V

Vultr

Cloud infrastructure provider offering SSD VPS

GPU Solutions Engineer

Full-Time
$180k - $200k
Senior
Remote in USA
RemoteTravel required 25%.
Solution EngineeringPre-Sales Solution Engineering

About the job

Requirements
  • Experience with structured sales engagement models such as MEDDPIC, Sandler, or BANT.
  • Expertise in the GPU ecosystem, including GPU hardware, bare metal and virtualized cloud delivery, AI and machine learning frameworks, and AI and machine learning operations orchestration.
  • Extensive knowledge of AI models and algorithms, libraries, compilers, and runtimes for diverse silicon ecosystems.
  • GPU benchmarking and workload testing experience.
  • Experience with workload orchestration, Kubernetes, and Slurm.
  • System- and cluster-level understanding of x86 server hardware architecture and Linux operating systems.
  • Hands-on experience with infrastructure as code methodologies, including Terraform and Ansible.
  • Networking experience, including knowledge of InfiniBand, RoCE/UEC Ethernet, or other networking protocols.
  • NCCL/RCCL performance optimization experience.
  • High-performance storage experience and knowledge of performant multi-user offerings, including open-source and commercial off-the-shelf options.
  • At least 5 years of design, implementation, or consulting experience in applications and infrastructure.
  • At least 4 years of solution engineering, sales engineering, professional services, or consulting experience.
  • At least 3 years of experience deploying GPU-based AI, machine learning, and analytics solutions, such as training, inference, fine-tuning, reinforcement learning, and agentic harnesses.
  • Ability to articulate technical and business concepts to diverse stakeholders.
  • Willingness and ability to work through unfamiliar areas to solve complex challenges.
  • Ability to influence, guide, and facilitate stakeholders and peers in decision-making.
Responsibilities
  • Engage collaboratively with customers to understand their objectives.
  • Create solutions and architectures to solve complex customer use cases.
  • Establish relationships within customer organizations independent of account executives.
  • Educate customers on Vultr's value and expand their understanding of possible solutions.
  • Participate in architectural discussions and design exercises to create solutions at Vultr.
  • Collaborate with Engineering and Product Management to deliver customer feedback that guides product and feature development.
  • Lead resolution of complex customer challenges.
  • Partner with Marketing to create reference architectures, white papers, workshops, and demonstrations for internal and external use.
  • Travel 25%.

About the company

Vultr provides cloud infrastructure services that let developers, startups, and enterprises run high-performance cloud servers (SSD VPS), storage, and networking. Its products include cloud compute instances, storage solutions, and networking capabilities, which can be deployed globally in 60 seconds and billed on a subscription (pay-for-use) basis. Customers manage resources through an online dashboard and API, scaling up or down as needed. Vultr differentiates itself by emphasizing fast global deployment, straightforward management, and strong customer support at a competitive price, supported by a large footprint of users and deployed servers. The company’s goal is to simplify cloud computing and offer scalable, reliable infrastructure that is easy to use and cost-effective for a worldwide audience.

Company Size

201-500

Company Stage

Debt Financing

Total Funding

$662M

Headquarters

West Palm Beach, Florida

Founded

2014

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Simplify Jobs

Simplify's Take

What believers are saying

  • $1.2 billion HPE AMD Helios order on September 30, 2026 expands AI capacity.
  • DPIIT and Vultr India signed August 8, 2026, unlocking startup cloud credits and support.
  • VAST, Wasabi, SoftwareOne, and Cycle.io broaden the Cloud Alliance ecosystem in September 2026.

What critics are saying

  • HPE’s $1.2 billion AI deal concentrates Vultr’s growth on one supplier and workload.
  • NVIDIA and HPE dominate Vultr’s AI stack, tightening margins and bargaining power by 2027.
  • AI capex misfires leave Vultr with stranded GPU racks and crushed cash generation.

What makes Vultr unique

  • Vultr’s multi-continent footprint places compute near end users across latency-sensitive markets.
  • The company stayed private and profitable, avoiding public-market pressure and quarterly growth theater.
  • HPE’s June 17 and September 30, 2026 orders validate Vultr’s AI-cloud specialization.

