Staff Software Engineer (AI Compute, Together Cloud)

Together AI, a company dedicated to building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle. As a Staff Software Engineer focusing on AI Compute, you will set the technical direction and build major components of the next generation AI cloud platform. This role involves architecting and building a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware. You will also own the GPU and network virtualization stack, the in-DC IaaS layer, and the GPU scheduling and global management plane. Additionally, you will mentor and grow the team, set the engineering bar, and drive projects from ambiguity to production.

Set technical direction and build major components of the next generation AI cloud platform, focusing on high availability and cutting-edge virtualization of ML hardware.

Own the GPU and network virtualization stack, architect and roadmap the services, Kubernetes operators, and libraries that provision and manage compute, storage, and networks in data centers.

To be successful you'll need to be deeply technical and an excellent communicator — expert software development fundamentals, deep systems knowledge and troubleshooting instincts, and the leadership and diplomacy skills to align teams that don't report to you

Responsibilities

• Lead design reviews, resolve cross-cutting architectural disagreements, unblock cross-team dependencies, and define the standards other engineers build against.
• Track record of owning the architecture of large distributed systems from blank page to production at scale, including the judgment calls that could not be reversed cheaply

Requirements

• 7+ years of professional software development experience, with expert-level proficiency in at least one backend language (Golang desired), writing high-performance, well-tested, production-quality code
• Excellent communication and diplomacy skills — able to write design docs that settle arguments, and to work effectively with technical and non-technical stakeholders
• Demonstrated technical leadership beyond your own commits: mentoring senior engineers, leading design reviews, and driving alignment across teams that do not report to you
• Experience building and operating reliable, customer-facing production systems at scale, and owning the infrastructure automation (Terraform, Ansible), observability (Prometheus, Grafana), and CI/CD (GitHub Actions, ArgoCD) that keep them healthy
• Deep experience building and operating globally distributed, high-performance microservice architectures across one or more cloud providers (AWS, Azure, GCP)
• Expert systems knowledge across compute, networking, and storage — including concurrency, memory management, performant I/O, and scale at a global level
• Deep Kubernetes internals experience, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches to Kubernetes itself
• Experience working on high-performance compute, networking, and/or storage
• Experience building IaaS or PaaS systems at scale

Preferred

• 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 VLAN, VXLAN, VPN, VPC, OVS/OVN
• Experience with Cluster API or similar
• Experience virtualizing GPUs and/or InfiniBand
• Experience with DPUs/SmartNICs
• GPU programming, NCCL, CUDA knowledge