GenAI Engineer — LLM & Agentic Systems

Jobvous Staffing Solutions
  • Houston, Texas
    30+ days ago

    Job Description

    GenAI Engineer — LLM & Agentic Systems

    Can you build a GenAI system that goes to production — not just a demo that impresses in a boardroom?

    About the opportunity:

    Jobvous Staffing Solutions is placing Generative AI Engineers at Houston's energy, technology, and financial services companies. These companies are past the experimentation phase — they're building production RAG systems, multi-agent workflows, and LLM-powered tools that operate at enterprise scale.

    This is the most in-demand AI profile in Houston right now. If you've shipped GenAI systems that real users rely on, we want to talk to you immediately.

    Responsibilities:

    Design and build production RAG pipelines and LLM-powered applications

    Develop multi-agent AI systems using LangChain, AutoGen, or similar frameworks

    Build and deploy AI copilots and decision-support tools for enterprise workflows

    Integrate GenAI solutions with existing enterprise systems via APIs

    Evaluate and fine-tune open-source and proprietary LLMs for domain-specific tasks

    What we are looking for:

    2+ years building production GenAI / LLM systems (not just prototypes)

    Strong Python and prompt engineering skills

    Hands-on experience with LangChain, LlamaIndex, or AutoGen

    RAG architecture, vector databases (Pinecone, Weaviate, ChromaDB) experience

    Azure OpenAI or AWS Bedrock experience highly valued

    GitHub with live GenAI projects is a major differentiator — include your link


    Working Place:

    Houston, Texas

    Numbers & Facts

    LocationHouston, Texas

    Skills

    • Application Programming Interface (API)unmatched
    • Artificial Intelligence (AI)unmatched
    • Decision Supportunmatched
    • Financial Servicesunmatched
    • GitHubunmatched
    • Open Sourceunmatched
    • Product Demonstrationunmatched
    • Production Systemsunmatched
    • Prototypingunmatched

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