Documentar procedimientos y buenas prácticas operativas. Qualifications - Experiencia de 3 a 5 años en roles DevOps, infraestructura o automatización. - Conocimiento en Terraform, Bicep, ARM, Ansible o Pulumi. - Manejo de Docker, Kubernetes y Helm. - Experiencia avanzada en Azure DevOps, GitHub y/o Jenkins. - Conocimiento en nube Azure, AWS y/o GCP. - Experiencia con observabilidad: Prometheus, Grafana, Loki, Kibana, Azure Monitor, Application Insights. - Manejo de scripting con PowerShell, Bash o Python. - Conocimiento en Git, GitOps (Flux, ArgoCD). - Gestión de secretos con Key Vault, Vault o SOPS. - Conocimiento en redes, VPNs, conectividad híbrida, Linux, Windows, SQL y KQL. - Manejo de herramientas como Jira, Confluence y deseable experiencia con IDP. Requirements - Pensamiento analítico y resolución de problemas. - Comunicación efectiva con equipos técnicos y no técnicos. - Trabajo autónomo y colaborativo. - Proactividad para identificar y resolver cuellos de botella. - Mentalidad de mejora continua y automatización.