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# AI Systems & Infrastructure Engineer

- **Company:** VC5 Consulting
- **Location:** Houston, TX, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Extract Transform Load (ETL), Machine Learning, Large Language Models, Multi-Agent Systems, Prompt Engineering, Non-relational Database, Data Management
- **Published:** July 31, 2026
- **Apply:** https://www.dice.com/job-detail/14ec85c4-6d94-4110-8039-8527b01a55e2

## About the Role

* Demonstrable skill and execution in AI/LLM infrastructure, with a strong understanding of deployment and scaling challenges.
 * Proficiency in working with both relational and non-relational databases, with practical experience in data management.
 * Experience with data isolation and ETL processes specifically tailored for machine learning and large language models.
 * Familiarity with LLM architectures and frameworks, including prompt engineering and agentic frameworks (e.g., LangChain, AutoGen, LlamaIndex).
 * Strong communication skills with the ability to present complex technical concepts to non-technical C-level executives.

## Description

This role involves working directly with leadership to enhance logistics operations through advanced Artificial Intelligence. As an AI Systems & Infrastructure Engineer, you will be responsible for optimizing a proprietary internal large language model platform and developing multi-agent systems to streamline core business functions. Your work will have a significant impact on fleet management and overall business efficiency while allowing you to present innovative AI solutions to C-suite executives., * Collaborate with leadership to maintain and optimize the internal large language model platform, ensuring it meets business needs.

 * Design and implement multi-agent systems that automate key business functions, enhancing operational efficiency.
 * Utilize relational and non-relational databases to support data management and machine learning processes.
 * Engage in prompt engineering and LLM architecture design to improve the performance of AI applications.
 * Present complex technical concepts and project outcomes to non-technical stakeholders, ensuring clear understanding and alignment.


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