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Emerald AI

Orchestrates AI workloads under grid stress

Distributed Systems Engineer - Backend/Distributed Systems

Backend EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Experience with distributed systems or data-intensive applications.
  • Experience building and operating backend or infrastructure systems with a focus on reliability, performance, and scalability.
  • Interest in grid systems, energy orchestration, and applying artificial intelligence to real-world infrastructure.
  • Experience working on real-time or near-real-time systems.
  • Strong system design skills, including evaluating tradeoffs across latency, consistency, and scalability.
  • Ability to work across the stack when needed to unblock progress.
  • Ability to operate in ambiguous environments and turn open-ended problems into production systems.

Responsibilities

  • Design and scale systems that interact with real-world energy infrastructure.
  • Build high-performance services and application programming interfaces that power core product workflows.
  • Solve problems in reliability, data modeling, and system design.
  • Ship end-to-end features from idea to production.
  • Improve system observability, performance, and fault tolerance.
  • Partner closely with product to turn ambiguous problems into shipped solutions.
  • For senior candidates, drive architecture and technical direction.
  • For senior candidates, lead ambiguous, high-impact initiatives.
  • For senior candidates, mentor and elevate other engineers.

About the Company

Emerald AI

Orchestrates AI workloads under grid stress

Emerald AI builds Emerald Conductor software that optimizes AI data-center workloads by analyzing delay tolerance and grid signals to slow, pause, cap, or shift deferrable tasks during grid stress. It targets compute infrastructure, not just cooling, to free up more than 100 GW of unused U.S. grid capacity for AI growth without building new generation or transmission. The system uses policy-driven actions to re-time or throttle deferrable jobs based on workload tolerance and grid conditions, demonstrated in field tests such as a May 2025 Phoenix demo where a 256-GPU cluster’s base load fell about 25% for three hours. Emerald differentiates itself through compute-side demand management and partnerships with Nvidia, Oracle, Nebius, EPRI, National Grid and more, aiming to expand flexible grid capacity for AI with real-time coordination and strong investor support.

Company size
51-200
Company stage
Series A
Total funding
$217.5M
Headquarters
Washington DC, District of Columbia
Founded
2025

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