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Full Stack Lead (Angular)
Location: Dallas, TX (Onsite)
Hiring Type: Full Time
Description:
We are seeking a Full stack Lead with a mastery of Angular and backend orchestration to spearhead the development of our Agentic AI platform. You will lead a team of engineers to build the interface and the "nervous system" that connects users to autonomous AI agents.
The ideal candidate understands that an Agentic AI UI is fundamentally different from a CRUD application it requires handling real-time streaming, complex state management for multi-agent workflows, and highly interactive "canvas-style" workspaces.
Key Responsibilities :
Lead Architect for AI UX: Architect and build a high-performance Angular frontend capable of handling real-time Server-Sent Events (SSE) and WebSockets for streaming AI "thoughts" and actions.
System Orchestration: Design the backend-to-frontend bridge that allows users to monitor, pause, and steer autonomous agents in real-time.
Advanced State Management: Implement robust state management (using Signals or NgRx) to handle the non-linear states of AI agents (e.g., Planning, Searching, Tool-calling, Error-recovery).
Scalable API Design: Lead the development of robust APIs (Python/FastAPI or Node.js) that act as the orchestrator between the Angular UI and the Agentic framework (LangGraph, AutoGen, etc.).
Fullstack Observability: Build tools for "Agent Observability," allowing users to debug agent decisions, view execution logs, and trace data lineage within the UI.
Team Leadership: Mentor a cross-functional team, conduct code reviews, and establish best practices for "AI-First" software engineering, focusing on low latency and high reliability.
Technical Requirements:
Frontend Mastery: 7+ years of experience in web development, with 4+ years specializing in Angular (v16+ preferred). Deep knowledge of Signals, RxJS, and performance optimization.
Backend Proficiency: Strong experience in Python (FastAPI/Flask) or Node.js, specifically in building asynchronous services that interface with LLMs.
AI Integration: Hands-on experience with OpenAI/Anthropic APIs and a conceptual understanding of how Agentic frameworks (like LangChain or LangGraph) function.
Real-time Communication: Expertise in streaming technologies (SSE, WebSockets) to provide a "live" feel as the agent works.
Cloud & DevOps: Experience with Docker, Kubernetes, and cloud providers (AWS/Azure/Google Cloud Platform) to deploy and scale AI-heavy workloads.
Database Knowledge: Proficiency with both relational (PostgreSQL) and Vector Databases (Pinecone, Milvus) for RAG-based applications.
Preferred Qualifications:
Experience building Canvas-based or Node-based UIs (e.g., using specialized libraries for drag-and-drop agent workflows).
Prior experience in a lead role within a startup or a rapid-growth AI lab.
Familiarity with Python-based AI libraries to better collaborate with AI Engineers.
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