---
title: 'Member of Technical Staff - AI Cloud Infrastructure at Emerald AI'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ai-cloud-infrastructure-emerald-ai-san-francisco-tpd56704ythb'
type: 'job'
last_seen: '2026-09-13'
---

# Member of Technical Staff - AI Cloud Infrastructure at Emerald AI

- **Company:** Emerald AI
- **Location:** San Francisco, CA / San Jose, CA / Oakland, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-05
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/emerald-ai/85bf88c8-e91c-4463-b5ad-e885b8dfaf11

## Job description

## About Emerald AI

We’re at a pivotal moment for AI and energy. Demand for compute is skyrocketing, but power constraints are becoming a critical bottleneck. Emerald AI sits at the intersection of these two worlds, enabling AI data centers to scale without overwhelming the grid. Our Emerald Conductor software platform makes data centers flexible and responsive, allowing them to adjust power usage dynamically. This unlocks massive AI growth without major new infrastructure, while also strengthening the grid and supporting the expansion of renewable energy. We’re a team of experts across AI, cloud, software, and energy—on a mission to scale AI sustainably. We’re backed by leading investors and partners including Radical Ventures and NVIDIA. Learn more about our vision, team, and backers athttps://www.emeraldai.co/.

## About the Role

Emerald AI is building the world's first power flexible managed cloud infrastructure. We are hiring a senior infrastructure engineer to architect and stand up our managed cloud services from end to end. The work covers the platform, the control plane, and the customer experience that together make up a managed AI cloud. The right person has done this before. They have built or served as a core early engineer on a managed cloud or AI platform, whether at a GPU cloud, an internal machine learning platform run at scale, a hyperscaler AI service, or a HPC research computing center operated as a service. This is a role for an architect who still builds. You will make the major design decisions and then implement them yourself.

## Key Responsibilities

- Architect our managed services from 0→1. Define the productization of GPU capacity, encompassing isolation boundaries, tenant models, provisioning flows, and service catalogs that scale across diverse providers.
- Engineer the platform core. Build robust control-plane services, self-service customer interfaces, and automated lifecycle systems, including usage metering integrated with billing infrastructure.
- Onboard and vet infrastructure partners. Conduct deep technical assessments of bare-metal GPU vendors, evaluating fabric quality, network isolation, and economics to automate the path from handoff to active tenant.
- Design end-to-end multi-tenancy. Implement rigorous isolation across compute, storage, and networking (InfiniBand/VLANs), ensuring secure boundaries, QoS, and encryption even when customers possess root access.
- Drive workload orchestration. Manage Kubernetes and Slurm environments for large-scale training and inference, overseeing node health, driver fleets, and kernel management across heterogeneous clouds.
- Lead high-performance storage strategy. Deploy and integrate parallel storage solutions like Lustre, VAST, or Weka, leveraging your deep experience with these systems to ensure they fold cleanly into our provisioning model.
- Ensure operational excellence. Define SLOs, observability standards, and incident response protocols that bridge our internal standards with underlying provider SLAs to deliver a reliable, sellable product.

## Minimum requirements

- At least 7+ years of experience in infrastructure or platform engineering, including the architecture and launch of a managed cloud or AI platform that reached production users.
- Strong experience with Kubernetes and Slurm and offering them as managed service
- Production experience deploying or operating Lustre or a comparable parallel filesystem such as GPFS, Weka, VAST, or BeeGFS, with a solid understanding of parallel filesystem architecture, tuning, and failure modes.
- A strong grasp of cloud service fundamentals, including control planes, tenancy and isolation models, APIs, quota and metering systems, and the operational discipline of running a service that customers pay for.
- Deep Linux systems knowledge, mature infrastructure as code practice with tools such as Terraform and Ansible, and solid programming ability in Python or Go.
- Familiarity with GPU infrastructure, including high performance networking with InfiniBand, RoCE, and RDMA, and the GPU software stack.

## Preferred requirements

- Prior time at a GPU cloud, a hyperscaler AI service, or an HPC center that delivers compute and storage as a service, especially one built on rented or colocated capacity.
- Familiarity with NVIDIA reference architectures such as SuperPOD, along with GPUDirect Storage, NCCL debugging, and DCGM.
- Experience with Lustre multitenancy features such as nodemap, fileset mounts, and Kerberos, or with service provider deployments of VAST or Weka.
- Experience negotiating with and integrating multiple infrastructure vendors, together with a practice of designing for portability between them.
- Experience running object storage at scale with systems such as S3, Ceph, or MinIO, including the design of data tiering.
- Experience building billing, metering, or FinOps pipelines for services that charge by usage.

## What We Offer

- Make an impact. Solve the AI power bottleneck and shape how data centers scale sustainably.
- Join a world-class team of AI, cloud, software, and energy experts in a collaborative, low-ego environment.
- Build from 0→1. Influence strategy, GTM, org design, and customer/investor engagement from day one.
- Competitive pay + equity. Stock options let you share in the value you help create.
- Comprehensive benefits, including medical, dental, vision, and 401(k) matching.
- Flexible location. Work from D.C., Boston, or the Bay Area, with 2 WFH days/week.
- Backed by top investors, including Radical Ventures and NVIDIA.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability, and any other protected ground of discrimination under applicable human rights legislation. Emerald AI strives to respect the dignity and ‎independence of people with disabilities and is committed to giving them the same ‎‎opportunity to succeed as all other employees. Inclusiveness is core to our culture at Emerald AI, and we strive to ensure you get the most from your interview experience. Emerald AI makes reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to the Talent team.

