Senior Full-Stack Engineer (Backend-Focused) | FRM CT

Job Description

Job Description

Role: Senior Full-Stack Engineer (Backend-Focused) | FRM CT
Location: SFO, CA
The Mission
The Financial Risk Management (FRM) team ensures the integrity of our platform through real-time
monitoring, complex data visualization, and AI-driven automation. We are looking for a Senior
Full-Stack Engineer (Backend-Focused) to architect the core data systems and service layers that
power our platform, while seamlessly tying them into high-velocity user interfaces. You will build
highly scalable infrastructure, orchestrate complex APIs, integrate GenAI capabilities into our
backend workflows, and deliver polished frontend experiences.

The Role: Architecting Intelligent, End-to-End Infrastructure
You will own the system architecture for our FRM compliance and automation tools. This means
moving fluidly across the entire stack-designing databases, building robust microservices,
integrating Model Context Protocols (MCPs) for AI agents, and hardening interactive dashboards to
handle live risk-data updates with ultra-low latency. You are a high-velocity engineer who embraces
the future of software development, treating data, APIs, and interfaces as a single cohesive product.

Key Responsibilities
System Architecture & Database Design: Architect scalable, low-latency backend
systems capable of handling massive datasets and live risk-data updates. Design highly
optimized database schemas (SQL/NoSQL) and data orchestration pipelines tailored for
FRM automation.
API & Service Orchestration: Develop and manage RESTful APIs, GraphQL, and
high-performance real-time communication layers (WebSockets/gRPC-web). Implement
microservices architecture and Model Context Protocols (MCPs) to securely connect AI
agents with internal enterprise data.
Advanced AI & LLM Integration: Design, integrate, and deploy production-ready LLM
systems using providers like OpenAI and Anthropic. Build sophisticated backend workflows
using AI agent frameworks (LangGraph, CrewAI), function calling, and complex tool-use
patterns to automate business logic.
Full-Stack Execution & Frontend Delivery: Translate high-fidelity Figma designs or rapid
prototypes into pixel-perfect, scalable, and secure React layouts. Manage complex
asynchronous workflows using Redux Sagas or Zustand, while implementing TanStack
Query for modern server-state synchronization.
Performance & AI Observability: Build resilient AI systems by implementing AI
Observability (e.g., LangSmith, Opik), hallucination detection, and retry logic. Optimize
end-to-end performance to ensure frequent real-time updates do not trigger unnecessary UI
re-renders, maintaining a fluid user experience even under high data loads.
AI-Driven Development: Lead by example in using AI-augmented coding workflows,
leveraging tools like Cursor, Codex, and GitHub Copilot to accelerate cross-stack feature
delivery, refactor legacy logic, and eliminate boilerplate.

Required Qualifications
7 Years of Engineering Experience: A deep background in system design, database
architecture, and scaling enterprise-grade backend services, with a recent pivot toward
full-stack delivery and AI-augmented workflows.
Core Stack Mastery: Deep proficiency in Python (Flask/FastAPI) and Node.js to develop
performant service layers, combined with a strong command of React and TypeScript to
build production-grade interfaces.
Real-Time & Protocol Expertise: Expert-level knowledge of RESTful APIs, service
orchestration, WebSockets, and gRPC-web to ensure data streams perfectly sync between
backend nodes and client apps.
State & Data Lifecycle Strategy: Expert implementation of high-throughput databases,
caching layers (e.g., Redis), and modern state management strategies (TanStack Query,
Zustand, or Redux) to handle heavy data mutations seamlessly.
AI Tooling & LLM Orchestration: Hands-on experience with LLM orchestration frameworks
(LangChain, LlamaIndex, Smolagents, DSPy) as well as advanced prompt engineering.
Mastery of the Cursor code editor (indexing, composer, and chat features) to maintain elite
velocity.

Nice to Have
Uber Ecosystem: Prior experience at Uber or deep familiarity with our internal developer
ecosystem, internal data pipelines, and platform services.
Workflow Domain: Background in building systems for anomaly detection dashboards,
compliance tools, or complex workflow-driven automation platforms (e.g., Celery, Cadence,
Temporal).
Rapid Prototyping Fluency: Familiarity with design-to-code or AI prototyping sandboxes
(like Lovable or v0.dev) to quickly map out internal tools before building them into permanent
architecture.
Product Mindset: Proven focus on delivering measurable user value, using stakeholder
feedback for iterative improvement, and treating technical components as a product to
ensure usability, quality, and adoption.

The Tech Stack
Backend Core: Python (FastAPI, Flask), Node.js, Microservices, MCP (Model Context
Protocol).
Frontend Core: React, TypeScript, Fusion.js (Uber's Framework).
AI & LLM Tools: Cursor, GitHub Copilot, LangGraph, CrewAI, LangSmith/Opik, Lovable,
v0.dev.
State & Data: Redux Sagas, TanStack Query, Zustand, Context API, WebSockets,
gRPC-web, GraphQL, Redis, SQL/NoSQL.
Design & UI: BaseUI design system, Styletron (CSS-in-JS), Figma, Tailwind CSS.