About

CAREERS

Building Fundamental American Infrastructure Takes a Renaissance Workforce

Powertown is actively hiring mission-driven, ambitious individuals looking to make our country a stronger place from the bottom up.

Why Apply

Technical Team

Software Engineer, Powertown

$190,000–$200,000 base salary · Full-time · In person, Boston office

Role

Powertown is hiring a Software Engineer to maintain the main software portal for our company. This is the command center for a battery storage company: the place where projects, people, documents, decisions, and execution come together. We want someone who can build software that makes a serious team move faster.

What You'll Do

Turn messy real-world workflows into clean product surfaces.
- Build the screens people actually want to use.
- Design the hidden logic that makes the product feel simple.
- Create systems that make information easier to find, trust, and act on.
- Ship fast without creating chaos.
- Make the portal feel like Powertown's operating system.

Preferred Majors

Computer Science, Software Engineering, Computer Engineering, Electrical and Computer Engineering, or a similarly rigorous technical field.

Ideal Candidate

You are a product-minded builder with real engineering depth. You can sit with an ambiguous problem, reduce it to its core, and build the first version before most people finish debating the requirements. You have taste. You know when a workflow is clunky, when a data model will age badly, and when a product is almost useful but not quite there yet.

Preferred Qualifications

Evidence of exceptional building ability: shipped products, startup work, serious side projects, open-source contributions, research systems, internal tools, or technically ambitious independent work.
- Experience building products where workflow, permissions, data quality, and usability matter.

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Software Engineering Intern, SCADA

$60/hour · Internship · In person, Boston office

Role

Powertown is hiring a Software Engineering Intern to help maintain software for real-time visibility into battery assets. This role sits close to the physical world. The data represents real equipment, real power, real failures, and real decisions. We want an intern who is not afraid of systems that have consequences.

What You'll Do

Make live energy data understandable.
- Build interfaces for status, alarms, events, and telemetry.
- Hunt for edge cases in real-time behavior.
- Help turn raw signals into operational clarity.
- Test the weird cases: stale data, missing data, noisy data, delayed data.
- Learn how infrastructure software behaves when the physical world is involved.

Preferred Majors

Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Electrical and Computer Engineering, Energy Systems, Robotics, or a similarly technical field.

Ideal Candidate

You are a technical student who likes real systems more than toy apps. You are careful, curious, and hard to overwhelm. You like the idea that a bug might not just break a button, but misrepresent what is happening in a live asset. You want to learn fast and contribute quickly.

Preferred Qualifications

Evidence of initiative through projects, research, internships, competitions, open-source work, robotics, hardware/software projects, simulations, or self-directed technical building.
- Experience working with live data, sensors, energy systems, IoT, visualization, or operational software.

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AI Engineer, Prospecting

$190,000–$200,000 base salary · Full-time · In person, Boston office

Role

Powertown is hiring an AI Engineer to build map-based intelligence for battery storage development. This role is for someone who can find signals in messy infrastructure data and turn it into a product advantage. The goal is simple: help Powertown see better sites, faster.

What You'll Do

Turn scattered infrastructure data into a living map of opportunity.
- Build systems that rank, enrich, and explain prospects.
- Extract signal from land, grid, utility, market, and spatial data.
- Use AI to compress research loops that usually take days.
- Create workflows that help the team notice what others miss.
- Make maps feel intelligent, not decorative.

Preferred Majors

Computer Science, Data Science, Artificial Intelligence, Electrical Engineering, Energy Systems, Physics, GIS, or a similarly analytical field with strong technical ability.

Ideal Candidate

You are part engineer, part detective, part strategist. You enjoy messy data because you know that is where the advantage is. You can look at a map and ask better questions than "what layer should we add?" You are not building dashboards. You are building a machine for discovering opportunity.

Preferred Qualifications

Experience with geospatial systems, infrastructure datasets, utility data, energy markets, site selection, ranking systems, AI-assisted research, data extraction, or large messy public/commercial datasets.
- Evidence of unusual initiative through shipped projects, research, startup work, competitions, technical writing, or self-directed data products.

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Machine Learning Engineer, Grid Intelligence

$190,000–$200,000 base salary · Full-time · 2 openings · In person, Boston office

Role

Powertown is hiring Machine Learning Engineers to build intelligence systems for battery storage and the electric grid. This role is about grid infrastructure, peak shaving, utility data, storage economics, asset behavior, forecasting, optimization, and agentic workflows. We are not looking for someone who simply trains models. We are looking for people who can invent new ways for AI, data, and software to make Powertown better at finding, evaluating, and operating storage assets.

What You'll Do

Build intelligence around peak shaving, load behavior, utility signals, and storage opportunities.
- Create agents that research, extract, compare, reason, and propose next steps.
- Turn grid data into decision systems.
- Design experiments where the answer is not obvious.
- Find the hidden structure in messy energy datasets.
- Build models only when models are the right tool.
- Use AI aggressively, then audit it ruthlessly.
- Invent workflows the industry does not yet have.

Preferred Majors

Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Math, Statistics, Electrical Engineering, Energy Systems, Operations Research, Power Systems, Physics, or another rigorous quantitative field.

Ideal Candidate

You are a superstar technical thinker who uses ML as one of many tools. You have very high agency. You do not wait for a clean dataset, a polished problem statement, or a perfect roadmap. You form hypotheses, build instruments, test ideas, and keep moving. You are AI-first but not AI-reliant. You use agents, LLMs, automation, and modern tools to move faster, but your own judgment stays in charge. You are drawn to the grid because it is physical, messy, high-stakes, and full of hidden leverage.

Preferred Qualifications

Evidence of exceptional ability: original research, serious side projects, open-source work, startup building, competitions, technical writing, or shipped systems.
- Experience with energy storage, utility data, tariffs, load analysis, peak shaving, grid infrastructure, electricity markets, forecasting, optimization, anomaly detection, agentic workflows, or AI-assisted research systems.

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Machine Learning Intern, Grid Intelligence

$60/hour · Internship · In person, Boston office

Role

Powertown is hiring a Machine Learning Intern to work on AI and ML problems for battery storage, grid infrastructure, peak shaving, utility data, forecasting, and internal intelligence. This is not a toy internship. The problems will be ambiguous. The data will be imperfect. The work will matter.

What You'll Do

Search for signals in messy energy data.
- Build quick models, then try to break them.
- Use AI tools to move faster without turning your brain off.
- Prototype agents for research, extraction, comparison, and reasoning.
- Visualize what matters, not what is easy to plot.
- Write down assumptions before they become mistakes.
- Help create the first version of systems that may become core products.

Preferred Majors

Ideal Candidate

You are early-career but unusually strong. You like math, code, energy, and hard questions. You are curious enough to explore and disciplined enough to measure. You can use AI tools well, but you do not outsource your thinking to them. You should be the kind of intern who makes full-time people move faster.

Preferred Qualifications

Evidence of unusual initiative through projects, research, competitions, internships, open-source work, technical writing, or self-directed building.
- Experience with energy data, forecasting, optimization, agentic workflows, applied ML, power systems, geospatial data, or AI-assisted analysis.

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