V

Vultr

Cloud infrastructure provider offering SSD VPS

Procurement Analyst

Full-TimePosted on 7/6/2026
$75k - $85k
Mid
Bachelor's
Remote in USA
Remote
Operations & LogisticsProcurement & Sourcing

About the job

Requirements
  • A Bachelor's degree in Business, Supply Chain, Finance, or a related field is required.
  • Two to four years of experience in procurement, supply chain, or strategic sourcing is required.
  • Proficiency with procurement or enterprise resource planning systems, such as Coupa, SAP Ariba, or NetSuite, is required.
  • Strong analytical skills and experience with Excel, Google Sheets, or business intelligence tools such as Tableau or Looker are required.
  • Attention to detail, strong organizational and time management skills, written and verbal communication skills, collaboration, and the ability to manage large data sets, multiple priorities, and deadlines are required.
Responsibilities
  • Analyze procurement data to identify cost savings, supplier consolidation opportunities, and process inefficiencies across hardware, software, and services categories.
  • Maintain and update procurement databases, vendor records, and contract repositories to ensure accuracy and accessibility.
  • Support request for proposal and request for quotation processes by collecting and comparing vendor proposals, pricing, and technical specifications.
  • Track and report key procurement performance indicators, including spend under management, realized savings, and purchase order cycle times.
  • Coordinate with Finance on purchase requisition approvals, invoice reconciliation, and budget tracking.
  • Assist with supplier onboarding, due diligence documentation, and performance scorecards.
  • Develop and maintain procurement dashboards and reporting using enterprise resource planning and analytics tools.
  • Support contract management activities, including tracking renewal dates, compliance milestones, and deliverable schedules.
  • Collaborate with technical teams to translate hardware and infrastructure requirements into actionable procurement specifications.
Desired Qualifications
  • Understanding of hardware procurement in data center or hyperscale environments.
  • Experience in a fast-paced, high-growth technology or infrastructure company.
  • Familiarity with GPU, networking, or data center hardware supply chains.
  • CPSM or CSCP certification in progress or completed.

About the company

V

Vultr

View
cbWebsite

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

Get referred to Vultr

See people who can refer or advise you

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.

Help us improve and share your feedback! Did you find this helpful?

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

6 month growth

27%

1 year growth

23%

2 year growth

23%
Digital Terminal
Oct 21st, 2026
Vultr to Deploy AMD Instinct MI355X GPUs in 20 MW Chennai AI Supercluster.