## About Emerald AI

## Company Overview
- **One-liner**: Emerald AI provides a platform that orchestrates AI data center workloads and onsite energy resources to enable power grids to use data centers as flexible, responsive assets.
- **Entity Type**: Private (Seed/Strategic Expansion)
- **Headquarters**: Washington, D.C., United States
- **Founded**: 2024
- **Founders**: Dr. Varun Sivaram (CEO)

## Core Business
- **Primary industry/industries**: Energy Technology, AI Infrastructure, Grid Flexibility
- **Target customers**: AI Innovators & Cloud Providers, Data Center Developers & Operators, Utilities, Regulators & Policymakers
- **Mission or purpose statement**: To solve the defining infrastructure challenge of our time by making AI data centers flexible grid allies, enabling AI innovation to grow in harmony with stronger, more affordable grids.

## Products & Services
- **[Emerald Conductor Platform](https://www.emeraldai.co/)**: An intelligent interface between power grids and data centers. It provides real-time connectivity, digital twin simulation, workload orchestration, and performance verification. The platform offers three types of flexibility:
    - **Temporal AI Flexibility**: Briefly slowing or pausing batchable AI workloads (e.g., fine-tuning) when the grid is stressed, then resuming within SLA guardrails.
    - **Spatial AI Flexibility**: Shifting workloads across data centers in different regions (e.g., from Virginia to Chicago) to where power is abundant, within latency bounds.
    - **Resource Flexibility**: Dispatching onsite batteries and other energy resources alongside compute orchestration for maximum, reliable flexibility.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding of **$68 million** as of March 2026 (raised in just 16 months since founding).
    - **Strategic Expansion Round (March 2026)**: $25 million, led by Energy Impact Partners (EIP), with participation from Amplo, Eaton, GE Vernova, IQT (In-Q-Tel), Lowercarbon Capital, NVentures (NVIDIA’s VC arm), Radical Ventures, Salesforce Ventures, Samsung Ventures, Siemens, and others. [emeraldai.co](https://www.emeraldai.co/blog/sharing-our-strategic-expansion-round-emerald-ai-raises-25-million-to-transform-ai-data-centers-into-flexible-power-grid-assets)
    - **Prior Seed Round (July 2025)**: $34.2 million, led by Radical Ventures.
    - **Corporate Rounds**: Led by Siemens Smart Infrastructure (March 2026) and National Grid (October 2025).
- **Notable Investors/Partners**: NVIDIA, Digital Realty, EPRI, PJM Interconnection, Siemens, National Grid, Energy Impact Partners, Lowercarbon Capital, Salesforce Ventures, Samsung Ventures, GE Vernova, Eaton, AES, Constellation, Invenergy, NextEra Energy, Nscale Energy & Power, Vistra.
- **Growth Signals**:
    - **Headcount**: 34 employees (as of mid-2026), with a monthly growth rate of +2.6% and a quarterly job posting growth of +61.1%. [linkedin.com](https://www.linkedin.com/company/emerald-ai-1)
    - **Live Demonstrations**: Completed five live demonstrations at commercial data centers across Arizona, Illinois, Virginia, Oregon, and London in collaboration with EPRI and NVIDIA. [emeraldai.co](https://www.emeraldai.co/blog/sharing-our-strategic-expansion-round-emerald-ai-raises-25-million-to-transform-ai-data-centers-into-flexible-power-grid-assets)
    - **Key Milestones**:
        - Published first peer-reviewed evidence of AI power flexibility in *Nature Energy*.
        - Demonstrated spatial flexibility by shifting inference workloads from Virginia to Chicago.
        - UK’s first live demonstration of grid-responsive AI infrastructure in London (reduced electricity demand by more than a third in under a minute).
        - Integration with NVIDIA DSX Flex to turn AI factories into power-flexible grid assets.
        - Collaboration with NVIDIA and major energy producers on a new class of flexible AI factories based on the NVIDIA Vera Rubin DSX reference design.
    - **Strategic Advisory Board**: Launched in March 2026, including seven Fortune 500 companies. [emeraldai.co](https://www.emeraldai.co/blog/sharing-our-strategic-expansion-round-emerald-ai-raises-25-million-to-transform-ai-data-centers-into-flexible-power-grid-assets)

