{"id":4022736,"date":"2026-09-24T13:26:13","date_gmt":"2026-09-24T11:26:13","guid":{"rendered":"https:\/\/remoteworkukraine.com\/ua\/remote-job\/data-engineer\/"},"modified":"2026-09-25T21:19:06","modified_gmt":"2026-09-25T19:19:06","slug":"data-engineer-cyberharbor-tech-09-24-2026","status":"publish","type":"job","link":"https:\/\/remoteworkukraine.com\/ua\/remote-job\/data-engineer-cyberharbor-tech-09-24-2026\/","title":{"rendered":"Data Engineer"},"content":{"rendered":"

Cyber Harbor is a fast-growing Ukraine-based company founded by engineers and researchers who helped defend critical infrastructure during the war. Our work is shaped by real-world experience, and we build AI-powered systems designed to handle complex, high-stakes environments.<\/p>\n

We are currently expanding and looking for a strong Data Engineer to help us design and build scalable pipelines for processing large volumes of both structured and unstructured data. These pipelines power comprehensive, interactive knowledge bases used in real-world operations.<\/p>\n

In this role, you will work closely with the core data processing workflows and collaborate daily with software engineers, AI\/ML engineers, DevOps specialists, and the QA team. Because much of the work happens across different parts of the system, strong communication and the ability to collaborate effectively with other teams are essential.<\/p>\n

What You Will Do
– Design and build ETL\/ELT pipelines for large volumes of unstructured data using orchestrators such as Temporal, Prefect, Celery, or Airflow, along with distributed processing engines like Ray and Spark.
– Automate AI-related tasks including text extraction, summarization, OCR, named entity recognition, and embedding generation using various self-hosted models, including some developed in-house.
– Design data schemas and manage storage across multiple systems, including relational databases (PostgreSQL), NoSQL databases (Elasticsearch, Mongodb), vector search engines (Qdrant, Milvus), and graph databases (Neo4j).
– Set up and maintain messaging queues for distributed data processing using tools such as Kafka, RabbitMQ.
– Develop custom Python tools and logic to ensure high throughput, reliability, and fault tolerance in data pipelines.
– Containerize services with Docker and orchestrate deployments using Kubernetes, including on-premise environments.
– Build and maintain CI\/CD pipelines to support reliable development and deployment workflows.
– Monitor infrastructure and pipeline health using Prometheus and Grafana, and manage centralized logging with the ELK Stack.<\/p>\n

What You Need to Join Us
– Strong hands-on experience with SELF-HOSTED data engineering tools.
– Solid Python skills and the ability to build reliable, production-grade data workflows.
– Experience automating workflows that involve different AI models, including self-hosted ones.
– Good understanding of how modern search and RAG systems are designed and operate.
– Familiarity with messaging systems such as Apache Kafka, RabbitMQ.
– Strong understanding of relational databases (PostgreSQL) as well as other data systems such as Elasticsearch, Qdrant\/Milvus, and Neo4j.
– Practical experience with Docker, Kubernetes, and CI\/CD tools (GitHub Actions or GitLab CI).
– Familiarity with monitoring and observability tools such as Prometheus, Grafana, and the ELK Stack.
– Experience working with on-premise infrastructure environments.<\/p>\n

Why Join Us
– Make a Real Impact: Our systems have already been validated in real-world, nation-state level operations.
– Right Place, Right Time: Work at the intersection of AI, large-scale data processing, and cybersecurity.
– Military Deferment: Available for full-time employees.
– Flexible Schedule: Remote-friendly environment focused on results rather than rigid hours.<\/p>\n

\u0420\u0456\u0434\u043d\u043e\u044e<\/p>\n

Cyber Harbor – \u0443\u043a\u0440\u0430\u0457\u043d\u0441\u044c\u043a\u0430 \u043a\u043e\u043c\u043f\u0430\u043d\u0456\u044f, \u0437\u0430\u0441\u043d\u043e\u0432\u0430\u043d\u0430 \u0456\u043d\u0436\u0435\u043d\u0435\u0440\u0430\u043c\u0438 \u0442\u0430 \u0434\u043e\u0441\u043b\u0456\u0434\u043d\u0438\u043a\u0430\u043c\u0438, \u044f\u043a\u0456 \u0431\u0440\u0430\u043b\u0438 \u0443\u0447\u0430\u0441\u0442\u044c \u0443 \u0437\u0430\u0445\u0438\u0441\u0442\u0456 \u043a\u0440\u0438\u0442\u0438\u0447\u043d\u043e\u0457 \u0456\u043d\u0444\u0440\u0430\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438 \u043f\u0456\u0434 \u0447\u0430\u0441 \u0432\u0456\u0439\u043d\u0438. \u041c\u0438 \u0441\u043f\u0438\u0440\u0430\u0454\u043c\u043e\u0441\u044f \u043d\u0430 \u0440\u0435\u0430\u043b\u044c\u043d\u0438\u0439 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0456 \u0441\u0442\u0432\u043e\u0440\u044e\u0454\u043c\u043e AI-powered \u0441\u0438\u0441\u0442\u0435\u043c\u0438 \u0434\u043b\u044f \u0441\u043a\u043b\u0430\u0434\u043d\u0438\u0445 \u0441\u0435\u0440\u0435\u0434\u043e\u0432\u0438\u0449, \u0434\u0435 \u043f\u043e\u043c\u0438\u043b\u043a\u0430 \u043c\u043e\u0436\u0435 \u043c\u0430\u0442\u0438 \u0432\u0438\u0441\u043e\u043a\u0443 \u0446\u0456\u043d\u0443.<\/p>\n

\u0417\u0430\u0440\u0430\u0437 \u043c\u0438 \u0440\u043e\u0437\u0448\u0438\u0440\u044e\u0454\u043c\u043e \u043a\u043e\u043c\u0430\u043d\u0434\u0443 \u0442\u0430 \u0448\u0443\u043a\u0430\u0454\u043c\u043e \u0441\u0438\u043b\u044c\u043d\u043e\u0433\u043e Data Engineer, \u044f\u043a\u0438\u0439 \u0434\u043e\u043f\u043e\u043c\u043e\u0436\u0435 \u043d\u0430\u043c \u043f\u0440\u043e\u0454\u043a\u0442\u0443\u0432\u0430\u0442\u0438 \u0439 \u0440\u043e\u0437\u0432\u0438\u0432\u0430\u0442\u0438 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u043e\u0432\u0430\u043d\u0456 \u043f\u0430\u0439\u043f\u043b\u0430\u0439\u043d\u0438 \u0434\u043b\u044f \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0432\u0435\u043b\u0438\u043a\u0438\u0445 \u043e\u0431\u0441\u044f\u0433\u0456\u0432 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u043e\u0432\u0430\u043d\u0438\u0445 \u0456 \u043d\u0435\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u043e\u0432\u0430\u043d\u0438\u0445 \u0434\u0430\u043d\u0438\u0445. \u0421\u0430\u043c\u0435 \u0446\u0456 \u043f\u0430\u0439\u043f\u043b\u0430\u0439\u043d\u0438 \u0454 \u043e\u0441\u043d\u043e\u0432\u043e\u044e \u043a\u043e\u043c\u043f\u043b\u0435\u043a\u0441\u043d\u0438\u0445 \u0456\u043d\u0442\u0435\u0440\u0430\u043a\u0442\u0438\u0432\u043d\u0438\u0445 \u0431\u0430\u0437 \u0437\u043d\u0430\u043d\u044c, \u0449\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0442\u044c\u0441\u044f \u0432 \u0440\u0435\u0430\u043b\u044c\u043d\u0438\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0439\u043d\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0430\u0445.<\/p>\n

\u0423 \u0446\u0456\u0439 \u0440\u043e\u043b\u0456 \u0432\u0438 \u043f\u0440\u0430\u0446\u044e\u0432\u0430\u0442\u0438\u043c\u0435\u0442\u0435 \u0437 \u043a\u043b\u044e\u0447\u043e\u0432\u0438\u043c\u0438 \u043f\u0440\u043e\u0446\u0435\u0441\u0430\u043c\u0438 \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0434\u0430\u043d\u0438\u0445 \u0442\u0430 \u0449\u043e\u0434\u043d\u044f \u0432\u0437\u0430\u0454\u043c\u043e\u0434\u0456\u044f\u0442\u0438\u043c\u0435\u0442\u0435 \u0437 software engineers, AI\/ML engineers, DevOps specialists \u0456 QA \u043a\u043e\u043c\u0430\u043d\u0434\u043e\u044e. \u0417\u043d\u0430\u0447\u043d\u0430 \u0447\u0430\u0441\u0442\u0438\u043d\u0430 \u0437\u0430\u0434\u0430\u0447 \u043b\u0435\u0436\u0438\u0442\u044c \u043d\u0430 \u0441\u0442\u0438\u043a\u0443 \u043a\u0456\u043b\u044c\u043a\u043e\u0445 \u043a\u043e\u043c\u043f\u043e\u043d\u0435\u043d\u0442\u0456\u0432 \u0441\u0438\u0441\u0442\u0435\u043c\u0438, \u0442\u043e\u043c\u0443 \u0434\u043b\u044f \u043d\u0430\u0441 \u0432\u0430\u0436\u043b\u0438\u0432\u0456 \u0441\u0438\u043b\u044c\u043d\u0456 \u043a\u043e\u043c\u0443\u043d\u0456\u043a\u0430\u0446\u0456\u0439\u043d\u0456 \u043d\u0430\u0432\u0438\u0447\u043a\u0438 \u0442\u0430 \u0432\u043c\u0456\u043d\u043d\u044f \u0435\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e \u043f\u0440\u0430\u0446\u044e\u0432\u0430\u0442\u0438 \u0437 \u0440\u0456\u0437\u043d\u0438\u043c\u0438 \u043a\u043e\u043c\u0430\u043d\u0434\u0430\u043c\u0438.<\/p>\n

\u0429\u043e \u0432\u0438 \u0431\u0443\u0434\u0435\u0442\u0435 \u0440\u043e\u0431\u0438\u0442\u0438
\u041f\u0440\u043e\u0454\u043a\u0442\u0443\u0432\u0430\u0442\u0438 \u0442\u0430 \u0440\u043e\u0437\u0440\u043e\u0431\u043b\u044f\u0442\u0438 ETL\/ELT-\u043f\u0430\u0439\u043f\u043b\u0430\u0439\u043d\u0438 \u0434\u043b\u044f \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0432\u0435\u043b\u0438\u043a\u0438\u0445 \u043e\u0431\u0441\u044f\u0433\u0456\u0432 \u043d\u0435\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u043e\u0432\u0430\u043d\u0438\u0445 \u0434\u0430\u043d\u0438\u0445 \u0456\u0437 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f\u043c \u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0456\u0432 \u043e\u0440\u043a\u0435\u0441\u0442\u0440\u0430\u0446\u0456\u0457, \u0442\u0430\u043a\u0438\u0445 \u044f\u043a Temporal, Prefect, Celery \u0430\u0431\u043e Airflow, \u0430 \u0442\u0430\u043a\u043e\u0436 \u0441\u0438\u0441\u0442\u0435\u043c \u0440\u043e\u0437\u043f\u043e\u0434\u0456\u043b\u0435\u043d\u043e\u0457 \u043e\u0431\u0440\u043e\u0431\u043a\u0438, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 Ray \u0456 Spark.
\u0410\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0437\u0443\u0432\u0430\u0442\u0438 AI-related \u0437\u0430\u0434\u0430\u0447\u0456, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 text extraction, summarization, OCR, named entity recognition \u0442\u0430 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0456\u044e embeddings, \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0447\u0438 \u0440\u0456\u0437\u043d\u0456 self-hosted \u043c\u043e\u0434\u0435\u043b\u0456, \u0443 \u0442\u043e\u043c\u0443 \u0447\u0438\u0441\u043b\u0456 \u0447\u0430\u0441\u0442\u043a\u043e\u0432\u043e \u0440\u043e\u0437\u0440\u043e\u0431\u043b\u0435\u043d\u0456 in-house.
\u041f\u0440\u043e\u0454\u043a\u0442\u0443\u0432\u0430\u0442\u0438 \u0441\u0445\u0435\u043c\u0438 \u0434\u0430\u043d\u0438\u0445 \u0456 \u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043b\u043e\u0433\u0456\u043a\u0443 \u0437\u0431\u0435\u0440\u0456\u0433\u0430\u043d\u043d\u044f \u0432 \u043a\u0456\u043b\u044c\u043a\u043e\u0445 \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u0445 \u043e\u0434\u043d\u043e\u0447\u0430\u0441\u043d\u043e: \u0440\u0435\u043b\u044f\u0446\u0456\u0439\u043d\u0438\u0445 \u0431\u0430\u0437\u0430\u0445 \u0434\u0430\u043d\u0438\u0445 (PostgreSQL), NoSQL-\u0440\u0456\u0448\u0435\u043d\u043d\u044f\u0445 (Elasticsearch, MongoDB), \u0432\u0435\u043a\u0442\u043e\u0440\u043d\u0438\u0445 \u043f\u043e\u0448\u0443\u043a\u043e\u0432\u0438\u0445 \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u0445 (Qdrant, Milvus) \u0456 \u0433\u0440\u0430\u0444\u043e\u0432\u0438\u0445 \u0431\u0430\u0437\u0430\u0445 \u0434\u0430\u043d\u0438\u0445 (Neo4j).
\u041d\u0430\u043b\u0430\u0448\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430 \u043f\u0456\u0434\u0442\u0440\u0438\u043c\u0443\u0432\u0430\u0442\u0438 \u0447\u0435\u0440\u0433\u0438 \u043f\u043e\u0432\u0456\u0434\u043e\u043c\u043b\u0435\u043d\u044c \u0434\u043b\u044f \u0440\u043e\u0437\u043f\u043e\u0434\u0456\u043b\u0435\u043d\u043e\u0457 \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0434\u0430\u043d\u0438\u0445 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0442\u0430\u043a\u0438\u0445 \u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0456\u0432, \u044f\u043a Kafka \u0442\u0430 RabbitMQ.
