Full-Time
Member of Technical Staff
Datacenter/Power Systems
Updated on 9/4/2026
Emerald AI
11-50 employees
AI-powered demand flexibility for data centers
No salary listed
Boston, MA, USA + 2 more
More locations: Washington, DC, USA | Oakland, CA, USA
Hybrid
One work-from-home day per week is available.
 Software Engineering (1) |
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- At least 7 years of software engineering experience with strong proficiency in Python, Rust, Go, or C/C++.
- Hands-on experience building telemetry ingestion pipelines or distributed systems that handle high-volume time-series data.
- Familiarity with at least one asynchronous messaging system, such as Kafka or RabbitMQ.
- Exposure to information technology or operational technology systems, including SCADA, EMS, BMS, or DCIM, and an understanding of how data flows between them.
- Build software modules that interact with datacenters, on-site industrial power systems, and the electrical grid.
- Architect and implement data ingestion pipelines that collect, normalize, and persist high-frequency telemetry from power meters, PDUs, UPS systems, cooling infrastructure, and compute hardware.
- Design fault-tolerant integration layers between IT systems, including cloud APIs, databases, and orchestration platforms, and OT systems, including protocol translation and data model definition and mapping.
- Ensure safety, reliability, and correctness when interacting with real-world energy assets and critical facilities, including behavior in degraded, disconnected, or split-brain network states.
- Collaborate across teams to deliver end-to-end solutions from edge devices to the control plane.
- Direct experience with industrial telemetry protocols such as Modbus TCP/RTU, DNP3, OPC-UA, BACnet, or SNMP.
- Familiarity with time-series databases such as InfluxDB, TimescaleDB, or Prometheus, or industrial historian platforms such as AVEVA PI/OSIsoft or Ignition.
- Experience with Kubernetes, containerized deployments, or HPC job scheduling in datacenter environments.
- Background in power systems, energy markets, microgrids, or datacenter infrastructure, including power distribution, cooling, UPS, or PDUs.
- Understanding of control-system design patterns such as PID loops, state machines, setpoint control, or demand-response logic.
- Experience with edge-compute runtimes or constrained environments requiring low-latency, reliable local execution independent of cloud connectivity.
- Familiarity with optimization algorithms or energy-management strategies such as load shifting, peak shaving, or curtailment.
Emerald AI uses AI-powered demand flexibility to help AI data centers reduce or shift power usage during peak grid times, easing stress on the electric grid. It analyzes real-time energy demand and grid signals to defer non-essential workloads or throttle usage, smoothing demand without building new infrastructure. What sets Emerald AI apart is its goal to unlock up to 100 GW of grid capacity through demand response, enabling data-center growth without costly capital investments in new grid assets. The company's objective is to stabilize the grid and lower power costs while supporting ongoing data-center expansion for the technology sector.
Company Size
11-50
Company Stage
Series A
Total Funding
$217.5M
Headquarters
Washington DC, District of Columbia
Founded
2025
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Simplify's Take
What believers are saying
- Emerald AI raised $150 million on August 25, 2026, at a $1.05 billion valuation.
- Five demonstrations across Arizona, Illinois, Virginia, Oregon, and London validated commercial deployments.
- NVIDIA, Oracle, Dominion, and PJM partnerships shorten sales cycles and utility adoption paths.
What critics are saying
- The model depends on utilities trusting telemetry, dispatch, and verification during peak-grid emergencies.
- Emerald AI still lacks disclosed revenue, pricing, contracted megawatts, and customer retention data.
- Hyperscalers can copy flexibility software or demand direct utility deals, squeezing Emerald's margins.
What makes Emerald AI unique
- Emerald Conductor proved 25% load cuts in Phoenix on 256 GPUs in May 2025.
- Emerald AI signed Silicon Valley Power's first Flexible Load Interconnection Program in August 2026.
- Digital Realty and NVIDIA are building the 100MW Vera Rubin AI Research Factory in Manassas.
