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Generative AI Engineer

Job in Houston, Harris County, Texas, 77246, USA
Listing for: Smart IT Frame LLC
Full Time position
Listed on 2026-03-08
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Cloud Engineer - Software, Software Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

We are seeking a skilled Generative AI Developer / Engineer with a strong software engineering background in Java or .NET
, who has transitioned into building Generative AI solutions
. The ideal candidate will have hands‑on experience designing, developing, and deploying AI‑driven applications using modern LLMs and AI frameworks.

Key Responsibilities:

  • Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs)
  • Build AI‑powered applications such as chatbots, copilots, summarization tools, and intelligent automation systems
  • Integrate Generative AI models with Java or .NET–based backend systems
  • Work with APIs and SDKs from LLM providers (OpenAI, Azure OpenAI, Anthropic, etc.)
  • Implement prompt engineering
    , fine‑tuning, and RAG (Retrieval‑Augmented Generation) pipelines
  • Collaborate with product, data, and cloud teams to deliver scalable AI solutions
  • Ensure performance, security, and scalability of AI‑driven applications
  • Stay updated with emerging trends in Generative AI and apply best practices

Required Skills &

Qualifications:

  • Strong experience as a Java Developer or .NET Developer (minimum 3–5 years)
  • 2–3 years of hands‑on experience in Generative AI development
  • Proficiency with LLMs
    , prompt engineering, and AI workflows
  • Experience with Python for AI/ML development
  • Hands‑on experience with frameworks like Lang Chain, Llama Index, Semantic Kernel
    , or similar
  • Knowledge of REST APIs
    , microservices, and cloud‑based architectures
  • Familiarity with vector databases (Pinecone, FAISS, Chroma, Azure AI Search, etc.)
  • Experience working on Azure, AWS, or GCP environments
  • Strong problem‑solving and communication skills

Good to Have:

  • Experience with MLOps / AIOps practices
  • Knowledge of AI model fine‑tuning and evaluation techniques
  • Exposure to CI/CD pipelines and containerization (Docker, Kubernetes)
  • Understanding of data privacy, security, and AI governance
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