AI Engineer – GenAI / Agentic Systems

AI Engineer – GenAI / Agentic Systems

Duration: 6–18 Months

Job Summary

STAFFXPERT LLC is seeking an AI Engineer – GenAI / Agentic Systems on behalf of our client in Charlotte, NC or Dallas, TX. The ideal candidate will have hands-on experience designing, developing, and deploying production-grade Generative AI solutions, with strong expertise in agentic AI, GraphRAG, LLM applications, and modern AI engineering practices.

Key Responsibilities

• Design, build, and deploy production-grade GenAI applications using foundation models and advanced architectures such as GraphRAG.

• Develop autonomous AI agents using frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.

• Take GenAI solutions from proof of concept through production while ensuring scalability, reliability, observability, and maintainability.

• Design and implement RAG and GraphRAG pipelines using embeddings, vector databases, knowledge graphs, and enterprise data sources.

• Develop scalable REST APIs using Python and FastAPI.

• Containerize and deploy AI services using Docker and cloud platforms such as AWS, Azure, or Google Cloud Platform.

• Implement LLM evaluation frameworks to measure response quality, groundedness, latency, and hallucination rates.

• Apply LLMOps practices including CI/CD, prompt and model version management, automated testing, monitoring, and observability.

• Collaborate with engineering teams to integrate AI capabilities into enterprise platforms.

• Mentor engineers and contribute to GenAI development standards and best practices.

• Evaluate emerging GenAI technologies, agent frameworks, and industry trends.

Required Qualifications

• Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience.

• 5+ years of software engineering experience, including recent experience developing GenAI or LLM-powered applications.

• Proven experience taking GenAI applications from proof of concept to production.

• Hands-on experience with modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.

• Strong Python development skills, including FastAPI and REST API development.

• Experience implementing RAG or GraphRAG solutions.

• Experience with embeddings, vector databases, knowledge graphs, and enterprise data integration.

• Experience deploying AI workloads using Docker and AWS, Azure, or Google Cloud Platform.

• Familiarity with LLMOps practices, including CI/CD, prompt management, model governance, monitoring, and evaluation.

• Experience with LLM evaluation tools such as LangSmith, Ragas, DeepEval, or equivalent.

• Strong communication, collaboration, analytical, and problem-solving skills.

Preferred Qualifications

• Experience building enterprise-scale AI platforms and applications.

• Experience with production observability and AI application monitoring.

• Strong understanding of emerging agentic AI architectures and multi-agent systems.

• Demonstrated ability to evaluate and adopt emerging GenAI technologies.