Startup - Full Stack Engineer

Job Description

EQORE turns energy storage into a zero-effort financial asset with exceptional ROI, supporting businesses while improving grid resilience. As an early hire, you will design, implement, and operate the software, data, and field systems that power distributed energy storage deployments — from edge controllers to internal tools to customer-facing dashboards. In this high-impact role, you will own core operational software across the entire stack (embedded/edge control on Raspberry Pi, cloud services, and internal tools), stand up reliable tooling and processes that let EQORE deploy, monitor, and scale battery systems efficiently, and partner directly with founders to translate business needs into robust, data-driven systems. With active deployments in the field and a growing base of engaged customers, this is a chance to help scale an early-stage venture into a durable, high-growth enterprise. We’re looking for someone who thrives in ambiguity, loves shipping, and is motivated by the opportunity to build practical systems that support businesses while advancing sustainability. We’re located in Greentown Labs, the largest climate tech incubator and a lively center of industry-leading events and startup community — so you’ll be at the heart of sustainability and entrepreneurship in North America.

You will:

• Build, test, and maintain Python services on Raspberry Pi controllers for site-level dispatch, telemetry, and safety interlocks.
• Develop internal tools and dashboards (frontend/backend) for deployment workflows, monitoring, alerting, and reporting.
• Design data pipelines for ingesting, cleaning, and storing time-series signals from sites, ISOs, and market feeds.
• Implement observability (logging, metrics, tracing) and incident response runbooks to improve system reliability.
• Provide decision support through analyses and dashboards that guide market selection, site targeting, and product roadmap.
• Document systems, establish playbooks, and help build the foundation for a scalable operations engineering function.

Requirements

• Strong software engineering experience with Python in production environments.
• Experience building services or applications end to end (APIs, data models, testing, CI/CD).
• Comfort working close to hardware or edge computing (e.g., Raspberry Pi, Linux, device provisioning, networking).
• Proficiency with data engineering for time-series data and operational analytics.
• Practical approach to reliability: instrumentation, monitoring, and debugging distributed systems.
• Clear written and verbal communication; ability to create documentation and operational runbooks.
• Entrepreneurial mindset: bias to action, ability to wear multiple hats, and willingness to own problems end to end.

Further desirable qualifications include:

• Familiarity with optimization modeling (e.g., LP/MILP using Pyomo, OR-Tools, or similar) and translating models into services.
• Experience with energy systems, battery storage, building controls, or DER aggregation.
• Exposure to ISO/RTO programs, tariff structures, demand charges, or grid services markets.
• Frontend experience (React/TypeScript) for internal dashboards and operator tools.
• Cloud and DevOps skills (Docker, Kubernetes or containers on a lightweight stack, IaC, CI/CD, secret management).
• Edge fleet management experience (OTA updates, device security, remote diagnostics).
• Background in controls, forecasting, or reinforcement learning for operational decision-making.
• Prior work at an early-stage startup or in a rapidly scaling environment.