AI Backend Engineer focused on building production-ready AI applications, retrieval systems, and scalable backend architectures.

My work sits at the intersection of software engineering, data systems, and applied AI. I design and build the infrastructure that powers intelligent applications—from knowledge retrieval pipelines and API integrations to agentic workflows and cloud-native backend services.

I enjoy transforming unstructured information into reliable AI experiences by combining retrieval systems, structured data pipelines, and modern backend engineering practices.

• Building Retrieval-Augmented Generation (RAG) systems
• Developing AI-powered backend services with Python and Node.js
• Designing knowledge retrieval and semantic search architectures
• Creating agentic workflows and AI automation pipelines
• Deploying scalable AI applications using modern cloud infrastructure
• Improving reliability through evaluation, monitoring, and observability

My background in web development, technical SEO, and digital analytics allows me to approach AI products with both engineering rigor and business impact in mind.

• Retrieval-Augmented Generation (RAG)
• Agentic AI Systems
• Semantic Search
• Knowledge Retrieval Systems
• AI Automation Workflows
• LLM Integrations
• AI Evaluation & Observability

• API Design & Integrations
• Backend Services
• Authentication & Authorization
• Event-Driven Architectures
• Microservices Fundamentals

• Data Modeling
• ETL & Data Pipelines
• Structured & Unstructured Data
• Vector Databases
• Knowledge Bases

• CI/CD
• Cloud Deployments
• Containerization
• Infrastructure Fundamentals
• Scalable Architectures

• AI Evaluation
• Monitoring & Logging
• Performance Optimization
• Reliability & Testing
• Production Readiness

• Technical SEO
• Core Web Vitals
• Digital Analytics
• User Experience
• Performance Optimization