GenAI / Agentic Systems Dallas/Charlotte Only Local Inperson Interview

Charlotte, NC, US • Posted 1 day ago • Updated 20 hours ago
Contract Corp To Corp
Contract W2
Contract Independent
No Travel Required
Able to Sponsor
On-site
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • GenAI / Agentic

Summary

GenAI / Agentic Systems

Dallas/Charlotte Only Local Inperson Interview

Long Term

Contract

To strong GenAI experience including RAG, GraphRAG, Knowledge Graphs, Entity/Ontology Extraction and related architectures, we re specifically looking for candidates who also bring start-up experience. Hands-on exposure to fast-paced, early-stage environments

Deploying AI models into live production environments

Integrating models into real applications or systems

Supporting models post-deployment (monitoring, performance, scalability, etc.)

Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.

Develop autonomous AI agents using modern agentic frameworks.

Design and deploy RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or Google Cloud Platform).

Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources.

Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks to measure answer relevance, groundedness, and hallucination rates.

Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality.

Develop systems leveraging embeddings at scale, knowledge graphs, and ontology extraction.

Collaborate across engineering teams, mentor developers, and help drive innovation in GraphRAG and agentic AI architectures.

Degree in Computer Science, AI/ML, or related field.

5+ years of AI/ML-focused software engineering experience.

Production experience building LLM-based or agentic AI systems.

Strong expertise in Python and modern AI frameworks.

Experience with embeddings, knowledge graphs, ontology extraction, and advanced RAG/GraphRAG implementations.

Full-stack development experience (Python back end + modern front end).

Experience deploying AI workloads to AWS, Azure, or Google Cloud Platform.

Familiarity with LLMOps/MLOps tooling and model evaluation frameworks.

Strong problem-solving, communication, and collaboration skills.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91081414
  • Position Id: 8910966
  • Posted 1 day ago
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