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Together AI

Senior Software Engineer - AI Compute, Together Cloud

Together AI is hiring a Senior Software Engineer - AI Compute, Together Cloud in Amsterdam, Netherlands. Level rates it ; you can apply on Together AI.

Level's read on this job

  • Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include Cursor, Elevenlabs and Decagon.
  • Level classifies it as a senior role.
  • Level lists 77 other open roles at Together AI.

AI in this role

CursorElevenlabsDecagon
fine-tuning

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 GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products.

As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs.

The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch.

Responsibilities

  • Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-performance, portable, and strongly isolated across heterogeneous hardware.
  • Build and maintain our in-DC IaaS layer: the services, Kubernetes operators, and libraries that provision and manage compute, storage, and networks in our data centers, including VMs, parallel filesystems, VPCs, and InfiniBand partitions. Implement and harden the bring-up path for a new Vera Rubin data center with thousands of GPUs.
  • Scale the distributed GPU scheduling and global management plane: the control-plane services behind on-demand and reserved clusters, including the automation that onboards new capacity and raises per-cluster limits.
  • Harden the monitoring and automated remediation layer for fault tolerance: automated detection, isolation, and recovery of failed nodes that keeps distributed pretraining and large-scale inference fault-tolerant.
  • Own your components end-to-end: write the design docs, break the work into milestones that ship incrementally, and improve the reliability of what's already in production.
  • Raise the bar around you: code review, design feedback, and mentoring junior engineers.
  • Build the tooling other teams rely on: testing frameworks, developer tools, and documentation that make our systems robust and usable across teams, plus contributions to the core, open-source Together AI platform.

To be successful, you'll need to be deeply technical, ready to own projects truly end-to-end, and an excellent communicator — strong software development fundamentals, strong systems knowledge and troubleshooting instincts, and the collaboration and diplomacy skills to work across teams.

Requirements

  • 5+ years of professional software development experience, with strong proficiency in at least one backend programming language (Golang desired).
  • Demonstrated ownership of large-scale projects driven end-to-end to completion, writing high-performance, well-tested, production-quality code.
  • Demonstrated experience building and operating high-performance and/or globally distributed micro-service architectures across one or more cloud providers (AWS, Azure, GCP).
  • Strong systems knowledge across compute, networking, and storage, including concurrency, memory management, performant I/O, and scale.
  • Excellent communication skills — able to write clear design docs and work effectively with both technical and non-technical team members.
  • 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.

Preferred Qualifications:

  • Proficiency with Kubernetes internals, such as implementing non-trivial Kubernetes operators, device/storage/network plugins, custom schedulers, or patches to Kubernetes itself
  • Proficiency with VMs/hypervisors, such as QEMU/KVM, cloud-hypervisor, VFIO, virtio, PCIE passthrough, Kubevirt, SR-IOV
  • Proficiency with DC networking tech + solutions, such as VLAN, VXLAN, VPN, VPC, OVS/OVN
  • Experience with Cluster API or similar
  • Experience working on high-performance compute, networking, and/or storage
  • Experience virtualizing GPUs and/or InfiniBand
  • Experience building IaaS or PaaS systems at scale
  • Experience with DPUs/SmartNICs
  • GPU programming, NCCL, CUDA knowledge

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Application Policy

Please read each role carefully and apply to the position best suited to you. Candidates are limited to 6 applications within a 90-day period, and applications beyond that limit will be automatically rejected. You may apply to additional roles 90 days after your last application.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

How we rate this

Senior Software Engineer - AI Compute, Together Cloud at Together AI rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningCursorElevenlabsDecagon

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Walk me through how you've used Cursor in your day-to-day work.
  3. What are the limits of Elevenlabs that you've run into, and how did you work around them?
  4. What's a project where you used Decagon hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Fine-tuning, Cursor, Elevenlabs, and Decagon. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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