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I am an ML/AI Engineer at Lingaro, working on applied AI systems with a current focus on AI agent-based workflows in Databricks, observability, reliability, and production readiness of LLM-powered applications.
My background combines backend engineering, machine learning engineering, and LLM application development. I have experience with RAG systems, document ingestion pipelines, vector search, semantic retrieval, reranking, response verification, OCR-based automation, backend APIs, and database-driven architectures.
I am also pursuing an M.Sc. in Computer Science at the Military University of Technology in Warsaw, where my academic work focuses on Retrieval-Augmented Generation and agentic RAG systems, including answer correction, retrieval quality, evaluation, and reliability of LLM-generated responses.
Languages: Python, SQL, TypeScript, JavaScript, Java, C#
AI / ML: LLMs, AI Agents, RAG, Agentic RAG, Embeddings, Reranking, OCR, Evaluation
Data Platforms: Databricks, MLflow, Qdrant
Backend: NestJS, REST APIs, Async Processing, Database-driven Architectures
Tools: Docker, Git, Terraform, Jupyter Notebook, Linux, JetBrains IDEs
Databases: PostgreSQL, MySQL, MongoDB, Oracle, Qdrant, Azure MongoDB vCore
Cloud: Azure, AWS, GCP
- AI agents and LLM-powered workflows
- Databricks-based AI systems
- Observability, tracing, and reliability for AI applications
- Retrieval-Augmented Generation and agentic RAG architectures
- Vector search, semantic retrieval, reranking, and response verification
- Backend platforms for applied AI/ML systems
- Evaluation of LLM-generated answers and RAG pipelines
AI Agents · LLM Systems · RAG · Bouldering · Mountaineering · Chess · Woodworking
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