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6 month growth
↑ 31%1 year growth
↑ 31%2 year growth
↑ 58%Emerald AI raises $150M for flexible AI data centers. Inside an AI data center, a fine-tuning run and a live inference request can draw power from the same bus without carrying the same promise to the customer. Emerald AI is building software that identifies when that difference can become usable flexibility for the electric grid without turning customer service into collateral damage. The Washington, D.C. company announced a $150M oversubscribed Series A on August 25, 2026, at a company-stated $1.05B valuation. Energize Capital and DCVC co-led the round, which brings together financial investors and strategic backers across chips, energy, industrial equipment, utilities, and data-center infrastructure. The financing is a wager that power access can become partly a software and operating-contract problem while new generation and transmission are still being built. Emerald AI has shown that selected AI workloads can reduce or shift electricity demand. The next job is making that response measurable, repeatable, and dependable enough for utilities and data-center operators to plan around it. What happened. Dr. Varun Sivaram founded Emerald AI in 2024 and serves as CEO. The company says the Series A will support worldwide commercial deployments, expansion across engineering, research, and commercial teams, utility programs, and standards for verified flexible load. Energize Capital Managing Partner John Tough is joining Emerald AI's board. The verified leadership team also includes Prof. Ayse Coskun, Chief Scientist; Shayan Sengupta, Head of Engineering; Aroon Vijaykar, Chief Commercial Officer; and Mansi Shah, Head of Product. Energize Capital says Emerald AI has grown to more than 35 employees across the United States, while the company lists Washington, D.C., Boston, and San Francisco locations. The investor roster includes NVIDIA, Samsung Ventures, Siemens, Aramco Ventures, Salesforce Ventures, GE Vernova, RWE, JERA Ventures, ADVentures, Sabanci Climate Ventures, In-Q-Tel, Radical Ventures, Energy Impact Partners, Lowercarbon Capital, Marunouchi Innovation Partners, Emerson Collective, The Olayan Group, the Temerty Group, John Doerr, Tom Steyer, Earthshot Ventures, Collective Global, and General Catalyst's scout fund. Emerald AI says 12 Fortune Global 500 companies now hold investments in the business. A Form D filed with the SEC on August 3 disclosed a $150M equity offering and provides regulatory corroboration for the round's size. The company says total funding now exceeds $220M, although its public round history and independent reports do not reconcile to one exact cumulative number. That makes the total a company-reported figure rather than an independently reconstructed sum. How Emerald Conductor makes compute flexible. Emerald Conductor coordinates eligible AI workloads and onsite energy resources against grid conditions. A customer-defined fine-tuning job may be able to slow during a constrained period, while a latency-sensitive inference service may need to keep running. The platform can also shift suitable workloads between locations and coordinate batteries or other onsite resources when the operating plan permits. The important product is not a generic instruction to use less electricity. Utilities need telemetry, defined ramp behavior, service limits, and measurement showing that a promised response arrived. Data-center operators need to know which workloads remain protected, how customer obligations survive the event, and what economic value faster or larger power access creates. That places Emerald AI between systems with different failure conditions. A grid operator worries about reliability across a region. A data-center operator worries about uptime, hardware utilization, and customer contracts. Software may decide which job can move, but commercial adoption depends on an agreement that both sides trust when the grid is under its greatest strain. What Emerald AI has proven. The strongest public technical evidence comes from a peer-reviewed Nature Energy paper. In a Phoenix field test, Emerald AI's software reduced power consumption by 25% for three hours on a 256-GPU cluster while maintaining defined quality-of-service requirements. The result showed that workload orchestration could deliver a measurable response on real AI infrastructure without requiring new generation or a dedicated energy-storage system for that test. Emerald AI says it has since completed five demonstrations in Arizona, Illinois, Virginia, Oregon, and London. The company also says it has entered commercial deployment at multi-megawatt, full-data-center scale and names public collaborators including NVIDIA, EPRI, Oracle, Nebius, National Grid, Digital Realty, Silicon Valley Power, Dominion, PJM Interconnection, and Portland General Electric. The evidence still has boundaries. A 256-GPU cluster does not represent every production workload, while most commercial customers, revenue, pricing, contracted megawatts, and unit economics remain undisclosed. The five demonstrations and broader commercial scale are company-reported except where a partner or peer-reviewed source provides separate corroboration. Why investors are funding grid flexibility. The International Energy Agency expects data centers to account for nearly half of U.S. electricity-demand growth through 2030. Data centers can be planned and built faster than generation, transmission, substations, and interconnection processes can expand. That timing mismatch is