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Neara is hiring a Customer Value Architect in New York City with remote options to serve utility customers. The role focuses on connecting a physics-based digital twin of the grid to real operations, building business cases, and proving value after deployment.
The ideal candidate blends technical fluency, consultative customer handling, and the ability to translate model outputs into decisions utilities care about, such as outage planning and risk reduction.
Customer & Solutions · New York City · Remote · FullTime
A Customer Value Architect in customer success typically works with utility customers to connect a technical product to their real operational goals, building business cases and proving value after deployment. A strong candidate brings a mix of technical fluency, consultative customer handling, and the ability to translate simulation outputs into decisions utilities care about, such as outage planning and risk. Comfort with energy network operations and with data heavy tools helps, since the product is a physics based digital twin of the grid.
AI speeds up scenario generation and analysis, so the role shifts toward framing the right questions and judging whether model outputs are credible for a utility. The human parts stay central: building trust with customers, understanding their constraints, and turning results into decisions people will act on. Value storytelling and change management become more important as the technical work gets faster.
This role builds AI experience by applying simulation and model outputs to real grid scenarios like storms and fires, and by learning how to validate and explain those results to non technical stakeholders. It also grows skill in pairing AI driven analysis with customer workflows, which is useful groundwork for more technical AI roles later.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
A physics-based 3D digital twin of the electricity network, so utilities can simulate a storm or a fire before it happens rather than inspect poles after.