Location: Bengaluru (primary). Other location: New Delhi.

About Pravah

Pravah is building the world's first foundation model of the electric grid. The world's most important physical industry is under unprecedented stress. We are using ML to build the 22nd-century grid. We are backed by Khosla Ventures, Pear VC, and Conviction.

We work directly with state-owned distribution and transmission electricity utilities to transform their decades of fragmented operational data into deployable, decision-grade intelligence. Our customers include some of the largest DISCOMs in the country, and our work spans demand forecasting (including renewable generation forecasting), weather forecasting, network mapping, and load flow analysis.

The role

As a Senior Full Stack Engineer, you will play a central role in designing, developing, and scaling Pravāh's AI-driven grid intelligence platform end-to-end, from interactive frontends that make complex energy data actionable, to backend services that power real-time forecasting and grid analytics for some of India's largest utilities.

You'll work across the entire stack: building high-performance web applications that visualize time-series and geospatial data, designing scalable APIs and data pipelines that integrate weather, demand, and grid topology datasets, and productionizing machine learning models in collaboration with our power systems and ML teams. You'll also shape our core infrastructure: CI/CD, observability, and deployment patterns.

This is an early engineering role. You'll have a direct impact on a platform relied on by utilities worldwide. If you want to build critical infrastructure at the intersection of AI and energy, with real contracts, real data, and real-world consequences, this is the role.

Key Responsibilities

Frontend Development

Design and implement high-performance web applications using TypeScript and React that visualize time-series demand forecasts, weather ensemble data, and grid analytics for utility operators.

Build interactive geospatial visualization layers using libraries like Mapbox to render distribution network topology, feeder-level load profiles, and spatial weather overlays on utility grid maps.

Develop real-time, dynamic dashboards for day-ahead and intraday energy demand forecasting, rendering large time-series datasets (billions of data points across thousands of feeders) with smooth, responsive interactions.

Create map-based views that allow utility engineers to drill down from substation-level to individual distribution transformers, supporting bottleneck identification, fault isolation, and capacity planning.

Implement reusable component libraries to ensure UI consistency across multiple utility-facing products. Collaborate closely with the Product team to translate Figma designs into powerful interfaces.

Write comprehensive tests using frameworks like Jest to ensure reliability of mission-critical tools that utilities depend on for operational decisions.

Backend Development

Design, build, and operate scalable microservices and REST APIs that power weather-driven electricity demand forecasting, grid simulation, and load-flow analytics.

Build and maintain data ingestion pipelines that process high-frequency time-series data at scale, normalizing across inconsistent formats and time zones.

Integrate backend services with ML inference pipelines, serving TiDE, transformer-based, and ensemble forecasting models that consume a rich set of feature covariates including weather, calendar effects, and grid state variables. Support model versioning, A/B testing, and automated retraining workflows.

Build services that manage network metadata and grid topology, ingesting GIS shapefiles, CIM models, and utility asset registers to support load-flow simulations and network loss calculations at distribution scale.

Develop and enforce secure, compliant data access frameworks for sensitive utility data, including role-based access controls (RBAC) and audit logging appropriate for enterprise utility clients.