AI Agent Developer

Summary of the Role

AI Agent Developer Intern

Internship Responsibilities

• Agent Development Support:

  Assist senior developers in the design and implementation of core agent components, including memory, planning modules, and tool-use capabilities.

• Prompt Engineering & Fine-Tuning:

  Design, test, and refine prompts to guide LLMs (e.g., GPT, Claude) to perform complex, multi-step tasks accurately.

• Tool/API Integration:

  Write code to connect AI agents to external APIs and internal systems, enabling them to retrieve data and perform actions in real-world environments.

• Data Preparation:

  Assist in preprocessing, cleaning, and preparing data for Retrieval-Augmented Generation (RAG) and model fine-tuning.

• Testing and Documentation:

  Write unit tests and conduct thorough debugging to ensure agent reliability. Document agent architecture, configuration, and performance metrics.

• Research:

  Conduct research on the latest advancements in agentic AI frameworks (like LangChain or AutoGen) and provide summaries and recommendations to the team.

• Ethical AI:

  Contribute to the development of safety checks and guardrails to ensure agents operate ethically and securely.

Required Qualifications and Skills

• Education:

  Currently pursuing or recently graduated with a degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.

• Programming:

  Strong foundational skills in

  Python

  are essential.

• AI/ML Basics:

  Fundamental understanding of Machine Learning concepts, including supervised/unsupervised learning.

• Familiarity with LLMs:

  Basic knowledge of how Large Language Models (LLMs) and Generative AI work.

• Projects/Coursework:

  Demonstrable personal projects, coursework, or a capstone project focused on AI, NLP, or chatbot development.

• Tools:

  Basic experience with Git for version control.

• Soft Skills:

  Eagerness to learn, strong problem-solving skills, and clear communication abilities.

Preferred/Bonus Skills

• Experience with

  AI Agent Frameworks

  (e.g., LangChain, LlamaIndex, AutoGen, CrewAI).
• Familiarity with

  vector databases

  (e.g., Chroma, Pinecone) and the RAG process.
• Knowledge of

  cloud platforms

  (AWS, GCP, or Azure).
• Experience with building RESTful APIs using frameworks like Flask or FastAPI.