Skills
Technologies I use for backend APIs, data layers, deployments, frontends, mobile, and AI features.
Backend
AI Engineering
Practical AI on production Python backends
I build production-oriented AI features—RAG, agents, and LLM integrations—on top of the same Python backends I ship for core product logic. These examples illustrate capability; employment projects are listed separately in the portfolio.
RAG Knowledge Assistant
Retrieval over your documents with citations, access control, and backend APIs the product already uses.
AI Chatbot
Context-aware assistants embedded in admin or customer workflows with guardrails and logging.
AI Agents
Tool-using agents for operational tasks—ticketing, lookups, and structured actions via APIs.
Document Q&A
Upload, chunk, embed, and answer questions over PDFs and knowledge bases.
Semantic Search
Meaning-based search across catalogs, support content, or internal wikis.
AI-powered Automation
Background jobs that classify, summarize, or route work using LLMs and queues.