10/07/2026 updated
100 % available
AI Engineer & Architect | RAG & Agentic LLM Systems | GenAI Consultant
Teplice, Czech Republic
Only remote
Engineer's degree (Ing.), Software Engineering, University of West Bohemia, PilsenAbout me
AI engineer and architect: 10 years as a developer, 7 in technical product roles, applied AI since late 2022. I take LLM systems from PoC to production, with RAG, agentic orchestration, evals and LLMOps. Led the team behind Česká spořitelna's GenAI chatbot, which serves about 2M clients.
Prompt EngineeringGenerative AIArtificial Intelligence Markup Language (AIML)
Generative AI & Agentic Systems
Design and implementation of RAG pipelines, agentic workflows, tool calling, prompt engineering, and guardrails for production GenAI applications serving millions of users.
LLM Evaluation & LLMOps
Setup of LLMOps pipelines including LLM-as-judge evaluations, eval datasets, red-teaming, retrieval quality testing, LangSmith tracing, and automated error classification.
Software Engineering & Cloud
Proficiency in Python, TypeScript/Node.js, Java, SQL, REST APIs, Docker, Kubernetes, and CI/CD, combined with cloud platforms such as Azure (AI Foundry, AI Search) and AWS.
AI Frameworks
Hands-on experience with LangChain, LangGraph, LangSmith, Langfuse, Claude Code, Codex, and Cursor for building and orchestrating AI systems.
Vector Databases & Data
Experience with PostgreSQL and pgvector, Qdrant, FAISS, and Azure AI Search as hybrid retrievers for semantic search and RAG applications.
Technical Product Leadership
Track record of leading engineering and product teams, defining product strategy, managing Scrum teams, and delivering B2B SaaS platforms from concept to production.
Automated Software Testing
Background in test automation using Java and Selenium, test analysis, quality gates, and teaching automated testing at university level.
API Integration & Rule Engines
Experience integrating third-party APIs such as Creditsafe, writing Python rules for rule engines, and normalizing KYC data from unstructured input.
Design and implementation of RAG pipelines, agentic workflows, tool calling, prompt engineering, and guardrails for production GenAI applications serving millions of users.
LLM Evaluation & LLMOps
Setup of LLMOps pipelines including LLM-as-judge evaluations, eval datasets, red-teaming, retrieval quality testing, LangSmith tracing, and automated error classification.
Software Engineering & Cloud
Proficiency in Python, TypeScript/Node.js, Java, SQL, REST APIs, Docker, Kubernetes, and CI/CD, combined with cloud platforms such as Azure (AI Foundry, AI Search) and AWS.
AI Frameworks
Hands-on experience with LangChain, LangGraph, LangSmith, Langfuse, Claude Code, Codex, and Cursor for building and orchestrating AI systems.
Vector Databases & Data
Experience with PostgreSQL and pgvector, Qdrant, FAISS, and Azure AI Search as hybrid retrievers for semantic search and RAG applications.
Technical Product Leadership
Track record of leading engineering and product teams, defining product strategy, managing Scrum teams, and delivering B2B SaaS platforms from concept to production.
Automated Software Testing
Background in test automation using Java and Selenium, test analysis, quality gates, and teaching automated testing at university level.
API Integration & Rule Engines
Experience integrating third-party APIs such as Creditsafe, writing Python rules for rule engines, and normalizing KYC data from unstructured input.
Experience
Professional experience5 - 10 years
Freelancer since2023
Languages
EnglishFluent
Project history
GenAI projects in financial services, higher education and SaaS, from PoC to production. Projects include routing and eval work for Aibility, RAG search over intranet for Charles University, benchmark tasks for a client under NDA, and Python rules for Terms.Tech B2B BNPL platform. Also delivers workshops and consulting on agentic coding.
Led the team of AI engineers and prompt engineers delivering HeyGeorge v2, the GenAI chatbot in the bank's mobile app serving about 2M clients. Designed agentic orchestration, set up LLMOps pipeline, improved conversational UX, and provided tooling for AI evals. Stack: Node.js, TypeScript, Kubernetes, OpenAI models in Azure, Mistral models fine-tuned in Databricks.
Product strategy for a B2B SaaS dealership management platform, led a product team of 3.