Vladimir S.

I build production-ready LLM chatbots and high-speed APIs that move business metrics. 15+ years in Python/FastAPI and data platforms. Led AI and backend at venture-backed and 🏅Fortune-500 products. 🏆 Launched LLM chatbot at GeoDB → new revenue vertical; deployed image generator to boost engagement. 🏆 Cut infra costs 8k→1k €/mo and halved annual budget 180k→90k by smart architecture & consolidation. 🏆 Built ETL pipelines (PyArrow/DuckDB) turning reports from days→minutes; scaled engine 1GB→4TB. 🏆 Hyperice (F500): WebSocket + FastAPI backend for group sessions → +15% engagement and $2M in subs revenue impact. What I deliver: 📦 LLM Chatbots & RAG: ChatGPT/Claude integration, LangChain/LangGraph, retrieval, tools, evals, guardrails. 📦 FastAPI Backends: Low-latency REST/WebSocket services, auth/RBAC, queues, testing, observability. 📦 Data Pipelines/ETL: Airflow jobs, PyArrow/DuckDB, PostgreSQL/MongoDB, analytics-ready models. 📦 Cost & Scale: Docker/AWS, async IO, caching, perf tuning, pragmatic infra that pays for itself. 🛠️ Stacks & keywords: Python, FastAPI, LangChain/LangGraph, OpenAI/Anthropic, RAG, Vector DBs, WebSockets, PyArrow, DuckDB, Airflow, PostgreSQL, MongoDB, AWS, Docker. How we start (low-risk): 🟢 48-hour Diagnostic – clarify use-cases, data, and constraints; mini-POC or architecture plan. 🟢 Milestone Plan – delivery roadmap with success metrics (latency, CTR, retention, cost). 🟢 Build & Ship – iterative releases with tests, dashboards, and handover docs. Results I optimize for: faster CX, higher conversion/retention, lower infra cost, clear analytics. 👉 Ready to move from idea to impact? Invite me with 2–3 lines about your users and goal. I’ll propose a concrete plan and timeline.