Summer 2026 Software Engineering, Agentic AI & Test Automation Internship

• Design and develop AI‑powered automation solutions to improve telecom test efficiency
• Build Python‑based backend components that integrate with CI/CD systems such as Jenkins
• Develop and evaluate LLM‑based solutions (e.g., Azure OpenAI, RAG workflows, agent frameworks) for analyzing logs, alarms, and KPI datasets
• Create intelligent workflows for anomaly detection and root‑cause analysis
• Integrate APIs and vendor platforms into internal orchestration and automation tools
• Work with large engineering datasets, including logs, time‑series KPIs, and performance metrics
• Participate in Agile ceremonies, such as daily standups, sprint planning, and team demos
• Present project findings and a final technical deliverable to engineering leadership
• Prototype and implement LLM‑based agents using enterprise‑approved tools such as OpenAI, Claude, or Windsurf
• Design and build data pipelines to process telecom logs, time‑series KPIs, and performance metrics
• Collaborate with domain subject‑matter experts (SMEs) to translate complex telecom requirements into practical automation solutions
• Document system architecture, workflows, and key technical decisions to support ongoing development and knowledge sharing

• At least 18 years of age
• Legally authorized to work in the United States
• Must be actively enrolled in a Bachelors or Graduate degree program
• Employees of T-Mobile or Metro by T-Mobile are ineligible for Internships
• Employer does not sponsor work visas for this position
• Note that this also applies to individuals who are students in F-1 status who desire sponsorship after they complete their education

• Experience working with Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG) architectures, or agent frameworks
• Familiarity with AI/ML ecosystems, including Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex, or vector databases
• Hands‑on experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit‑learn
• Exposure to log analysis, anomaly detection, or time‑series data processing
• Experience with containerization and cloud technologies, including Docker, Kubernetes, or cloud platforms (Azure/AWS)

Relocation assistance may be provided to program participants who reside more than 50 miles from the internship location