FP Alpha builds an AI-powered financial planning tool for wealth advisors, with a tech stack anchored in Python data science (NumPy, Pandas, scikit-learn) paired with dual LLM integrations (OpenAI and Anthropic) via LangChain and LangGraph. Active modernization work—migrating Angular 14 to 20, refactoring legacy components, scaling backend services—combined with hiring velocity focused on engineering suggests the company is moving from initial product-market fit toward architectural stability and feature depth, while simultaneously investing in customer success operations.
FP Alpha is a fintech platform enabling financial advisors to generate comprehensive financial plans using AI and client data. Founded in 2018 and based in New York, the company operates at 11–50 employees with an engineering-forward structure: four of five open roles are engineering positions. The platform runs on Python-backed data science and LLM inference layers (OpenAI, Anthropic), with an Angular-based advisor interface and cloud infrastructure across AWS, GCP, and Azure. Current work centers on modernizing the frontend stack, scaling backend services, and building customer success tooling—all while managing churn and expanding revenue per customer.
Python (NumPy, Pandas, scikit-learn) for data science; OpenAI and Anthropic for LLMs; LangChain and LangGraph for orchestration; Flask and FastAPI for backend; Angular and TypeScript for frontend; AWS, GCP, Azure for cloud; MongoDB for data storage.
Platform modernization (Angular 14→20 migration, legacy refactoring), LLM-powered chatbot, document processing workflows, scalable backend services, and customer success infrastructure (tools, dashboards, playbooks).
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