turning electricity access into a constraint on AI deployment and a competitive issue for operators. Emerald AI says flexible computing could unlock more than 100GW of capacity on the existing U.S. grid. That number describes a modeled system opportunity, not Emerald AI's contracted capacity or customer demand. The distinction matters because the investment case depends on converting a large theoretical resource into specific utility programs, operating agreements, and paid deployments. The strategic cap table gives Emerald AI access to many of the institutions that must make the model work. Chipmakers understand workload behavior, utilities understand system needs, equipment companies understand physical limits, and data-center operators understand service obligations. Their presence does not guarantee commercial adoption, but it puts the negotiation inside the ownership structure rather than leaving Emerald AI to introduce each party from opposite sides of a conference table. The commercial test starts with the contract. Emerald AI and its partners are working toward a nearly 100MW power-flexible AI factory in Manassas, Virginia, planned for later in 2026. A project at that scale can test whether workload flexibility changes interconnection economics and daily operations, not merely whether software can execute a controlled response during a demonstration. The hard questions are contractual. Someone must define who can call a flexibility event, which workloads may move, how much notice is required, how the response is verified, and who carries the cost when actual performance misses the plan. Those terms determine whether grid flexibility becomes a bankable infrastructure service or remains an impressive technical feature. The $150M gives Emerald AI capital to standardize those answers across markets, customers, and utility programs. Software can move the work, but the company's lasting product will be the trust that allows a utility, an operator, and an AI customer to rely on the same decision when each one prices failure differently.
Emerald AI has raised $150 million in a funding round led by DCVC and Energize Capital, reaching a $1.05 billion valuation. Nvidia, Samsung Ventures, GE Vernova, and Salesforce Ventures also participated. The startup's proprietary software helps data centres adjust power consumption based on grid demand, reducing load during peak times and utilising excess capacity during low periods. This addresses pressure on power supply from surging AI computing needs. Emerald AI has secured contracts in California and Virginia and is testing with Nvidia and Oracle. Founder Sivalram aims to transform data centres from grid burdens into flexible resources, addressing regional backlash against data centre construction.
Emerald AI, now valued at $1.05 billion, uses software to keep power demand at the computing facilities from getting out of control.
Emerald AI raises $150 million Series A at $1.05 billion valuation to scale power-flexible AI data centers. * Emerald AI is tackling AI's power crunch by transforming AI data centers into flexible grid assets that dynamically adjust power consumption in response to power grid conditions, an approach that can unlock more than 100 gigawatts of capacity on the existing U.S. grid for AI while protecting grid reliability and energy affordability for communities. * The oversubscribed round was co-led by Energize Capital and DCVC, including participation from leading global financial and strategic investors, and brings Emerald AI's total funding raised to more than $220 million. * Having completed five commercial demonstrations around the world, Emerald AI has entered commercial scaling: its software is now deployed commercially at multi-megawatt, full data center scale, and the company serves customers spanning leading AI firms, data center operators, and electric power utilities. * As Emerald AI convenes the AI and energy ecosystem to advance power-flexible AI data centers, 12 Fortune Global 500 companies now hold investments in Emerald AI. WASHINGTON-(BUSINESS WIRE)-Emerald AI, the company transforming data centers into flexible assets for the power grid, today announced it has raised $150 million in an oversubscribed Series A financing at a valuation of $1.05 billion. The round was co-led by Energize Capital and DCVC, joined by a global group of leading financial and strategic investors-the company now counts 12 Fortune Global 500 companies as investors. With five global demonstrations complete, Emerald AI's technology is now deployed commercially, dynamically flexing power consumption at multi-megawatt, full data center scale. The company will use the new capital to scale commercial deployments worldwide with its customers, which include leading AI firms, data center operators, and electric power utilities. "We founded Emerald AI on the conviction that the intelligence driving the AI revolution could solve its own greatest bottleneck: power," said Emerald AI Founder and CEO Dr. Varun Sivaram. Share Rather than treating data centers as inflexible consumers of electricity, Emerald AI transforms them into intelligent, responsive assets that are good grid citizens and protect energy affordability and reliability for local communities. The Emerald Conductor software platform dynamically orchestrates AI computational workloads and onsite energy resources to control a facility's power draw when the grid is stressed while protecting the performance of critical AI workloads. The result is AI infrastructure that strengthens the electric grid rather than straining it. The