## Competitive Advantages
- **First-Mover in a Critical Niche**: Positioned at the exact intersection of AI infrastructure and energy grid management, a growing bottleneck for AI growth.
- **Proven Technical Validation**: Has published peer-reviewed research in *Nature Energy* and completed five live demonstrations with major industry partners (NVIDIA, EPRI, Digital Realty).
- **Unmatched Ecosystem of Partners**: Backed by strategic investors across the entire value chain: AI (NVIDIA), energy (Siemens, National Grid, GE Vernova, Eaton), and finance (EIP, Lowercarbon Capital). This provides direct access to customers and deployment channels.
- **High-Caliber Team**: Founded by Dr. Varun Sivaram (former Fortune 500 C-suite energy executive, senior U.S. diplomat, Rhodes Scholar, physicist, author). Chief Scientist is Prof. Ayse Coskun (Director of Boston University’s Center for Information and Systems Engineering, pioneer in flexible AI and HPC). Head of Engineering is Shayan Sengupta (20 years of hyperscale cloud and AI leadership from Amazon and Intel). [emeraldai.co](https://www.emeraldai.co/)
- **Clear Value Proposition**: Solves a trillion-dollar problem: unlocking up to 100 GW of grid capacity for AI data centers without building new power plants, while strengthening grid reliability and protecting ratepayers.

## Strategic Focus
- **Commercial-Scale Deployment**: The primary focus for 2026 is moving from demonstrations to commercial-scale deployment. The company is targeting the world’s first power-flexible AI factory at commercial scale: the 96MW NVIDIA Aurora facility in Manassas, Virginia. [emeraldai.co](https://www.emeraldai.co/blog/sharing-our-strategic-expansion-round-emerald-ai-raises-25-million-to-transform-ai-data-centers-into-flexible-power-grid-assets)
- **Scaling the Platform**: Using the $25 million strategic expansion round to scale the Conductor platform globally.
- **Policy & Regulatory Engagement**: Actively working with regulators and policymakers to establish data centers as credible grid resources, as evidenced by their collaboration with the U.S. Department of Energy's Genesis Mission Consortium. [emeraldai.co](https://www.emeraldai.co/)
- **Expanding the Ecosystem**: Deepening partnerships with utilities, data center operators, and AI innovators to standardize power-flexible AI infrastructure.

## Why Work Here
- **Mission-Driven Impact**: The company is tackling one of the most critical infrastructure challenges of the AI era — the energy bottleneck. Employees work at the intersection of AI and climate/grid resilience.
- **High-Growth, Well-Funded Startup**: With $68 million raised in 16 months and a clear path to commercialization, the company is in a hyper-growth phase (61.1% quarterly job posting growth).
- **World-Class Team & Culture**: The company has assembled a team that "speaks every language fluently" — from hyperscale cloud architects and AI researchers to grid scientists and energy policy diplomats. [emeraldai.co](https://www.emeraldai.co/)
- **Active Hiring**: As of mid-2026, there are **29 active job postings** across engineering, product, policy, and business roles. [linkedin.com](https://www.linkedin.com/company/emerald-ai-1)
- **Global Presence**: Operates in 5 countries (U.S., Denmark, Canada, South Korea, Egypt), offering potential for international exposure. [linkedin.com](https://www.linkedin.com/company/emerald-ai-1)
- **Notable Perks/Environment**: The company is built by veterans from top-tier tech (Amazon, Intel, NVIDIA, AMD) and energy sectors, suggesting a high-performance, intellectually rigorous environment. The mission combines cutting-edge tech with real-world power systems.

## Sources
1. [emeraldai.co](https://www

_…truncated._

## Other roles at Emerald AI

- [Member of Technical Staff - Research](https://feeny.ai/job/member-of-technical-staff-research-emerald-ai-san-francisco-q9d7kgd8g3ks) — San Francisco, CA / San Jose, CA / Oakland, CA
- [Senior Product Manager, AI Cloud Services](https://feeny.ai/job/senior-product-manager-ai-cloud-services-emerald-ai-san-francisco-2xmmsc2zdg4h) — San Francisco, CA / San Jose, CA / Oakland, CA
- [Senior Product Manager, Compute Platform](https://feeny.ai/job/senior-product-manager-compute-platform-emerald-ai-san-francisco-z7ps98raf8c1) — San Francisco, CA / San Jose, CA / Oakland, CA
- [Legal Secretary](https://feeny.ai/job/legal-secretary-emerald-ai-washington-9r3795x9jahe) — Washington, DC
- [Member of Technical Staff - Grid Services](https://feeny.ai/job/member-of-technical-staff-grid-services-emerald-ai-san-francisco-e57mpmjv6mt4) — San Francisco, CA / San Jose, CA / Oakland, CA
- [Policy & Regulatory Affairs Manager](https://feeny.ai/job/policy-regulatory-affairs-manager-emerald-ai-washington-neempb36p285) — Washington, DC
- [Corporate Counsel](https://feeny.ai/job/corporate-counsel-emerald-ai-washington-d9zkg3qcd8vw) — Washington, DC
- [Member of Technical Staff- Datacenter/Power Systems](https://feeny.ai/job/member-of-technical-staff-datacenter-power-systems-emerald-ai-san-francisco-wy2r46sjkxck) — San Francisco, CA / San Jose, CA / Oakland, CA
- [Member of Technical Staff - Backend/Distributed Systems](https://feeny.ai/job/member-of-technical-staff-backend-distributed-systems-emerald-ai-san-francisco-4qzsmy0bjek1) — San Francisco, CA / San Jose, CA / Oakland, CA