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stakent

Senior systems engineer in Rzeszów seeking remote-only work on correctness-critical systems involving Python, PostgreSQL, FastAPI, LLM-assisted search and document extraction, and deterministic data pipelines.

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Remote Rzeszów senior

Skills

PythonPostgreSQLFastAPILLMsembeddingssemantic searchself-hosted open-weights modelson-prem deploymentoffline systemsdeterministic data pipelinesdeterministic ML pipelinesPDF extractiondocument extractionOCRIoTtime-series datalog analysisdata verificationcorrectness checkinggraph data modeling

Domains

backend data engineering AI/ML document processing search IoT observability systems engineering legal tech
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Location: Rzeszów, Poland
Remote: Yes — remote only (~EU hours or async)
Willing to relocate: No
Technologies: Python, PostgreSQL, FastAPI; LLMs & embeddings, semantic search, self-hosted open-weights models (on-prem, offline); deterministic data/ML pipelines; PDF/document extraction, OCR, IoT, time-series, logs → decision-useful information
Résumé/CV: https://walat.eu/cv/  |  https://linkedin.com/in/dariusz-walat
Email: [email protected]
Trustworthy output from untrustworthy data. I build systems that catch what's silently wrong — a dead sensor nobody noticed, contradictory records, a garbled scan, a confidently-wrong model — so it surfaces as a flag today, not a six-month catastrophe.
I use LLMs where they earn their place (development, meaning, embeddings, plain-language access to jargon-locked data) and keep them out of decisions and the data flow, which stay deterministic and verifiable. An LLM can help you find the answer; it can't be the answer.
Senior systems engineer, multiple AI cycles of judgment on what survives the hype and where it breaks. Currently turning messy Polish legal PDFs into a correctness-checked graph — the hard part is the verification, not the AI. Previously I built a legislative-notification service that ran autonomously in production for over three years before I retired it. I've written about where AI coding agents actually fail and why verification is the real work: https://walat.eu
Best fit when: correctness matters, the data is real-world-messy, and you want someone who names what doesn't work and why.

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