Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
Yesterday
DockerFastAPIAWSAzureGenerative AIGoogle CloudLLMPythonREST
Job Description
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
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.
- 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.
- 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.
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