Lead Full Stack Engineer (all genders)

Job description

About GeneralMind GeneralMind builds AI Systems of Action for complex enterprise workflows. We deploy AI employees that automate messy operational handovers across supply chains - processing orders, validating invoices, coordinating suppliers, and handling exceptions directly on top of enterprise systems like SAP, Oracle, JDE, and Dynamics. Our platform combines AI agents, operational context graphs, and real transaction data to achieve Autopilot-grade automation in real operational environments. We work closely with leading global companies across manufacturing, retail, and logistics to deploy AI into mission-critical workflows. About the role We are looking for a Lead Full Stack Engineer to own and evolve the core architecture of the company across both the frontend and backend, and to set the technical bar for how the rest of the engineering team builds full-stack features. You will work directly with the founders on systems that orchestrate real operational workflows across emails, documents, humans, databases, and ERP systems. A crucial part of this role is bridging our AI infrastructure with user experience - you will build the next-generation interfaces where human operators collaborate with our Systems of Action, and make the architectural calls that other engineers will build on top of. The work sits at the intersection of full-stack engineering, workflow orchestration, UI/UX architecture, and AI infrastructure. This is not a feature-factory role. We want someone who can hold large parts of the system in their head, make strong architectural decisions across the stack, and raise the quality bar for the team. What You'll Do Design, build, and evolve production-grade full-stack applications using Python (FastAPI) and React (Next.js). Architect and develop next-generation interfaces for our Systems of Action, enabling seamless human-in-the-loop interactions and complex data visualization. Build durable backend workflow systems using tools like Temporal to support asynchronous AI agent execution. Improve reliability, observability, and operational tooling across both client and server applications. Integrate with enterprise systems such as ERP platforms (SAP, Dynamics, etc.) and external APIs, surfacing that data intuitively on the frontend. Scale multi-tenant systems, database architectures (PostgreSQL), and platform abstractions. Work closely with pr…