Vultr to Deploy AMD Instinct MI355X GPUs in 20 MW Chennai AI Supercluster. The Chennai deployment extends that collaboration as AMD and Vultr expand access to advanced AI infrastructure through Vultr's global cloud footprint. Published on: 21 Oct 2026, 4:04 am Vultr announced a major expansion of its AMD powered infrastructure for enterprise and sovereign cloud initiatives. Vultr will deploy AMD Instinct(TM) MI355X GPUs in a new 20 MW supercluster in Chennai, India, creating the country's largest AMD Instinct deployment and giving Vultr two of the world's largest AMD AI infrastructure deployments globally, alongside its flagship supercluster in Springfield, Ohio. With 288GB of HBM3E memory and 8TB/s of memory bandwidth per GPU, AMD Instinct MI355X GPUs provide the performance and memory capacity required to develop and deploy increasingly complex AI models at scale. The Chennai supercluster is designed to serve AI labs and foundation model builders, AI-native startups, enterprises, and research and academic institutions. It will support demanding AI workloads including large language model and foundation model training, fine-tuning and high-throughput inference, providing the compute capacity organizations need to develop and deploy AI at scale. "Enterprises deploying AI at scale need infrastructure they can access locally to meet data sovereignty, data residency, and latency requirements," said J.J. Kardwell, CEO of Vultr. "Vultr's Chennai supercluster, powered by AMD MI355X GPUs, gives organizations in India the capacity to train, fine-tune, and run inference on in-country infrastructure." Vultr's longstanding relationship with AMD spans the AMD Instinct GPU roadmap, from MI300X and MI325X to MI355X and the planned MI455X and AMD Helios rack-scale architecture, together with the AMD EPYC data center CPUs that power Vultr VX1 Cloud Compute. The Chennai deployment extends that collaboration as AMD and Vultr expand access to advanced AI infrastructure through Vultr's global cloud footprint. Looking ahead, Vultr plans significant additional capacity expansion in 2027, including AMD Instinct(TM) MI455X GPUs and the AMD Helios(TM) rack-scale AI architecture, broadening global access to next-generation AI infrastructure. The Chennai supercluster will also leverage the AMD ROCm(TM) open software ecosystem, giving developers access to widely used AI frameworks, libraries and models, with greater flexibility and choice in how they develop and deploy AI workloads. The open software approach also supports AI innovation in India through open-source software and community-driven development. "India has the talent and ideas to build the next generation of AI. Access to compute at this scale will help turn more of those ideas into reality," said Jaya Jagadish, Country Head & SVP Engineering, AMD India. "Through our collaboration with Vultr, we're expanding access to AMD Instinct compute in India, backed by the AMD ROCm open software ecosystem, giving researchers, startups and enterprises greater choice and flexibility in how they develop and deploy AI." The launch comes as demand for sovereign cloud infrastructure is rising globally. Security concerns, regulatory requirements and performance expectations are intensifying the need for in-country infrastructure that can support advanced AI workloads. With 34 global cloud data center regions, Vultr provides secure, compliant infrastructure at a predictable cost to enterprises, AI innovators, and government agencies in 17 countries across six continents. The Chennai deployment reflects a broader shift toward geographically-distributed AI infrastructure, bringing large-scale compute closer to where data is created and AI applications are deployed. [Stay informed with our latest updates by joining the] [WhatsApp Channel now!]

Data Center Dynamics
Oct 21st, 2026
Vultr to deploy 20MW AMD MI355X cluster in Chennai, India.

Vultr to deploy 20MW AMD MI355X cluster in Chennai, India. Says it will be the country's largest AMD Instinct deployment October 21, 2026 Vultr is planning to deploy a 20MW cluster of AMD Instinct MI355X GPUs in Chennai, India. The privately owned cloud company claims this will be the country's largest AMD Instinct deployment. It would give Vultr two large AMD clusters, following a similar deployment in Springfield, Ohio. "Enterprises deploying AI at scale need infrastructure they can access locally to meet data sovereignty, data residency, and latency requirements," said J.J. Kardwell, CEO of Vultr. "Vultr's Chennai supercluster, powered by AMD MI355X GPUs, gives organizations in India the capacity to train, fine-tune, and run inference on in-country infrastructure." The AMD Instinct MI335X is built on the 4th Gen AMD CDNA architecture. The chips have 288GB of HBM3E memory, 8TBps bandwidth, and support for advanced data types like FP6 and FP4 - accelerating AI training, inference, and scientific simulation. "India has the talent and ideas to build the next generation of AI. Access to compute at this scale will help turn more of those ideas into reality," added Jaya Jagadish, country head & SVP engineering, AMD India. "Through our collaboration with Vultr, we're expanding access to AMD Instinct compute in India, backed by the AMD ROCm open software ecosystem, giving researchers, startups and enterprises greater choice and flexibility in how they develop and deploy AI." The company has not disclosed which data center the capacity will be deployed in. Operators in the area include Digital Realty, Equinix, Sify Technologies, CtrlS, NTT Data, CapitaLand, and Iron Mountain. Vultr has an ongoing relationship with AMD, which has previously seen the cloud provider deploy the chip firm's MI325X and MI355X GPUs, the latter becoming available in September 2025. In July 026, Vultr added the MI455X GPUs to its platform, for which it plans to expand capacity in 2027. Vultr currently has 34 global cloud data center regions. The company opened a Mumbai cloud region in 2022, and the Chennai region launched earlier this week. More in cloud & hyperscale.

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.

INACTIVE