Fullstack Engineer - Cofounder
generalintelligencecompany · New York ·
- Work mode
- Onsite
- Category
- Fullstack
- Experience
- 4+ years
- Visa sponsorship
- No
- Company size
- 11-50
generalintelligencecompany · New York ·
natter · Remote - GMT */-3hrs
houseful · London, England, United Kingdom
Focal Systems · Poland, Remote
Photon · United States
Builds and maintains the full-stack autonomous agent platform for Cofounder, a product that helps entrepreneurs coordinate AI agents to run companies, using React/Next.js, Python FastAPI, and Postgres.
At General Intelligence, we’re building highly-capable autonomous agents for startups. Our goal is to enable the one-person, one-billion-dollar company.
Our product, Cofounder, enables entrepreneurs to start and run companies. Using it should feel more like a company-building game where users coordinate agents, unlock roadmap nodes, run missions, build artifacts, grow departments, and make revenue go up.
End-to-end product work across the agent experience: flows, integrations, and UI/UX
Flows: creation, editing, run criteria, execution reliability, and observability
Integrations: add new integrations and deepen existing ones
UI/UX: work on novel, interesting ways of building human<>agent interactions
Product sense for complex UX: making powerful systems feel simple and reliable
Ship features across the stack with a tight feedback loop from real users (frontend + backend)
Improve performance, reliability, and cost across agent runs and flow execution
Build instrumentation, analytics, and developer tooling to speed up iteration
Maintain a high bar for code quality, tests, observability, and documentation
4+ years building and shipping user-facing products end to end
Frontend: React/Next.js (or equivalent), TypeScript; component-driven development, performance profiling, accessibility, data fetching/state, optimistic UI and cache invalidation
Backend: Python FastAPI, background workers/queues, webhooks, Postgres (or similar) schema design, transactions, migrations
Solid testing and observability habits (unit/integration tests, metrics, traces, structured logs)
Bias to ship: scope thin slices, deliver quickly, instrument, iterate
Event-driven architectures, WebSockets/real-time UIs
LLM/agent experience: tool-use patterns, prompt hygiene, guardrails, evaluation
Infra familiarity (Vercel/AWS/Modal/Supabase/Redis Cloud or equivalent), CI/CD, feature flags
Ship directly to engaged users; your work is visible and high-impact
Build the core of an autonomous agent platform with real integrations and real workloads
Small, elite team; high ownership; fast decisions; zero bureaucracy
Bristlecone Companies · United States