# Senior Full-Stack Product Engineer **Company:** [Parisi Labs](null/companies/o1TEgMywySM7fktrXb3rQE.md) **Location:** New York, United States **Workplace:** hybrid **Employment type:** Full-time [Apply for this job](null/view/2ff3da7a-49eb-4d18-b53d-82c5be214843) ## Description About Parisi Labs Parisi Labs is an AI research and product company building systems that understand how the physical world changes over time. We combine live data, forecasting, and interactive software so people can see what is happening, reason about what comes next, and make better decisions. Energy is our first proving ground. Ask The Grid is our live product for exploring the power system across markets, generation, demand, weather, and outages. It gives us a real environment in which to test models, ship useful tools, and learn from real users. We are a small team working across research, data, and product engineering. Everyone is expected to move from an ambiguous problem to a working system and to care whether the result is useful, reliable, and faithful to the underlying world. About the role Ask The Grid is already a substantial live product. We are looking for a senior product engineer to take technical ownership of it and keep making it faster, clearer, more reliable, and more useful. You will work across React and TypeScript, maps and time-series interfaces, APIs, accounts, data-intensive workflows, reliability, and AI-assisted product experiences. This is a product engineering role for someone who likes owning the whole outcome, not an ML research role. What you will own \- The public surfaces: maps, radar, assets, network views, and how they work together as one dependable product. \- The path from visitor to operator: accounts and organizations, saving and claiming assets, portfolios, private-data connection, permissions, alerts, and reports. \- Product architecture, APIs, performance, observability, reliability, accessibility, and the ordinary systems that make ambitious software dependable. \- The interaction quality of the agent inside the product: how context is selected, how sources are shown, and what happens when the system should refuse. \- The judgment call about what becomes reusable software, what remains an operator-specific workflow, and what should not be built. You will work across product, data, model, agent, and decision-system boundaries without replacing the engineers and researchers who own those systems. Your job is to make their capabilities cohere as software a user can understand and trust. First 90 days In your first month, you will ship to production and map the product architecture and the places real sessions stall. By day 60, you will ship one end-to-end improvement that measurably improves exploration, account creation, or operator workflow completion. By day 90, you will own the product surface and deliver a practical technical plan for the next reusable product capability.About Parisi Labs Parisi Labs is an AI company building learning systems for complex physical environments. We combine historical and live data with real operational context to help people understand the present, evaluate possible futures, and make better decisions. Energy is our first proving ground. Ask The Grid (https://askthegrid.com) is our public product for exploring the systems, markets, and assets that make up the power grid. We are a small technical team working across machine learning, data infrastructure, software, and real-world operations. About The Role We are hiring a senior full-stack product engineer to take substantial ownership of Ask The Grid and help us build the product experiences that follow from it. You will work across frontend, backend, data-backed workflows, and AI-assisted product features. The product is already live, so this is not a greenfield mockup role: you will learn from real usage, improve what exists, and ship durable software that makes a complex system understandable and useful. This role owns the user-facing product experience. It does not own the core machine-learning research agenda or the shared data platform. What You Will Own \- Ship end-to-end product improvements across the application, from interface through backend behavior and release. \- Make complex, changing data legible through clear interactions, visualizations, and workflows. \- Improve the ways people explore, save, organize, and act on the information that matters to them. \- Build AI-assisted features that are useful, trustworthy, and clear about their limits. \- Use product evidence to find friction, set priorities with the founders, and measure whether a change worked. \- Raise the bar for performance, reliability, accessibility, and maintainability across the product. \- Help decide which repeated needs should become reusable product capabilities. First 90 Days \- 30 days: Learn the product and user journey, ship an early improvement, and identify the highest-leverage sources of friction. \- 60 days: Own and deliver an end-to-end product improvement with a clear measure of success. \- 90 days: Establish durable ownership of the product surface and a written view of the next highest-value improvements ## Requirements You may be a fit if \- You write production-quality software and have strong product taste. \- You can inherit a large existing application, understand it quickly, and improve it without reaching for a rewrite. \- You care about architecture, tests, observability, performance, accessibility, and the small interaction details users feel. \- You use AI tools aggressively without giving up correctness or clarity. \- You can sit with a battery operator or grid planner and come back with working software, not only a specification. \- You are comfortable saying no to work that will not generalize. Helpful background \- Senior product engineering, full-stack engineering, or founder-close software work on a substantial live application. \- TypeScript and React in production; strong API and database judgment; comfort in Python where the data lives. \- Maps, charts, time-series visualization, or interfaces over large live datasets. \- Authentication, organizations, permissions, billing, reliability, and production operations. \- Experience integrating LLMs or agents is useful but not required. \- Startup or high-ownership experience is strongly preferred. Energy experience is welcome and not required. ## Benefits Location and working style New York City, in person by default. Boston/Cambridge can work for an exceptional candidate who maintains a regular in-person cadence with the founders in New York. Compensation The base salary range is $180,000-$260,000 per year, plus meaningful early equity. Final compensation depends on experience, location, seniority, and role scope. Interview process The process is a founder screen with the CTO and CEO, a working session on a real Ask The Grid surface, technical calibration with the CTO, an in-person final, and offer review with all founders. Why join now You will take ownership of a live product with real data and real users, while helping define how an early AI research and product company turns ambitious technical work into dependable software.