financing arrives at an inflection point for American energy. Building new grid infrastructure can take a decade or more, while data centers are projected to account for nearly half of the growth in U.S. electricity demand through 2030, according to the International Energy Agency. Data centers running Emerald AI's software can connect to the grid faster and at larger scale, support grid reliability during periods of stress, and help hold down energy costs for the communities around them. Applied across the AI build-out, this approach can unlock more than 100 gigawatts of untapped capacity in the U.S. alone on the existing United States power grid, power available years before new infrastructure can be built. "We founded Emerald AI on the conviction that the intelligence driving the AI revolution could solve its own greatest bottleneck: power," said Emerald AI Founder and CEO Dr. Varun Sivaram. "Our demonstrations around the world proved that data centers can adjust their power use precisely when the grid needs relief, without compromising critical computing workloads. Today that technology runs commercially at full data center scale, and this financing lets us take it everywhere AI is built, so the AI era can accelerate while the grid becomes more reliable and more affordable for the communities it serves." The round drew together the companies building the AI era and the companies powering it. Energize Capital, a leading multi-strategy investment firm focused on digital solutions for the energy transition, co-led the financing alongside DCVC, one of the world's foremost deep tech venture firms, known for backing companies that turn frontier science and engineering into industrial-scale businesses. The round also convened leading financial and strategic investors across North America, Europe, and Asia. Twelve Fortune Global 500 companies are now investors in Emerald AI and sit on the company's Strategic Advisory Board, working directly with the company on product integration and commercial deployment across the AI and energy ecosystem. "The binding constraint on AI is no longer chips or capital; it is power, and software is the fastest way through it. Emerald AI has converted world-class research into commercial deployments faster than any company we have seen in this category, and we are proud to co-lead this round as the team defines how AI infrastructure and the grid grow together," said John Tough, Managing Partner at Energize Capital. "Emerald AI's compute workload orchestration platform makes flexibility a permanent feature of how data centers are powered. This turns data centers into grid-responsive assets instead of energy-hogging liabilities - increasing America's strength in AI, decreasing rises in electrical bills for communities, and protecting the environment. This is deep tech at its best," said Zachary Bogue, Co-Founder and Managing Partner, DCVC. Over the past year, Emerald AI has completed five successful demonstrations at commercial data centers in Arizona, Illinois, Virginia, Oregon, and London, working alongside partners including NVIDIA, EPRI, Oracle, Nebius, and National Grid as well as regional utilities and grid operators, proving at live commercial sites that AI data centers can flex their power use on the grid's schedule. With its demonstration phase complete, the company has entered commercial scaling, deploying at an entire data center in California that proved grid-responsive power flexibility during peak grid strain. Emerald AI now serves customers across the AI power value chain, from electric power utilities to leading AI companies to global data center operators, with additional large-scale deployments planned for later this year. Emerald AI partnered with Silicon Valley Power to launch its first-in-the-nation Flexible Load Interconnection Program, which grants data centers expanded grid access in exchange for verified, dispatchable flexibility. And in Manassas, Virginia, Emerald AI is working with Digital Realty and NVIDIA to bring online the world's first power-flexible AI factory, the nearly 100-megawatt Vera Rubin AI Research Factory, tested in collaboration with EPRI, Dominion, and the PJM Interconnection and slated to come online later this year. The company was also recently named one of the 2026 TIME 100 Most Influential Companies as well as a 2026 Technology Pioneer by the World Economic Forum. The Series A round was co-led by Energize Capital and DCVC. Several of the world's largest companies and leading financial investors participated, including NVIDIA, Samsung Ventures, Siemens, Aramco Ventures, Salesforce Ventures, GE Vernova, RWE, JERA Ventures, ADVentures (ADI's corporate venture capital fund), Sabanci Climate Ventures, In-Q-Tel (IQT), Radical Ventures, Energy Impact Partners, Lowercarbon Capital, Marunouchi Innovation Partners, Emerson Collective, The Olayan Group, the Temerty Group, John Doerr, Tom Steyer, Earthshot Ventures, Collective Global, and General Catalyst's scout fund. About Emerald AI Emerald AI transforms AI data centers into flexible assets for the power grid, securing larger and faster power connections for AI infrastructure, protecting electricity grid reliability, and advancing energy affordability for communities. The Emerald Conductor software platform is the intelligent interface between the world's two most valuable networks, power grids and AI infrastructure, unlocking critical power capacity for the AI era. For more information, visit www.emeraldai.co. Emerald AI. Release Summary Release Versions
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