> Markdown version of [/jobs/ext/3700321-hpc-architect](https://www.wearedevelopers.com/jobs/ext/3700321-hpc-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # HPC Architect - **Company:** Quantori - **Location:** Spain - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Amazon Elastic Compute Cloud, Microsoft Azure, Data Architecture, Extract Transform Load (ETL), Data Security, File Systems, General Parallel File Systems, MATLAB, Peering, Scientific Computating, Network Switches, Google Cloud, Cloud Platform System, High Performance Computing, Jupyter, Amazon Virtual Private Cloud (VPC), Slurm, Cloud Integration - **Published:** October 12, 2026 - **Apply:** https://www.jobleads.com/es/job/hpc-architect--spain--ecb7d2b41852339fcf66892fa1093ecac ## About the Role * Knowledge of HPC-with-cloud integration strategies, experience with technical feasibility planning * Strong understanding of regulated enterprise R&D environments * Understanding scientific computing reproducibility requirements, relying on enterprise standard tooling. * Deep understanding of Amazon VPC /Google Cloud / Azure networking, peering and security group configurations. Nice to have: * Experience in life-sciences * Experience in specific applications in life sciences, Jupyter, Matlab ## Description Location: Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities: * Hybrid Architecture Design: Architect and deploy scalable HPC clusters using on-prem and/or cloud-native HPC cluster managers ( e.g., AWS ParallelCluster + Amazon EC2 / Azure CycleCloud + Azure VM Scale Sets / Google Cloud Cluster Toolkit or similar + Compute Engine), ensuring seamless integration with on-premises schedulers. Proven expertise with HPC schedulers and orchestration patterns (e.g., Slurm, cloud HPC cluster orchestration, batch orchestration) * Design and optimize data architectures for large-scale HPC workloads, including high-throughput data movement between on-premises and cloud environments and integration with parallel file systems. Ensure data access, lifecycle, and reproducibility patterns to support scientific computing performance and operational requirements. * Design and implement high-performance networking solutions, including private dedicated connectivity and low-latency HPC interconnects (e.g., AWS Direct Connect / Azure ExpressRoute / Google Cloud Interconnect; AWS EFA / Azure HPC fabrics e.g. IB/ GCP HPC interconnect options etc.), to support low-latency MPI applications. Design high I/O workloads (parallel file system patterns) (e.g., AWS / GCP / Azure Managed Lustre or parallel FS deployments and/or self-managed Lustre/GPFS/BeeGFS), observability, reproducibility and operational excellence * Define and maintain containerization standards using containerization and related technologies to ensure binary compatibility across heterogeneous hardware and environments. What we expect: * Knowledge of HPC-with-cloud integration strategies, experience with technical feasibility planning * Strong understanding of regulated enterprise R&D environments * Understanding scientific computing reproducibility requirements, relying on enterprise standard tooling. * Deep understanding of Amazon VPC /Google Cloud / Azure networking, peering and security group configurations. Nice to have: * Experience in life-sciences * Experience in specific applications in life sciences, Jupyter, Matlab We offer: * Competitive compensation * Remote or office work * Healthcare benefits: medical insurance and paid sick leave * Continuous education, mentoring, and professional development programs