AI Development Engineer

iPeople Infosystems LLC Logo
iPeople Infosystems LLC
Dallas, TX, United States
  • Production

Role: AI Development Engineer
Location: Dallas, TX

Type: Contract Position

Job Description

We are seeking a highly skilled AI Development Engineer with strong expertise in telecom domains (4G/5G and OSS/BSS) and advanced AI technologies. The candidate will design and implement AI-driven solutions for test automation, leveraging LLMs and Retrieval-Augmented Generation (RAG) to enhance efficiency and accuracy in telecom testing environments.

Education and Experience:

  • Bachelor s degree in computer science, Information Technology, AI/ML, Data Science, or related field.
  • Certifications in AI/ML technologies , LLM development , or telecom protocols are a plus.

Key Responsibilities:

  • Develop and integrate AI models for telecom test automation using Python , LLMs , and RAG techniques.
  • Short-train and fine-tune AI engines with existing Verizon test scripts, scenarios, and domain-specific data.
  • Generate Robot Framework scripts using GenAI to automate test case creation and execution.
  • Integrate AI solutions with existing test platforms and tools for seamless automation workflows.
  • Perform test execution and IrisView log analysis, generating summaries and actionable insights using AI-driven approaches.
  • Collaborate with QA, DevOps, and network engineering teams to embed AI capabilities into CI/CD pipelines.
  • Design and implement data pipelines for training and inference, ensuring data quality and compliance.

Required Skills:

  • 3+years of experience in AI development and telecom domains (4G/5G and OSS/BSS).
  • Strong proficiency in Python and AI frameworks (TensorFlow, PyTorch, Hugging Face).
  • Hands-on experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
  • Familiarity with GenAI-based script generation and automation frameworks like Robot Framework.
  • Solid understanding of telecom protocols (LTE, 5G NR, Diameter, SIP, etc.).
  • Experience in log analysis and summarization using AI/NLP techniques.
  • Strong problem-solving and debugging skills for AI-driven automation solutions.
  • Knowledge of MLOps practices and deployment of AI models in production.
  • Experience with vector databases (e.g., Pinecone, Weaviate) for RAG implementations.
  • Familiarity with API development and integration for AI services.
  • Exposure to cloud platforms (AWS, Azure, Google Cloud Platform) for AI model hosting.
  • Understanding of CI/CD pipelines and integration with AI workflows.
  • Knowledge of data preprocessing, feature engineering, and prompt engineering for LLMs.
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