Job Description
Job Description : As an experienced Full-Stack AI Engineer, you will design, build, and deploy end-to-end, AI-native applications. You will own the entire feature lifecycle-from designing intuitive frontend user interfaces that handle streaming AI data, to building robust backend architectures, orchestrating complex LLM or agentic workflows, and managing vector databases and cloud infrastructure. You are a generalist with architectural breadth and deep specialization in applying AI to practical software challenges. Make an Impact by: Applied AI & Intelligent Orchestration Orchestration & Workflow Design: Build complex multi-agent frameworks, task routing systems, and Human-in-the-Loop (HITL) workflows using orchestration engines like LangChain or LangGraph. RAG & Vector Management: Architect high-performance Retrieval-Augmented Generation (RAG) pipelines. Design indexing strategies, chunking mechanisms, and hybrid search (semantic + keyword) utilizing vector databases. Model Integration & Optimization: Integrate state-of-the-art LLMs and foundational models via commercial APIs or self-hosted inference setups. Implement strategies to manage model latency, token constraints, context windows, and fallback mechanisms. Evaluation & Guardrails: Establish AI evaluation frameworks to test for hallucinations, drift, and accuracy. Implement prompt safety, structural validation, and robust guardrails to handle non-deterministic outputs safely. Full-Stack Application Architecture Backend & API Engineering: Design high-concurrency, asynchronous backend services using Python (FastAPI) or Node.js/TypeScript. Develop robust RESTful APIs and optimize interactions using Model Context Protocol (MCP) systems where applicable. AI-Native Frontend Experiences: Build responsive, stateful UIs using React or Next.js. Implement streaming response interfaces (HTTP Stream), chat architectures, agentic UI interaction models, and intuitive data visualizations for complex model outputs. Data Manag
