Senior Full Stack Engineer

Pravāh • San Francisco, CA

2d • Onsite

About The Position

Pravāh is building foundational intelligence for the electric grid, so that utilities and energy companies can better predict supply, demand, grid volatility, and extreme weather. We’re looking for early team members to scale our platform globally. We’re negotiating multi-million dollar contracts with some of the largest utilities in the world, have raised $7.5M from three of Silicon Valley’s top VCs and are actively working on scaling our platform in three countries. But most importantly, we’re solving a problem with global impact - all while having fun working every single day. If you care about solving global problems, have high agency, and want to work with some of the most energetic and brilliant people in the world, join us :)

This role is extremely important for us, and we want to be honest with what type of people will succeed in this team. We took the time to write out a much more detailed note on our team here: https://pravah.notion.site/

Role Summary
As a Senior Full Stack Engineer, you will own the design, development, and scaling of 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 the world'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 — from the ground up.

This is an early engineering role. You'll have a direct impact on a platform that already serves utilities managing power for over 300 million customers across three countries. 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.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
• 5+ years of experience building and deploying production-grade full-stack web applications.
• Proficiency in TypeScript and at least one modern frontend framework (Angular strongly preferred; React also considered), with deep understanding of state management, reactive patterns, and asynchronous data flows.
• Strong backend development experience in Python, Java/Kotlin, or Go, with a solid grasp of foundational CS concepts for optimizing code performance and memory usage.
• Experience designing and building microservices architectures, including RESTful APIs, gRPC, event-driven design patterns, and message queues.
• Hands-on experience with Google Cloud Platform (preferred) or AWS/Azure, including managed databases, compute, storage, and networking.
• Working experience with Cloud SQL (PostgreSQL/MySQL) and familiarity with time-series data storage patterns.
• Experience with Docker, containerized deployments, and CI/CD pipeline design.
• Experience with automated testing — unit, integration, and end-to-end (Jest, Cypress, Playwright, or equivalent).
• Knowledge of logging and monitoring tools (Prometheus, Grafana, GCP Cloud Monitoring) for troubleshooting production systems.
• Ability to operate with high autonomy in ambiguous, fast-moving environments — you'll be making architectural decisions, not just executing tickets.

Nice To Haves

• Experience with D3.js, Mapbox, Deck.gl , or WebGL for rendering complex geospatial or time-series visualizations.
• Experience building data-intensive applications that process and visualize large-scale time-series datasets (millions of records, sub-minute resolution).
• Working knowledge or background in power systems, electric grid technologies, or energy markets.
• Experience with GIS data formats (shapefiles, GeoJSON, CIM models) and spatial analysis.
• Familiarity with ML model serving — deploying and monitoring inference pipelines in production, model versioning, or feature stores.
• Experience with enterprise security architectures, compliance standards, or building multi-tenant SaaS platforms for regulated industries.
• Track record in high-growth or "zero-to-one" environments where you've built core infrastructure from scratch.
• Experience designing reusable component libraries and managing complex frontend build pipelines (Webpack, Vite, or Nx).

Responsibilities

• Design and implement high-performance web applications using TypeScript and Angular (or 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, Deck.gl , or D3.js 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 (millions of data points across thousands of feeders) with smooth, responsive interactions.
• Create map-based views that allow utility engineers to drill from substation-level down 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 UX to translate Figma designs into delightful interfaces.
• Write comprehensive tests using frameworks like Jest to ensure reliability of mission-critical tools that utilities depend on for operational decisions.
• Design, build, and operate scalable microservices and REST APIs (with gRPC where performance-critical) 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 — including 5-minute interval weather forecasts from multiple providers (XWeather, OpenMeteo), AMI meter data, SCADA telemetry, and grid topology datasets — normalizing across inconsistent formats and time zones.
• Integrate backend services with ML inference pipelines — serving TiDE, transformer-based, and ensemble forecasting models that consume 1000+ 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 and audit logging appropriate for enterprise utility clients.
• Design backend systems using event-driven architecture patterns and message queues to handle asynchronous processing of large-scale batch forecasting jobs and automated reporting workflows.
• Work with Cloud SQL (PostgreSQL) for relational data and appropriate NoSQL stores for high-throughput time-series ingestion.
• Optimize query performance as data volume scales across utility clients.
• Build and evolve CI/CD pipelines on Google Cloud Platform to reliably deploy data-intensive services, ML-backed APIs, and frontend applications.
• Implement production observability using tools like Prometheus, Grafana, and GCP Cloud Monitoring — structured logging, metrics dashboards, and alerting to detect and debug issues across data pipelines and forecasting services.
• Own production deployments and incident response for backend systems that utilities rely on for operational planning.
• Ensure high availability and graceful degradation.
• Containerize services with Docker, manage orchestration, and design deployment patterns that support multi-tenant utility environments with client-specific configurations.
• Continuously improve system scalability and reliability as Pravāh scales from serving 5 utility clients to 50+, with data volumes growing by orders of magnitude.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior