Aleksei Chenosov
Senior backend engineer with 15+ years of experience building production-grade systems.
About
Senior backend engineer with 15+ years of experience building production-grade systems.
I specialize in high-load and failure-resilient architectures: queues, retries, idempotency, long-running workflows, and real-time platforms. My work typically focuses on making distributed systems stable, predictable, and safe under stress.
I’ve led development of privacy- and compliance-critical products, including encrypted messaging platforms and GDPR-aware systems. In these environments, reliability, correctness, and operational clarity matter more than speed.
I’m usually brought in when backend systems need stronger guarantees around scalability, data safety, or failure handling.
I actively use AI tools to improve development speed, debugging, and architectural exploration, while maintaining strict review and production quality standards.
Tech stack: Node.js, TypeScript, MongoDB, Redis, RabbitMQ, event-driven architectures.
- 11 years' experience
- Joined September 2025
Skills· 15
Languages
- EnglishFluent
- Spanish; CastilianIntermediate
Industry experience
- Healthcare
- Financial Services
- Software & Internet
- Government
- Life Sciences
- Professional Services
- Media & Entertainment
Work experience· 19 roles
Leading backend development for a vascular/neurovascular image processing platform. Designed a DICOM ingestion and normalization pipeline (PACS/Orthanc, ZIP uploads, multi-series CT/MR data; converts to 3D NIfTI) with robust metadata extraction and S3 storage. Implemented a Redis-based orchestration contract between API and Orchestrator (Dagster) enabling asynchronous, scalable processing across distributed components. Integrated validation, normalization, AI-based vascular segmentation/analysis, and results delivery, laying groundwork for PACS interoperability and report generation.
Developed backend platform for vascular imaging, built DICOM ingestion and normalization pipeline, implemented Redis-based orchestration contract with Dagster, integrated AI-based vascular segmentation/analysis, and ensured secure data handling and scalable infrastructure to support hospital deployments and PACS interoperability.
Architecture and backend development for an AI-powered mental health therapy platform. Built secure backend with Node.js, PostgreSQL, Redis, and WebSockets, ensuring end-to-end encryption and GDPR/HIPAA-ready data handling. Developed analytics modules to detect recurring themes, emotional shifts, and long-term therapy patterns; created insight-driven tools to generate personalized therapy recommendations and summarize patient progress. Collaborated closely with clinicians to reduce administrative overhead and support decision-making during live sessions.
Education
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