Full-Time

Senior Frontend Developer

AI Cloud Platform

Evergrid

Evergrid

1-10 employees

Enterprise AI training and inference platform

No salary listed

Remote in USA

Remote

Category
Software Engineering (1)
Required Skills
Graphics Processing Unit (GPU)
Kubernetes
Microsoft Azure
React.js
D3.js
Jupyter
Data Visualization
Computer Networking
TypeScript
AWS
Next.js
Linux/Unix
Databricks
Google Cloud Platform

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Requirements
  • At least 5 years of experience building complex, data-heavy single-page applications using React and TypeScript.
  • Deep proficiency with Next.js for hybrid rendering strategies and performance optimization.
  • Strong data visualization skills using libraries such as D3.js, Recharts, or Visx.
  • Experience building developer tools or infrastructure dashboards.
  • Experience using artificial intelligence in the development workflow.
  • Ability to abstract complex concepts such as virtual GPUs and Kubernetes schedulers into simple user-interface components.
Responsibilities
  • Architect and build the unified web console for managing tenancy, identity, and compute resources.
  • Develop complex provisioning workflows for deploying high-density resources such as bare-metal MI300X clusters and H100 nodes.
  • Implement real-time state management for asynchronous infrastructure events and provisioning, scaling, and recovery states.
  • Build high-performance dashboards visualizing GPU usage metrics, thermal health, and cluster load.
  • Create interactive financial visualizations for compute, storage, and network costs across zones and regions.
  • Design visual topologies showing workload distribution across nodes, racks, and high-performance interconnects.
  • Engineer the frontend experience for Notebooks as a Service to launch and manage data science environments in the browser.
  • Build low-latency web interfaces for Deployment as a Service, including container image selection, replica scaling, and inference configuration.
  • Optimize the user interface for high-frequency real-time updates such as model training progress and inference latency.
Desired Qualifications
  • Experience designing user interfaces for cloud platforms such as AWS, GCP, or Azure, or machine learning operations platforms such as Weights & Biases or Databricks.
  • Familiarity with the Jupyter ecosystem or building integrated development environment-like browser experiences.
  • Basic understanding of Linux and networking concepts.

Evergrid provides a cloud platform for enterprise AI training and inference built on high-performance GPU infrastructure, partnering with AMD to access GPUs such as the MI300X and MI325X. The platform optimizes software, storage, compute, and networking to maximize GPU utilization and ROI for AI workloads, with advanced monitoring and adjustable autoscaling. It differentiates itself with enterprise-grade security and hard multi-tenancy on dedicated nodes plus provisioned networking to ensure data isolation for mission-critical models. The goal is to offer scalable, secure, and cost-controlled AI infrastructure that supports deployment of frontier-scale models for large organizations.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

New York City, New York

Founded

2025

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Simplify's Take

What believers are saying

  • Evergrid’s 2026 documentation shows an operational product, not just a landing page.
  • AMD MI325X support aligns Evergrid with newer accelerator supply and performance improvements.
  • The 2025-2026 blog cadence signals active engineering, technical marketing, and customer education.

What critics are saying

  • On 2026-03-25, AFM warned Evergrid AI is a suspected boiler room fraud.
  • Latka reports no funding for Evergrid.ai as of 2026-06-08, limiting runway confidence.
  • If public customer adoption stays hidden, Evergrid becomes invisible beside hyperscaler and neocloud rivals.

What makes Evergrid unique

  • Evergrid’s 2026 docs promise dedicated AI infrastructure with 24/7 engineer monitoring and 12-minute response SLAs.
  • Its 2025 AMD MoE work claims up to 10x speedups on MI100 and 7x on MI300X.
  • The 2026 service agreement formalizes hard operating terms for enterprise inference customers.

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