AI Engineer – Agentic AI | LLM | LangGraph | LangChainLocation: Dallas, TX (Hybrid)Duration: 12+ MonthsInterview Process: Technical Screening + Final In-Person Interview (Mandatory)Compensation : Depends on Experience, Skills.We are seeking an experienced AI Engineer with strong expertise in Agentic AI, Large Language Models (LLMs), and AI orchestration frameworks to design and develop enterprise-grade AI applications. The ideal candidate will have hands-on experience building multi-agent systems, conversational AI solutions, and production-ready LLM applications using modern AI frameworks and cloud technologies.This role requires a strong software engineering background with practical experience in AI orchestration, machine learning integration, prompt engineering, and LLMOps.Responsibilities* Design, develop, and deploy agent-based AI applications using LangGraph, LangChain, and similar orchestration frameworks.* Build scalable multi-agent workflows with intelligent task planning, execution, and state management.* Develop reusable tools, workflows, and orchestration components for enterprise AI applications.* Design and integrate Model Context Protocol (MCP) clients and tool ecosystems.* Build conversational AI applications with contextual memory, reasoning, and dynamic tool invocation.* Develop and integrate REST APIs and external enterprise systems into AI workflows.* Integrate machine learning models using TensorFlow, PyTorch, or Scikit-learn for inference, prediction, and feedback loops.* Implement Retrieval-Augmented Generation (RAG), vector search, and knowledge retrieval solutions where applicable.* Apply LLMOps best practices including prompt engineering, prompt versioning, evaluation, monitoring, logging, observability, and performance optimization.* Define and execute testing strategies for AI applications, including unit testing, workflow validation, scenario simulation, regression testing, and agent behavior evaluation.* Optimize AI systems for scalability, reliability, security, and cost efficiency.* Collaborate with engineering, product, and business teams to deliver enterprise AI solutions.* Stay current with emerging technologies, frameworks, and best practices in Agentic AI and Generative AI.Required Qualifications* Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.* 5+ years of software engineering experience.* 2+ years of hands-on experience developing Generative AI or LLM-based applications.* Strong experience with LangGraph, LangChain, or similar AI orchestration frameworks.* Experience designing and implementing multi-agent AI systems.* Experience with Model Context Protocol (MCP) or similar tool integration architectures.* Strong understanding of LLM architecture, prompt engineering, function calling, tool usage, memory management, and agent orchestration.* Hands-on experience with Python.* Experience with TensorFlow, PyTorch, or Scikit-learn.* Experience building REST APIs and microservices.* Experience working with cloud platforms such as AWS, Azure, or GCP.* Experience deploying AI applications into production environments.* Strong problem-solving and communication skills.Preferred Qualifications* Experience with CrewAI, AutoGen, Semantic Kernel, or similar frameworks.* Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.* Experience implementing RAG architectures.* Familiarity with LangSmith, Weights & Biases, Arize AI, or other LLM observability platforms.* Experience with Docker, Kubernetes, CI/CD, and cloud-native deployments.* Knowledge of distributed systems and scalable AI architecture.