Top Tech Jobs & Startup Jobs in Dublin

Lead and drive cross-team technical projects across engineering domains (incident, capacity, runtime infra). Align stakeholders including C-level, facilitate technical decisions, establish scalable processes, and collaborate with engineering, infrastructure, and business teams.

Design and implement cloud infrastructure and MLOps solutions for ML/AI customers. Advise clients, run PoCs and workshops, create IaC and technical documentation, optimize GPU training/inference pipelines, and act as primary technical liaison across product, support, and marketing teams.

Serve as the primary technical advisor for strategic GPU cloud customers: troubleshoot complex AI/ML issues, optimize GPU performance, guide deployments at scale, collaborate with sales and product teams, and translate customer needs into product feedback and solutions.

Administer and improve the Atlassian Cloud ecosystem (Jira, Confluence, Assets, Statuspage), design workflows and automations, manage SSO/SCIM with Azure Entra ID, integrate via APIs/webhooks, ensure SaaS governance and security compliance, monitor performance, document configurations, and provide user support and training across enterprise teams.

Lead performance analysis and optimization of large-scale GPU/HPC clusters across hardware and software stacks. Troubleshoot real workloads, qualify and integrate new hardware, tune system configurations (networking, virtualization, kernel), support escalations, and collaborate with infrastructure teams and hardware vendors to ensure cluster performance meets expectations.

Lead and coordinate large-scale cloud platform programs across many teams, set goals and timelines, drive technical and procedural decisions, introduce reproducible processes, and align stakeholders up to C-level to scale regions and hardware generations.

Own product direction for Soperator, a Slurm-on-Kubernetes control plane for GPU clusters. Drive discovery, design, delivery and adoption; lead customer research; prioritize roadmap and metrics; coordinate across compute, storage, networking, observability and IAM teams; lead open-source strategy and community adoption.

Maintain and scale DevTools SRE systems: improve user-facing developer workflows, build fault-tolerant self-healing architecture, optimize performance, modify open- and closed-source tools (GitLab, TeamCity), and support users while measuring improvements via metrics.

Build and maintain a distributed, fault-tolerant, high-performance block and filesystem storage system. Work on virtualization (virtio-blk, virtio-fs, QEMU, vhost-user), high-throughput VM-to-storage networking (TCP, RoCEv2/RDMA), and core storage features like replication, consensus, self-healing, and data migration. Debug and optimize performance-critical I/O paths while writing reliable, maintainable code in a collaborative team environment.

Serve as primary technical advisor for strategic GPU cloud customers, guiding design, deployment, and scaling of large-scale ML training and inference workloads. Troubleshoot complex AI/ML issues, optimize GPU performance, liaise with sales and product teams, and drive customer-aligned feature requests and solutions.