S
Agentic AI Engineer
Select Minds LLC
3 hours ago
Full-time
On-site
Dallas, Texas, United States
Job Description Job Description Benefits:
ONSITE
Competitive salary
Opportunity for advancement
AI Engineer – Agentic AI | LLM | LangGraph | LangChain Location: Dallas, TX (Hybrid) Duration: 12+ Months Interview 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.
AI Engineer – Agentic AI | LLM | LangGraph | LangChain Location: Dallas, TX (Hybrid) Duration: 12+ Months Interview 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.