Senior Software Engineer - Fullstack

Role Overview

What You Will Do

• Build and own features across Next.js, Node.js or Express, and Python or FastAPI service layers.
• Implement real-time data flows with WebSockets, Socket.IO, Kafka consumers, and Server-Sent Events.
• Develop interactive charts, grids, dashboards, widget layouts, and a conversational AI assistant panel.
• Maintain shared packages within the Turborepo monorepo.
• Integrate capital markets data infrastructure including KDB+/Q, time-series pipelines, and enterprise messaging.
• Build and optimize the authenticated backend-for-frontend proxy layer.
• Implement Redis and RTK Query caching, invalidation, optimistic updates, and rate limiting.
• Build AI and LLM features including RAG context orchestration and streamed responses.
• Maintain production reliability through Kubernetes, Helm, routing, autoscaling, and observability.
• Translate trading desk workflows into platform features with quants, traders, and product teams.

Must-Have Qualifications

• 5+ years of professional software engineering experience with significant full-stack development experience.
• Expert TypeScript proficiency in large, strictly typed codebases.
• Deep React and Next.js experience, including App Router, Server Components, middleware, API routes, and SSR or ISR.
• Strong Node.js and Express experience with REST APIs, middleware, and asynchronous data pipelines.
• Experience with Redux Toolkit and RTK Query for state management at scale.
• Experience designing real-time systems with WebSockets, Socket.IO, Server-Sent Events, or similar technologies.
• Proficiency with MongoDB, Mongoose, Redis, caching patterns, and pub/sub.
• Experience with monorepo tools such as Turborepo, Nx, or Lerna.
• Experience implementing authentication and authorization with OAuth2/OIDC, JWT, LDAP/AD, or NextAuth.js.
• Experience with Docker and Kubernetes deployments using Helm.
• Strong communication skills for explaining technical trade-offs to non-technical stakeholders.

Nice-to-Have Qualifications

• Capital markets or financial services experience with knowledge of equities trading workflows and desk structures.
• Python or FastAPI experience for AI or machine learning service layers.
• KDB+/Q or time-series database experience with real-time and historical market data.
• AI or LLM integration experience, including RAG, prompt engineering, and streaming inference.
• Charting and visualization experience with Highcharts, D3, or similar libraries.
• Observability experience with ELK, Prometheus, or Grafana.
• Knowledge of Kafka, Solace, or similar event-driven messaging systems.