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Benefits

  • Remote Work Options
  • 401(k) Retirement Plan
  • 401(k) Company Match
  • Professional Development Budget
  • Paid Vacation
  • Paid Sick Leave
  • Home Office Stipend
  • Phone/Internet Stipend
  • Gym Membership

Growth & Insights and Company News

Headcount

6 month growth

23%

1 year growth

23%

2 year growth

23%
Yahoo Finance
Oct 19th, 2026
Vultr upgrades platform for enterprise agentic AI with new IAM, VPN and storage tools

Vultr, the world's largest privately owned cloud infrastructure company, has released a batch of platform upgrades to help enterprises run agentic AI. The updates focus on security, cost efficiency, ease of use, and wider access to open-source tools. Key changes include upgraded identity and access management with SCIM support and audit logs that track user and agent activity. Vultr also revamped its interface for provisioning clusters on demand, and added bootable storage for VX1 and Cloud GPU instances. New offerings include a Cloud VPN for securely linking AI workloads to other data centres or devices, and a Vultr app for Slack to manage support tickets. "We need a new class of infrastructure that gives enterprises the best of both worlds," said Kevin Cochrane, chief marketing officer of Vultr. In December 2024, Vultr announced equity financing at a $3.5 billion valuation.

Vultr
Oct 8th, 2026
Building innovative enterprise agentic AI systems on Vultr at the Agent Arena Hackathon.

Building innovative enterprise agentic AI systems on Vultr at the Agent Arena Hackathon. Vultr's composable cloud platform is strengthened by its ecosystem of AI builders and developers. It was on full display recently when Vultr Llc teamed up with Cerebral Valley for the Agent Arena Hackathon in San Francisco. Successful agentic AI relies on two pillars: the agents themselves, and the infrastructure supporting them. Agents have progressed to a point that requires better infrastructure. That was the focus of the Agent Arena Hackathon. Using tools like Vultr Serverless Inference, Vultr Cloud Compute, and VM backends, competitors applied Vultr infrastructure to build production-ready enterprise agentic systems. Here are the three winning projects: Nusa: An agent that rewrites inference kernels for Vultr VX1(TM) Cloud Compute Nusa is a project built to make AI models run faster on the CPU servers that a user already has. Once the user picks a model, Nusa rewrites its slowest kernel to run on a user's exact CPU, then returns the faster version of that model. Nusa is an LLM running on Vultr Serverless Inference. In the hackathon, Nusa tailored models for Vultr VX1 Cloud Compute, reading a profile of the model and rewriting the kernel that took the most time. It's built to run unattended, with every attempt running in a throwaway microVM with no network, and it resulted in up to twice-as-fast decode time on AMD's Llama 3.1 8B. Read more about Nusa, from Alazar Shenkute, here. Skeleton Key: Fast, cheap browser automation for sites with no API Skeleton Key gives agents a way to access the websites you use every day - even the ones without an API. Vultr is the entire control plane, with Vultr Cloud Compute VMs, Vultr VPC, Vultr Serverless Inference, Vultr Container Registry, Vultr Object Storage, and more. If a user wants their agent (such as Claude Code or Codex) to access their Luma account, it can't do so, as Luma lacks an API and MCP. So Skeleton Key turns the website into an API the agent can call: It walks the site, clicks by numbered element IDs, records the site's requests, turns each request into an operation, and runs and verifies the operations in a sandbox. Results can be published as an MCP, REST, OpenAPI spec, and downloadable Python; personal data is redacted. Learn more about Skeleton Key, built by Carl Okpala and Jiyun Park, here. RL Forge: Turn any paper into a reinforcement learning environment With RL Forge, users can upload a paper or specification, and the system builds exercises with a standalone evaluation runtime for the agent to learn through trial and error. RL Forge uses document extraction, task generation, sandbox execution, and reward verification to create an environment where agents learn by doing. It improved accuracy from 2/20 to 5/20 on a mathematics evaluation and improved successful engineering repairs from 3/20 to 7/20 on an eight-turn LEGO bridge environment. Learn more about RL Forge, by Vishnu Vennelakanti, here. These projects all reinforced the great potential of agentic AI - provided it's built on infrastructure that can support it. Vultr provides that critical layer, and Vultr Llc were excited to demonstrate it with the innovative developers and builders who will power the agentic enterprise.

