• Collaborate with infrastructure to design and build scalable SDN orchestration systems leveraging NVIDIA Bluefield-3 DPUs to deliver programmable, high-performance networking for AI workloads with hardware-accelerated forwarding isolation. • Design and implement networking systems for research computing environments including Kubernetes and SLURM clusters, enabling high-performance connectivity, optimized network topology for distributed workloads, and seamless integration with cluster orchestration systems. • Implement automated SDN provisioning systems that handle VPC creation, subnet allocation, routing configuration, and network resource lifecycle from deployment through decommissioning. • Develop platform capabilities for managing Bluefield-3 DPUs including SR-IOV virtual function management, OVS offload configuration, network function deployment, and integration with compute orchestration systems. • Build enterprise-grade network isolation using VPCs, VXLAN, and hardware-accelerated forwarding to ensure complete tenant separation while maintaining high-performance connectivity for GPU clusters and distributed workloads. • Collaborate with infrastructure to optimize network paths for RDMA, RoCE, and GPU-to-GPU communication, ensuring minimal latency and maximum throughput for distributed training and large-scale computational workloads. • Develop robust APIs and SDKs for network resource management that integrate seamlessly with compute and storage platforms, enabling programmatic network provisioning and configuration. • Implement comprehensive network monitoring, telemetry, and troubleshooting systems that provide visibility into network performance, utilization, and tenant traffic patterns. • Build platform network security features including security groups, firewall rules, and policy enforcement that protect tenant workloads while enabling flexible network configuration.

• Design and build scalable compute orchestration platforms that manage GPU clusters, bare-metal server provisioning, and resource allocation across co-located infrastructure environments. • Implement intelligent workload scheduling, resource allocation, and optimization algorithms that maximize GPU utilization while maintaining performance guarantees for research and training workloads. • Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads. • Develop platform capabilities for managing latest-generation NVIDIA GPU configurations (H100, H200, B200, B300), including GPU resource management, multi-tenant isolation, and integration with compute orchestration systems. • Build automation and tooling for complete bare-metal server lifecycle management – from initial provisioning and configuration through ongoing operations, updates, and resource reallocation. • Optimize compute platform components for high-throughput and low-latency performance, ensuring research workloads achieve near-bare-metal efficiency in virtualized or containersized environments. • Develop robust APIs and SDKs that enable researchers to programmatically provision and manage compute resources, integrating seamlessly with existing workflows and research infrastructure. • Implement comprehensive monitoring and telemetry systems for compute resources, providing visibility into GPU virtualization, workload performance and infrastructure health. • Build enterprise-grade multi-tenant compute isolation, security boundaries, and resource quotas that enable safe sharing of GPU infrastructure across teams and organizations.

• Develop independent microservices that solve domain-specific problems (users, vehicles, debts, payments, etc.). • Responsible for the entire code development lifecycle, from planning with the product team (pre-code) through production deployment and monitoring its impacts (post-code). • Troubleshoot and contribute to the challenges of the technology and product teams by sharing ideas, solutions, code, architectures, etc. • Improve the software development experience within the company, including tools, test coverage, code structure, and more. • Actively participate in software design discussions and decisions, taking the lead and helping to create documentation. • Create scalable, sustainable, and user-focused solutions. We use technologies such as Node.js, Python, React Native, Flutter, and PostgreSQL. You don’t need prior experience with all of them, but you should be open to learning them. • Help structure the software architecture to harmoniously orchestrate our services.

• Delegate tasks and assignments to the technical team, providing the necessary support for them to grow quickly from a technical perspective and become high-performing • Conduct regular 1:1 meetings with your technical team • Develop independent microservices that solve domain-specific problems (user, vehicle, debts, payments, etc.) • Responsible for the entire code development lifecycle, from planning together with the product team (pre-code) to deploying to production and monitoring the impact (post-code) • Lead problem resolution and actively contribute to the challenges of the technology and product teams, sharing ideas, solutions, code, architectures, etc. • Improve the software development experience at Gringo, considering tools, test coverage, code structure, etc. • Actively participate in software design discussions and decisions. Take the lead and help create documentation • Build scalable, sustainable, and user-focused solutions. We use technologies such as Python, Node.js, React, PostgreSQL. You don’t need to know all of these technologies, but you should be open to learning them • Help organize the software architecture to harmoniously orchestrate our service architecture • Conduct security and structural audits to identify opportunities for improvement.