Job DescriptionPLEASE NOTE:- This is a 100% onsite position inDallas, TX or Charlotte, NC.
- Candidates located in either of these locations will be considered.
KEY REQUIRED SKILLS:- AI/ML, LLM-based or agentic AI systems, Python and modern AI frameworks
JOB DESCRIPTION:We are seeking an experienced AI Engineer to design, build, and deploy production-grade GenAI solutions. This role focuses on developing agentic AI systems, GraphRAG applications, and enterprise LLM services that solve real business problems. The ideal candidate has hands-on experience taking GenAI applications from proof of concept into production, enjoys working with modern agent development frameworks, and stays current with the rapidly evolving GenAI ecosystem.
KEY RESPONSIBILITES:- Design, build, and deploy production-grade GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.
- Develop autonomous AI agents using modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
- Take AI solutions from prototype through production deployment, ensuring scalability, reliability, observability, and maintainability.
- Design and implement advanced RAG and GraphRAG pipelines that integrate enterprise knowledge sources using embeddings and knowledge graphs.
- Build scalable REST APIs using Python (FastAPI) that power LLM-driven enterprise applications.
- Containerize and deploy AI services using Docker and cloud platforms including AWS, Azure, or GCP.
- Implement LLM evaluation frameworks using LangSmith, Ragas, DeepEval, or custom evaluation pipelines to measure answer quality, groundedness, latency, and hallucination rates.
- Apply LLMOps best practices including CI/CD, prompt/version management, automated testing, monitoring, and production observability.
- Collaborate with engineering teams to integrate AI capabilities into enterprise platforms.
- Mentor engineers and contribute to technical best practices for GenAI application development.
- Stay current with emerging GenAI technologies, agent frameworks, and industry best practices, evaluating new tools and approaches as the ecosystem evolves.
RequirementsREQUIRED 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 building GenAI or LLM-powered applications.
- Demonstrated experience taking GenAI applications from proof of concept into production.
- Hands-on experience with one or more modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
- Strong Python development skills, including FastAPI and REST API design.
- Experience implementing RAG or GraphRAG solutions using embeddings, vector databases, knowledge graphs, and enterprise data sources.
- Experience deploying AI workloads using Docker and AWS, Azure, or GCP.
- Strong communication, collaboration, and problem-solving skills.
PREFERRED QUALIFICATIONS:- Familiarity with LLMOps practices including CI/CD, prompt management, model/version governance, monitoring, and evaluation.
- Experience with LLM evaluation tools such as LangSmith, Ragas, DeepEval, or equivalent frameworks.
- Demonstrated curiosity and commitment to staying current with the rapidly evolving GenAI and agentic AI landscape.
