Senior Software Engineer - Together Cloud Infrastructure

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. The Together Cloud team builds the Together GPU Clusters product, which provides high-performance, AI-ready GPU clusters through a self-serve cloud console and is the virtualized infrastructure layer powering Together’s inference, RL, and fine-tuning products. As a Senior Software Engineer in Together Cloud Infrastructure, you will play a key role in building the next generation AI cloud platform – a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs). You'll enable state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters, for both our internal SaaS products (inference, fine-tuning, RL) and our external cloud customers, spanning dozens of data centers across the world. Responsibilities Design, build, and maintain performant, secure, and highly-available backend services/operators that run in our data centers and automate hardware management, such as Infiniband partitioning, in. DC parallel storage provisioning, and VM provisioning. Design and build out the IaaS software layer for a new GB200 data center with thousands of GPUs. Design and build distributed GPU scheduling and the global management plane that power on-demand and managed clusters across dozens of data centers Develop infrastructure that powers our internal inference, RL, and fine-tuning products in addition to external cloud customers Design and build systems that scale per-cluster capacity limits and automate the onboarding of new capacity Work on a global multi-exabyte high-performance object store, serving massive datasets for pretraining and model weights for large-scale inference. Build advanced observability stacks for our customers with automated node lifecycle management for fault-tolerant distributed pretraining and large-scale inference. Perform architecture and research work for decentralized AI workloads Work on the core, open-source Together AI platform Create services, tools, and developer documentation Create testing frameworks for robustness and fault-tolerance To be successful, you’ll need to be deeply technical and possess excellent communication, collaboration, and diplomacy skills. You have strong fundamental software development skills. In addition, you have strong systems knowledge and troubleshooting abilities. Requirements 5+ years of professional software development experience and proficiency in at least one backend programming language (Golang desired) 5+ years experience writing high-performance, well-tested, production quality code, and demonstrated ownership of large-scale projects driven end-to-end to completion Demonstrated experience with building and operating high-performance and/or globally distributed micro-service architectures across one or more cloud providers (AWS, Azure, GCP) Excellent communication skills – able to write clear design docs and work effectively with both technical and non-technical team members Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale Experience building and operating reliable, customer-facing production systems at scale with infrastructure automation tools (Terraform, Ansible), monitoring/observability stacks (Prometheus, Grafana), and CI/CD pipelines (GitHub Actions, ArgoC Preferred Qualifications: Deep experience with Kubernetes internals, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches to Kubernetes itself Deep experience with VMs/hypervisors, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV Deep experience with DC networking tech + solutions, such as…