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.