Full Stack Engineer Hybrid (Cambridge, MA)

S27a; Boston (MA); On-site; USD 120,000 - 160,000; Full time

Job summary

S27a in Boston is seeking an early technical hire to design and build customer-facing interfaces, data pipelines, APIs, and energy simulation workflows. You will join a founding team and ship features across the stack.

You will own end-to-end work from API design to frontend deployment, working with Python, FastAPI, PostgreSQL, and AWS to normalize diverse data sources and deliver value to customers.

Qualifications

• Built and deployed web applications using Python and a modern JS framework (Svelte, React, Vue, or similar).
• Designed REST APIs and worked with relational databases (PostgreSQL or equivalent).
• Wrangled imperfect data—cleaning, transforming, or integrating datasets from multiple sources.

Responsibilities

• Design and build a customer-facing interface for exploring building data, energy simulations, and upgrade recommendations.
• Extend and maintain data pipelines and integrations from diverse sources.
• Develop and evolve the FastAPI backend to support new data products and frontend features.
• Contribute to asynchronous job systems that run energy simulations at scale across thousands of buildings.
• Own features end-to-end from API design through frontend deployment.

Skills

Problem solving

Team collaboration

Ownership

Frontend collaboration

Education

CS degree or equivalent experience

Tools

Python

FastAPI

PostgreSQL

AWS

REST APIs

React/Svelte/Vue

Job description

Location: Boston

Type: Full-time, early technical hire

What you’ll help build

• Customer-Facing Interface: Help design and build the interface where customers explore building data, view energy simulations, and act on upgrade recommendations.

• Data Pipelines & Integrations: Connect and normalize data from diverse sources (satellite imagery, utility records, building permits, economic data) into a unified format our models can use.

• API Development: Extend our FastAPI backend to serve new data products and support frontend features.

• Simulation Workflow: Contribute to the asynchronous job systems that run energy simulations at scale across thousands of buildings.

Day-to-day (Your First 90 Days)

Month 1: Orientation & UI

• Get up to speed on the core stack (Python, FastAPI, PostgreSQL, AWS).

• Take ownership of your first front-end components and ship a customer facing feature to production.

Month 2: Start getting into the backend and data pipelines

• Extend the API to support new data visualizations and customer workflows based on customer feedback and input.

• Wrangle messy datasets: cleaning, formatting, and integrating sources that may require custom web scrapes, pdf parsing, etc. across different location granularities (e.g., county, state, federal).

Month 3: E2E ownerships

• Own a feature from API design through frontend deployment.

• Contribute to the feedback loop: how we ingest customer input and use it to improve outputs.

In 6 months, success looks like

• You have a deep understanding of our full analytics platform and can navigate the codebase with confidence.

• You are shipping high-quality code across the entire stack, from frontend components to backend logic and AI integrations.

• Engineering velocity is high because you are a proactive problem solver who can unblock yourself and others.

The kind of problems you’ll enjoy

• Data normalization: Buildings don't come with clean datasets. You'll figure out how to reconcile mismatched addresses, incomplete utility records, and inconsistent permit data into something usable.

• Making dense outputs legible: Energy simulations produce a lot of numbers. You'll build interfaces that help non-technical users understand what matters and what to do next.

• Fast iteration with real customers: We work directly with our users to improve our products, and want to ensure we are always developing new features that align with their vision.

You might have done some of this

• Built and deployed web applications using Python and a modern JS framework (Svelte, React, Vue, or similar).

• Designed REST APIs and worked with relational databases (PostgreSQL or equivalent).

• Wrangled imperfect data—cleaning, transforming, or integrating datasets from multiple sources.

• Shipped something end-to-end, whether through internships, personal projects, or open-source work.

• CS degree or equivalent experience (new grads welcome!).

What makes this role special

• Early team ownership: You’ll join an experienced founding team—a former McKinsey partner, a technical founder with deep energy expertise, and an experienced operator.

• Greenfield + real traction: We’ve proven the MVP and have paying customers—now we’re scaling to thousands of buildings.

• Surface area that matters: Every feature you build directly contributes to bending the curve down on global emissions.

What we value

• Intellectual Curiosity: A desire to learn the "why" behind building energy systems and AI models.

• Pragmatic rigor: Measure, ship, iterate.

• Low-ego collaboration: Teach, learn, and write things down.

Compensation

Competitive salary + potential for equity (early-engineer level).