Top Tech Jobs & Startup Jobs in Dublin

Lead Infrastructure Engineer designs, implements, and modernizes infrastructure for performance, resiliency, and security. Responsibilities include cloud and on-prem migrations, Kubernetes and cloud-native app administration, data streaming (Kafka/Event Grid/Service Bus), scripting and CI/CD automation, AI-assisted infrastructure analysis, and cross-functional collaboration to deliver traceable, auditable infrastructure changes.

Lead design and implementation of secure data management in public cloud. Perform risk-based assessments for Data & AI/ML services, review infrastructure-as-code, advise engineering teams on controls, integrate with security operations, and mentor junior staff to maintain robust cloud security.

Lead design and implement reliability, scalability, and observability for cloud and data platforms. Build IaC, CI/CD pipelines, use monitoring and SLO-driven improvements, apply enterprise AI for incident triage and reliability insights, and collaborate across teams to reduce toil and improve operational outcomes.

Lead and mentor SRE practices to design, implement, and operate reliable cloud and data platforms. Build IaC, CI/CD, observability, and containerized deployments; use enterprise AI to accelerate incident triage and reliability improvements while ensuring compliance and data sensitivity controls.

Lead design and build production software for enterprise-scale reliability: automation, control loops, self-healing, SLI/SLO definition and alerting, observability, incident leadership, on-call ownership, toil reduction, and AI-native engineering across the SDLC while ensuring security, performance, and cost control.

Lead and manage an engineering team to design, build, and operate scalable data integration and processing solutions using Databricks/Spark, AWS data services, Kafka streaming, and CI/CD tooling. Collaborate with cross-functional and distributed teams to deliver secure, high-performance data pipelines and analytics-ready platforms.

Lead a global security engineering organization to design, deliver, and operate enterprise-scale AI-powered security platforms. Own strategy, lifecycle, and adoption of cloud-native security and Data & AI/ML controls, partner with product and infrastructure teams, manage staffing and budget, and drive risk-based assessments for cloud Data & AI services.

Bridge product owners, business, operations, and developers to elicit and document business and data-flow requirements, translate them into technical solutions, perform data analysis and BI reporting, support architecture and governance, maintain healthy product backlogs, and facilitate sprint planning and stakeholder communication.

Provide independent oversight of technology and cybersecurity risk for Employee Platforms. Conduct technical risk assessments and threat model reviews, identify and drive remediation of control gaps, assess third‑party and cloud risks, monitor incidents, integrate AI/LLM toolsets into assessments, and collaborate with stakeholders to ensure compliance with policies and regulatory standards.

Lead and coach data engineering teams to onboard enterprise datasets into Palmos and deliver scalable Databricks/Spark pipelines. Drive adoption of data mesh and lakehouse patterns, enforce governance, security, observability, and SDLC best practices, and enable analytics and AI/ML use cases through high-quality, reusable data products.