About the role
About Roebling We're building Roebling , an AI-native capital projects platform aimed at enabling the rapid development of the industrial infrastructure required to power our future. Today, innovators face an outdated reality: getting to construction on projects big and small requires thousands of hours of repetitive, PDF- and spreadsheet-driven workflows with heavy QA/QC overhead. It's inefficient, slow, and largely unchanged for more than a century. Roebling is now reducing planning timelines by 10x to help companies bring new products to market faster. The technological foundation of Roebling's backend is a deterministic first-principles process model paired with major LLMs to deliver trusted output. Combined with a no-code project simulation engine that integrates aspects of chemical engineering, finance, and operations, our agentic environment informs and supports infrastructure investment decisions for industrial projects with 7-10 figure construction budgets. If you're motivated by using software and AI to unlock physical infrastructure, we'd love to chat!
The Role You'll be one of the next two or three engineers on
the team. You'll own large surfaces of the product (schemas, services, agent loops, UI) alongside the founders, our earliest customers, and a small senior team that ships major features to prod every week. Some weeks you'll be prototyping new workflows against live customer feedback; others you'll be designing core systems that have to stay correct, performant, and maintainable for years. You'll help set the bar for how engineering operates as we scale.
What you'll work on AI agents that explore a project's design space across thousands of simulation scenarios, evaluating tradeoffs across CAPEX, OPEX, throughput, and carbon intensity. Ingestion pipelines for public utility data, equipment specs, and financial datasets. Performance, stability work and numerical optimization in our simulation engine. The CI/CD, observability, and testing foundations a fast team needs to stay fast. What we're hiring for (in order) Engineering fundamentals. ~5-7 years shipping production software, with meaningful time at a startup that grew through a real scaling phase. You learned to engineer before LLM coding tools existed. You read code, debug live systems, and reason about performance, scalability, and maintainability without leaning on autocomplete. This is the bar. End-to-end product instinct. You can hold a Pydantic schema, a React component, and a customer's planning constraint in your head at the same time, and ship the right tradeoff between them. You write clearly enough that a teammate in a different timezone can pick up where you left off without a meeting. AI-native workflow. You use Claude Code, Cursor, or similar agentic tooling every day, not because we told you to, but because you've internalized that these tools are a force multiplier when paired with strong fundamentals (and a foot-gun without them). You know what to delegate, what to review carefully, and where the tools fall down. If you have (1) and (2) but are still ramping on (3), we'll teach you. The reverse isn't true. What this role is not If you want to manage a team rather than ship code, this isn't that. We're hiring builders. If you want to live in one part of the stack and let someone else worry about the rest, this isn't that. Every engineer here owns features end-to-end. Our stack Frontend: React, Next.js, Redux, TailwindCSS, Vercel Backend: FastAPI, PostgreSQL, Pydantic, Supabase Engine: Custom simulation engine with an internal solver layer LLM layer: Direct Anthropic and Google model APIs with our own orchestration; no LangChain/LangGraph dependency Dev workflow: Claude Code, Cursor