AI Product Engineer · Applied AI, backend systems, and product development
I build document-intensive AI workflows with structured output, source traceability, and human review.
My background combines hands-on engineering with product research, startup operations, and grant-backed development.
Industrial work-instruction drafts, with source context and expert review.
I designed and developed the application end to end: document retrieval, structured generation, video-processing workflows, editing, review, version history, and execution checklists.
The engineering focus is traceability: keeping input claims distinct from verified information, validating structured output, and retaining a record of review decisions. The product is a controlled demonstration prototype; generated instructions require qualified expert review.
Python · FastAPI · Pydantic · SQL · Retrieval · Computer vision
Product overview / Presentation / Working paper
Explore the interface · Actual application screens with synthetic demo content; not a production deployment.
| Project | Focus |
|---|---|
| MedAI | Co-founder experience spanning product architecture, analytics, partner communication, and grant work. Public case study of a private healthtech prototype. |
| Engineering Drawing OCR | Contributed to text recognition on technical drawings: preprocessing, recognizer experiments, and evaluation. Runnable synthetic preprocessing demo, tests, and selected reference code. |
Selected contributions accepted by project maintainers:
- Mellea — hardened release-dispatch input validation and literal payload handling.
- Backlot — improved HubSpot object-type compatibility, alongside GitHub API pagination and version-header handling.
- Agent Swarm — corrected environment-flag parsing for integrations and provider configuration.
- Autosubmit — documented YAML configuration loading and override order.
Product and research work across healthtech, industrial AI, and early-stage digital products. Experience with market research, competitor analysis, MVP definition, partnerships, and grant applications. Listed as an author of the registered MedAI software.
Currently pursuing a master's in Computer Science and Engineering through the Digital Ural program, following a bachelor's in Architecture and Civil Engineering.
| Practice | Tools and methods |
|---|---|
| Software engineering | Python, FastAPI, Pydantic, SQL, JavaScript / TypeScript, Docker, REST APIs |
| Applied AI | Retrieval, LLM integration, structured output, OCR, video processing, evaluation |
| Engineering quality | pytest, mypy, Ruff, GitHub Actions, validation and audit trails |
| Product & research | Discovery, market research, competitor analysis, MVP scoping, grant-backed execution |