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AI Agents & LLM Engineering Experiments

Personal ProjectAI / Full-Stack Engineer (Learning & R&D)Present

Exploring AI engineering through Python-based LLM integrations, agent systems, and practical automation tools built around modern large language models.

Tech Stack

Python

Actively researching and building AI-powered systems focused on Large Language Models (LLMs), agent architectures, and intelligent automation workflows. The work includes experimenting with prompt engineering, tool-based AI agents, structured data processing, and integrating AI capabilities into real-world applications. The goal of this ongoing project is to combine full-stack engineering experience with modern AI development practices.

Responsibilities

  • Building AI agents using Python and modern LLM frameworks
  • Experimenting with prompt engineering and structured outputs
  • Designing tool-calling workflows and agent decision pipelines
  • Integrating LLM capabilities into web applications
  • Working with embeddings, context management, and retrieval concepts
  • Exploring automation and developer productivity tooling powered by AI

Challenges

  • Understanding probabilistic behavior vs deterministic software systems
  • Designing reliable agent workflows and guardrails
  • Managing context windows and information retrieval strategies

Highlights

Represents transition toward AI-augmented software engineering, combining strong frontend/full-stack background with modern LLM-based system design.