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About the Role
Your initial focus will be Ask The Grid, our live product for exploring the power grid, its markets, and its assets. You will take technical ownership of the application and make 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, and AI-assisted product experiences. Your scope includes the public product, enterprise-facing capabilities, and the application work needed for customer deployments. You will work directly with users and customers to understand their workflows, partnering with the founders, applied-AI engineer, and data engineer on technical scoping and delivery. Your primary ownership is the shared product and the application layer of customer deployments. You will collaborate with, rather than replace, the engineers and researchers responsible for the underlying data and models.
Responsibilities
- Own the public product: maps, radar, assets, network views, and how they work together as one dependable application.
- Own the path from visitor to operator: accounts and organizations, saving and claiming assets, portfolios, private-data connections, permissions, alerts, and reports.
- Own product architecture, APIs, performance, observability, reliability, accessibility, and the systems that keep the application dependable.
- Own the agent's interaction quality: how context is selected, how sources are shown, and how the product handles uncertainty, unsupported requests, and unreliable answers.
- Own customer-facing workflows and application-level integrations, working with the engineers who own the underlying data and model systems.
- Own direct user feedback and production debugging, turning repeated friction into clearer workflows and better software.
- Own decisions, with the founders and technical team, about what becomes reusable product, what remains customer-specific, and what should not be built.
- Ship to production, understand the product architecture, and identify where real user sessions encounter friction or stall within the first 30 days.
- Ship an end-to-end improvement that measurably improves exploration, account creation, or completion of an operator workflow within the first 60 days.
- Own the product application and deliver a practical technical plan for the next reusable capability, informed by product usage and customer needs within the first 90 days.
Requirements
- Experience owning complex, data-rich applications from an ambiguous user need through implementation, deployment, and production operation.
- Strong React and TypeScript skills, together with the backend and API experience needed to own an end-to-end product outcome.
- Product judgment: the ability to translate complex user needs into understandable interfaces and dependable workflows.
- Experience with production debugging, performance, reliability, accounts, and permissions.
- The ability to work directly with customers, ask precise questions, and separate the underlying need from a requested implementation.
- Clear collaboration across product, data, model, and agent boundaries without treating those boundaries as someone else's problem.
Skills
- React
- TypeScript
- Backend experience
- API experience
- Production debugging
- Performance optimization
- Reliability engineering
- Account management
- Permissions management
- Maps
- Time-series interfaces
Location
- New York City
- Boston/Cambridge
Work Type
- Hybrid
Salary/Compensations
- $180,000–$260,000 USD
Benefits
- Meaningful early-company equity
About the Company
- Parisi Labs is building foundational world models for physical industry, developing models that learn how complex physical systems behave and reuse that understanding across forecasts, scenarios, and operational decisions.
- Energy is our first proving ground. We combine historical and live data with operational context, bringing together machine learning research, data infrastructure, and software engineering to turn advances in modeling into useful technology for energy operators.
- We are a small technical team working directly with the founders on our core models, systems, and products.