AI Development Engineer

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2

Skills

4G
API
Amazon Web Services
Artificial Intelligence
Automated Testing
Business Support Systems
Computer Science
PyTorch
Python
TensorFlow
Vector Databases
Scripting
SIP
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Natural Language Processing
Generative Artificial Intelligence (AI)
Large Language Models (LLMs)

Job Details

Role: AI Development Engineer
Location: Dallas, TX (Onsite)

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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