Full-Time

Forward Deployed Engineer

Updated on 8/1/2026

Pravāh

Pravāh

11-50 employees

AI-driven grid intelligence for utilities

Compensation Overview

$20k - $30k/yr

India + 1 more

More locations: New Delhi, Delhi, India

Hybrid

Frequent travel across India to DISCOM sites is required.

Category
Software Engineering (1)
Required Skills
Scikit-learn
Python
PyTorch
Xgboost
SQL
Machine Learning
Data Engineering
AWS
Pandas
DevOps
Google Cloud Platform

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Requirements
  • A degree in engineering, computer science, or a quantitative discipline is required.
  • Strong programming fundamentals in Python are required, along with comfort with SQL, pandas, and at least one machine learning framework such as scikit-learn, XGBoost, or PyTorch.
  • Experience working with large, messy real-world datasets is required.
  • Comfort with cloud infrastructure such as GCP or AWS and modern data tooling is required.
  • Strong written and verbal communication is required.
  • Willingness to travel within India to DISCOM offices, often at short notice, is required.
  • The candidate must be able to lead and execute tasks with minimal hand-holding.
  • The candidate must have a strong problem-solving instinct, including the ability to use AI agents and modern tooling intelligently.
Responsibilities
  • Travel to DISCOM sites across India and embed with their engineering, planning, and operations teams to understand their data landscape and operational pain points.
  • Acquire, clean, and structure large-scale operational datasets, including SCADA streams, smart-meter telemetry, GIS networks, billing records, and weather feeds, often spanning multiple years and hundreds of millions of rows.
  • Partner with the machine learning and engineering teams to tune and deploy models for demand forecasting, renewable generation forecasting, network mapping, and load flow analysis, owning the data side and feeding the model side.
  • Architect and ship cloud-native data pipelines on GCP alongside the engineering team to productionize models for customers.
  • Work alongside utility leadership on procurement, compliance, and rollout from the initial pitch through live deployment.
  • Identify product gaps from field work and communicate them to the core engineering team.
Desired Qualifications
  • Prior exposure to the power, energy, or infrastructure sector.
  • Experience with geospatial data, including QGIS, GeoPandas, shapefiles, and GDB.
  • Experience deploying, managing, or building end-to-end software products at scale.

Pravāh builds AI-powered intelligence infrastructure for the electric grid. Its software analyzes grid data to help utilities plan, monitor, and operate more reliably and efficiently. The product combines data from different parts of the grid and uses machine learning to provide insights, forecasts, and optimization recommendations that utilities can act on. Pravāh distinguishes itself through real-world deployments with utilities serving tens of millions of customers across India, Germany, and the US, backed by notable venture investors. The goal is to help energy providers run smarter grids by turning data into actionable intelligence at scale.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

San Francisco, California

Founded

2025

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Simplify Jobs

Simplify's Take

What believers are saying

  • Pilots span India, Germany, Colombia, and the United States.
  • Utilities need outage reduction amid extreme weather and renewable variability.
  • Backers like Khosla Ventures, Pear VC, and Conviction increase buyer credibility.

What critics are saying

  • Utility procurement cycles delay pilots and slow revenue conversion.
  • Poor or delayed grid data breaks real-time forecasting and optimization.
  • A major forecast error can destroy trust and freeze deployments.

What makes Pravāh unique

  • Stanford-founded team builds AI-native grid intelligence for utilities.
  • Uses graph neural networks, transformers, reinforcement learning, and probabilistic forecasting.
  • Deploys real-time decision support across load, generation, and congestion.

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