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# AI Engineer (Application Design & Rapid Deployment)

- **Company:** Internet Brands, Inc.
- **Location:** Newark, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, AI Evaluation, Artificial Intelligence, Automation of Tests, Relational Databases, Programming Tools, Human-Computer Interaction, Python (Programming Language), Node.Js, Rapid Prototyping Process, Next.js, Software Engineering, Unstructured Data, Web Application Frameworks, Data Logging, Pinecone, Qdrant, ReactJS, Large Language Models, Claude Code, Multi-Agent Systems, Prompt Engineering, Backend, Agentic-AI, Data Layers, LangSmith, Kubernetes, Low Latency, RAGAS (Retrieval Augmented Generation Assessment), Milvus, Machine Learning Operations, Evaluation of Large Language Models
- **Published:** October 30, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-engineer-application-design-rapid-deployment-newark-nj--5ebb2ec8-a9b0-4b95-ab95-37f5d046e0c8

## About the Role

Artificial Intelligence (AI), Software Design, Programming Tools, Artificial Intelligence (AI), Software Design, Performance Modeling, Use Cases, Rapid Prototyping, Quality Assurance, Test Harness, * Industry Tenure: 5+ years of professional full-stack software development experience.

 * AI Engineering Specialization: Proven track record of designing and deploying production-grade LLM applications, with a heavy emphasis on multi-agent architectures.
 * The "Tiger Team" Mindset: Experience thriving in fast-paced, high-agility environments where requirements evolve rapidly and execution speed is critical.

Technical Skills

 * Orchestration Mastery: Deep, production-level expertise with LangGraph for building stateful, multi-agent workflows, alongside standard libraries.
 * AI Tooling & Full-Stack Stack: Hands-on mastery of Claude Code for accelerated development, combined with robust backend skills (Python, Node.js) and modern frontend frameworks (React/Next.js).
 * AI Evaluation & MLOps: Strong understanding of LLM evaluation methodologies, dataset curation for testing, and semantic logging/tracing tools (e.g., LangSmith).
 * Data Layer: Proficient with vector databases (e.g., Pinecone, Qdrant, Milvus), relational databases, and integrating unstructured data pipelines.
 * Prompt Engineering: Excellent at prompt engineering best practices and with good linguistic intuition for LLM best performance.

Soft Skills & Leadership

 * Excellent communication and collaboration skills.
 * Self-driven and eager to mentor and share knowledge.
 * strong product sense; the ability to balance complex AI logic with intuitive user experiences and immediate business value.
 * A self-starter who can own an application from a blank text document to a live production URL with minimal supervision.

## Description

As an AI Engineer, you will serve as one of our "Tiger Team" engineers: a highly versatile, full-stack application specialist who designs, builds, and deploys high-impact AI applications from end to end. You excel at taking a vague business problem and turning it into a production-ready AI solution in record time. Leveraging expertise in advanced orchestration frameworks like LangGraph and cutting-edge developer tools like Claude Code, you will act as the primary designer of our user-facing AI applications.

Beyond execution, you will play a vital role as an organizational enabler. You will build the evaluation systems necessary to guarantee model performance, integrate AI capabilities into workflows safely and effectively., AI Application Design & Rapid Execution

 * End-to-End Application Design: Serve as designer and builder for new AI applications, mapping out how the user interface, backend logic, and AI agents interact.
 * Advanced Agentic Workflows: Build complex, stateful, multi-agent systems and cyclic workflows using LangGraph inside and out to handle sophisticated enterprise use cases.
 * Rapid Prototyping: Utilize full-stack capabilities and AI-assisted development tools (e.g., Claude Code) to build high-fidelity minimum viable products (MVPs) at an accelerated pace.

Evaluation & Quality Assurance

 * LLM Evaluation Tools: Design, build, and maintain automated testing and evaluation frameworks (e.g., Ragas, TruLens, or custom LLM-as-a-judge pipelines) to measure accuracy, latency, hallucinations, and regression across applications.
 * Framework Stress-Testing: Act as power-user of our internal AI Development Framework, enabling its capabilities in real-world scenarios and providing direct feedback to the core architecture team.