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Posted 5h ago

AI Agent Research and Development Intern (787598)

@ Ericsson
United States
OnsiteInternship
Responsibilities:implementing agents, integrating tools, contributing guides
Requirements Summary:Pursuing a Bachelor’s or Master’s in CS or related field; programming in Python or Java; familiarity with REST/JSON, Git; interest in LLMs and agent development.
Technical Tools Mentioned:Python, Java, REST, JSON, Git, LLMs, LangChain, Kiro, OpenAI APIs, vector databases
Job Description
Requisition ID 787598 - Posted  - Country/Area (1) - state/province (1)


Join our Team

About this opportunity:

As an AI Agent Developer Intern, you will help design and build intelligent agents that support real engineering workflows. You will work with experienced engineers to turn concrete business needs into AI-powered tools that automate tasks and improve developer productivity.

 

What you will do:

  • Implement and test AI agents for use cases such as code assistance, documentation support, test automation, and troubleshooting.
  • Integrate agents with internal tools, services, and APIs under guidance from senior developers.
  • Follow good engineering practices (Git, code reviews, basic logging/monitoring).
  • Contribute short usage notes or guides to help engineers adopt the agents

 

The skills you bring:

  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
  • Solid programming skills in at least one backend-oriented language (e.g., Python, Java).
  • Basic understanding of web services/APIs (REST, JSON).
  • Familiarity with Git and collaborative development.
  • Strong interest in applying AI (LLMs, agents) to real engineering scenarios.

 

Nice to Have:

  • Exposure to LLM-based tools or frameworks (e.g., LangChain, Kiro, OpenAI APIs, vector databases).
  • Basic understanding of software testing and CI/CD concepts.

 

What You Will Gain

  • Hands-on experience building AI agents on real engineering data and workflows.
  • Practical understanding of how AI is integrated, evaluated, and adopted in a large engineering organization.
  • Collaboration with AI-focused roles (e.g., AI champions, infrastructure developers, domain experts).