AI ENGINEER BERLIN
I build Python applications and data pipelines, with a current focus on applied AI. My work includes retrieval-augmented generation, model evaluation and interactive applications for complex data.
Katerina Zhittsova · Applied AI engineer
I build Python applications and data pipelines, with a current focus on applied AI. My work includes retrieval-augmented generation, model evaluation and interactive applications for complex data.
RAG & LLM Evaluation · Python & SQL · Data Engineering
Featured AI project
A learning assistant should help you work through course material and show which sources support its answer. I built this project to compare baseline RAG with layered guardrails: where each check helps, where it rejects a valid request and whether the answer has enough evidence behind it. The Python application separates request checks, scoped retrieval and answer verification, with evidence kept alongside each decision. OpenAI-compatible integrations let suitable embedding and answering models be configured independently.
You can try an offline demo, follow a request through the pipeline, or inspect the tools for reviewing evaluation data. The evaluation workflow keeps calibration separate from final evaluation.
Python applications that connect retrieval, metadata filters and model calls, with checks on the evidence used to answer a question.
Baseline comparisons, answer verification and abstention behavior. I build review tools and keep calibration decisions separate from final evaluation.
Python and SQL pipelines, ingestion debugging, validation checks and reporting datasets, including spatial analysis with PostgreSQL/PostGIS.
My professional background is in energy and agricultural analytics, including Python/SQL workflows, PostgreSQL/PostGIS and reporting used for operational decisions. I've worked with operational, environmental and GPS data, from investigating broken ingestion to building datasets for reporting. I bring that attention to sources and validation into my AI applications.
I'm based in Berlin and seeking an Applied AI Engineer or Data Engineer role, particularly with a team building useful applications around complex data. I have full work authorization in Germany and need no visa sponsorship. More about me.
Latest blog
20 Sept 2026
How to choose the evaluation unit, data split and metrics for predictions, generated answers and sequences of actions, with worked examples and a RAG case study.
Featured case study
6 Apr 2026
A weather, yield, soil, and geospatial analysis project for risk-aware siting and environmental review.
Pinned projects
Built the first public crude benchmark visual bundle, including interactive API/sulfur and regional context views.
Built a rerunnable analytics pipeline for risk-aware siting conversations, with transparent assumptions and map-ready layers.
Browse the full project list on /portfolio.
I like following a result back to its inputs, whether it's an LLM answer or a reporting dataset. That means making the system easy to inspect as well as useful to run.