Senior Full Stack Software Engineer | Applied AI Engineering
Full Stack Software Engineer with experience designing, building, and operating scalable web applications and backend systems across fintech, logistics, and real-time platforms.
Strong understanding of software architecture, API design, system integration, database performance, reliability, and production operations, with the ability to evaluate technical trade-offs and adapt solutions as product requirements evolve.
Currently expanding into Applied AI Engineering, building AI-driven applications and integrating LLMs, AI agents, RAG, vector databases, and agentic workflows into existing software systems.
- LLM-powered application development
- Retrieval-Augmented Generation (RAG)
- Vector embeddings and semantic retrieval
- Vector databases using Chroma
- AI agents and agentic workflows
- LangChain and LangGraph
- Structured LLM outputs
- Tool / function calling
- Integration of AI services with existing backend systems
- Local and API-based LLM integration (Ollama, hosted model APIs)
- AI microservices with Python & FastAPI
- RESTful API design and integration
- Modular and service-oriented architectures
- Database schema design, indexing, and performance optimization
- Redis caching, queues, and background jobs
- Real-time applications and event-driven systems
- Third-party API integrations
- Dockerized development environments
- Linux server administration
- Production debugging and performance optimization
Building production-oriented AI applications that combine traditional backend engineering with modern AI capabilities:
Vue.js → Laravel API → Python/FastAPI AI Services → LLMs → RAG → Tools → Agents
Current areas of focus include:
- Agentic AI systems
- Multi-agent workflows
- RAG architecture
- AI tool/function calling
- LLM evaluation and observability
- AI application reliability and guardrails
- Integrating AI agents with existing SaaS and enterprise applications
- Email: reemramzym@gmail.com
- LinkedIn: Reem Ramzy