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OpenFX is building infrastructure to move money as freely as data across borders, unrestricted by time zones or legacy systems. The company powers next-generation cross-border payment systems for institutions and is backed by top-tier investors including Accel, Lightspeed, and NFX.
You will join the Trading team as a Senior Full Stack Engineer, owning the client-facing surface of the institutional trade experience. This role is frontend-heavy but genuinely full-stack. You'll architect critical client trade flows including quote generation, pricing surfaces, trade initiation, and settlement tracking across GUI, API, and conversational AI interfaces.
Key responsibilities include: designing and owning frontend architecture for high-volume trading surfaces (state management, data fetching, error handling, performance); building and extending backend APIs and data models to support these surfaces; shipping features end-to-end rather than stopping at team boundaries; instrumenting the client experience to surface problems before clients report them; partnering with Design and Product to shape flows; acting as a product engineer who understands business impact and makes prioritization calls; mentoring junior engineers; managing tech debt; and participating in on-call incident response.
You must have 5–7 years building production web applications with majority depth on frontend, plus a critical requirement: hands-on trading background from a crypto exchange, brokerage, or trading platform (CoinDCX, Groww, CoinSwitch Kuber, or similar). Deep expertise required in TypeScript, React, and Redux or equivalent state management. You need strong grasp of server-side rendering, code splitting, frontend architecture, and building reliable UIs on asynchronous systems with partial failures. Backend proficiency is essential: CRUD/REST APIs, PostgreSQL schema design, and comfort in Next.js or Hono runtimes. You should be able to own the backend of your own feature. Track record on frontend performance diagnosis and fixing slow production surfaces is required. You're comfortable with abstract, ambiguous problems, high-agency, hands-on, and a heavy AI tool user.
