Full-Stack Architect

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.

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.

• Backend Infrastructure & Service Logic: Extensive experience with Python-based frameworks (FastAPI/Flask) and Node.js environments to construct high-performance microservices and tune both relational and non-relational database models.
• Agentic AI Frameworks & Tooling: Demonstrated technical capability in engineering sophisticated AI agent workflows involving Model Context Protocols (MCPs), function calling, and complex patterns for tool interaction, supplemented by expertise in AI monitoring suites like LangSmith or Opik.
• High-Performance Data Syncing: Competency in managing intensive data mutations and fine-tuning server-state synchronization to ensure fluid React-based user interfaces without latency or freezing during real-time backend operations.
• Corporate Internal Tooling: Previous familiarity with Client’s development resources, internal data streams, and specific frontend libraries such as Fusion.js, BaseUI, and Styletron.
• Risk & Workflow Domain: Proficiency in developing automated monitoring platforms, compliance dashboards, or leveraging distributed task engines including Temporal, Cadence, or Celery.
• Rapid AI Iteration: Practical knowledge of utilizing accelerated prototyping environments like v0.dev or Lovable for the swift creation of internal applications., 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.

The Tech Stack Backend Core: Python (FastAPI, Flask), Node.js, Microservices, MCP (Model Context Protocol). Frontend Core: React, TypeScript, Fusion.js (Client’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.

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Compensation: The pay offered to a successful candidate will be determined by various factors, including education, work experience, location, job responsibilities, certifications, and more. Additionally, IntelliPro provides a comprehensive benefits package, all subject to eligibility.

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