Vultr
Oct 5th, 2026
Vultr at All-In Summit 2026: connecting the future of Enterprise AI Infrastructure.

Vultr at All-In Summit 2026: connecting the future of Enterprise AI Infrastructure. The All-In Summit brought together technology leaders, investors, and operators in Los Angeles to explore AI, infrastructure, and the future of enterprise technology. Bringing partners together. As part of its sponsorship of the Frontier Tech Hub, Vultr brought together six technology partners - HPE, DDN, Moody's, AMD, Qdrant, and LegionEdge - to share perspectives on the technologies and infrastructure shaping enterprise AI. Partner-led sessions explored topics ranging from AI infrastructure and data management to benchmarking and specialized models, and were separate from the All-In Summit's curated main-stage content. Vultr CMO Kevin Cochrane kicked off the sessions with "Beyond Hyperscale: The New Era of Enterprise AI Infrastructure," examining how enterprise AI is moving beyond training toward inference and agentic AI. AMD's Aleks Shargorodskiy discussed AMD's approach to AI infrastructure in the "AMD IS ALL-IN ON AI," covering compute, networking, intelligent systems, and open software. DDN's Brian McCloskey focused on the data behind AI workloads in "The Data Engine Powering the AI Economy," including GPU utilization and the cost of running AI infrastructure. From benchmarks to specialized models. The sessions also looked at some challenges that come once the infrastructure is in place. Qdrant's Daniel Azoulai presented "Enough with the Bad Benchmarks," explaining why Qdrant built a large dataset with deep ground truth to improve benchmarking for vector search. LegionEdge CEO Sean Filimon covered two topics: how memory should work across the different layers around a model, and how specialized models are shaping the next stage of AI development. HPE's Geeta Chhabria discussed "Every Watt, Every Token: HPE's AI Infrastructure Advantage," focusing on the infrastructure needed to run AI efficiently. From AI infrastructure to benchmarking, the conversations at the Vultr Frontier Tech Hub covered a wide range of technologies shaping enterprise AI. Vultr is grateful to its partners for joining Vultr at the All-In Summit and sharing their perspectives with this community. Catch Vultr at another event or get in touch today.

Yahoo Finance
Sep 30th, 2026
HPE shares surge 4.5% on $1.2B Vultr AI deal and raised networking outlook

Hewlett Packard Enterprise shares jumped 4.5% on Wednesday after announcing a $1.2 billion AI systems deal with cloud provider Vultr and raising its networking revenue outlook. The agreement marks the first major order for AMD Helios AI Rack by HPE systems, which will be deployed across Vultr's US data centres. Each rack will integrate 72 AMD Instinct MI455X GPUs alongside HPE's purpose-built switching technology to support Vultr's AI cloud services. HPE also increased its fiscal 2027 networking revenue growth forecast to the high-teens to low-20s percentage range. The company projects data centre networking revenue will grow at a compound annual rate in the 50% range through fiscal 2029, whilst routing revenue is expected to increase in the low-to-high 20s range over the same period.

Yahoo Finance
Sep 30th, 2026
HPE lands first $1.2B AMD Helios order from Vultr to expand AI infrastructure

HPE shares rose over 4% in premarket trading Wednesday after announcing a $1.2 billion order from Vultr for AMD Helios AI Rack systems. The deal marks HPE's first order for the new AMD Helios system and will deploy the infrastructure across Vultr's US data centres. HPE is supplying networking infrastructure, liquid cooling, and deployment services for the systems. Each AMD Helios rack combines 72 AMD Instinct MI455X GPUs with AMD EPYC CPUs and networking cards. The order extends HPE's relationship with Vultr and Juniper Networks following HPE's 2025 acquisition of Juniper. Vultr CEO J.J. Kardwell said demand for high-performance AI infrastructure "continues to outpace available capacity." HPE stock has gained over 150% this year.