\u0420\u043e\u0437\u0440\u043e\u0431\u043b\u044f\u0442\u0438 \u043a\u0430\u0441\u0442\u043e\u043c\u043d\u0456 Python-\u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0438 \u0439 \u0432\u043d\u0443\u0442\u0440\u0456\u0448\u043d\u044e \u043b\u043e\u0433\u0456\u043a\u0443, \u0449\u043e \u0437\u0430\u0431\u0435\u0437\u043f\u0435\u0447\u0443\u044e\u0442\u044c \u0432\u0438\u0441\u043e\u043a\u0443 \u043f\u0440\u043e\u043f\u0443\u0441\u043a\u043d\u0443 \u0437\u0434\u0430\u0442\u043d\u0456\u0441\u0442\u044c, \u043d\u0430\u0434\u0456\u0439\u043d\u0456\u0441\u0442\u044c \u0456 \u0432\u0456\u0434\u043c\u043e\u0432\u043e\u0441\u0442\u0456\u0439\u043a\u0456\u0441\u0442\u044c data pipelines.
\u041a\u043e\u043d\u0442\u0435\u0439\u043d\u0435\u0440\u0438\u0437\u0443\u0432\u0430\u0442\u0438 \u0441\u0435\u0440\u0432\u0456\u0441\u0438 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Docker \u0442\u0430 \u043a\u0435\u0440\u0443\u0432\u0430\u0442\u0438 \u0440\u043e\u0437\u0433\u043e\u0440\u0442\u0430\u043d\u043d\u044f\u043c \u0447\u0435\u0440\u0435\u0437 Kubernetes, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 \u0432 on-premise \u0441\u0435\u0440\u0435\u0434\u043e\u0432\u0438\u0449\u0430\u0445.
\u0411\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u0439 \u043f\u0456\u0434\u0442\u0440\u0438\u043c\u0443\u0432\u0430\u0442\u0438 CI\/CD pipelines \u0434\u043b\u044f \u0441\u0442\u0430\u0431\u0456\u043b\u044c\u043d\u0438\u0445 \u0456 \u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0443\u0432\u0430\u043d\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0456\u0432 \u0440\u043e\u0437\u0440\u043e\u0431\u043a\u0438 \u0442\u0430 \u0434\u0435\u043f\u043b\u043e\u044e.
\u0412\u0456\u0434\u0441\u0442\u0435\u0436\u0443\u0432\u0430\u0442\u0438 \u0441\u0442\u0430\u043d \u0456\u043d\u0444\u0440\u0430\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438 \u0442\u0430 \u043f\u0430\u0439\u043f\u043b\u0430\u0439\u043d\u0456\u0432 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Prometheus \u0456 Grafana, \u0430 \u0442\u0430\u043a\u043e\u0436 \u043f\u0456\u0434\u0442\u0440\u0438\u043c\u0443\u0432\u0430\u0442\u0438 \u0446\u0435\u043d\u0442\u0440\u0430\u043b\u0456\u0437\u043e\u0432\u0430\u043d\u0435 \u043b\u043e\u0433\u0443\u0432\u0430\u043d\u043d\u044f \u0447\u0435\u0440\u0435\u0437 ELK Stack.<\/p>\n

\u0429\u043e \u043d\u0430\u043c \u0432\u0430\u0436\u043b\u0438\u0432\u043e
\u0421\u0438\u043b\u044c\u043d\u0438\u0439 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0440\u043e\u0431\u043e\u0442\u0438 \u0437 self-hosted \u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u043c\u0438 \u0434\u043b\u044f data engineering.
\u0412\u043f\u0435\u0432\u043d\u0435\u043d\u0435 \u0432\u043e\u043b\u043e\u0434\u0456\u043d\u043d\u044f Python \u0456 \u0432\u043c\u0456\u043d\u043d\u044f \u0431\u0443\u0434\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0434\u0456\u0439\u043d\u0456 data workflows production-\u0440\u0456\u0432\u043d\u044f.
\u0414\u043e\u0441\u0432\u0456\u0434 \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0437\u0430\u0446\u0456\u0457 \u043f\u0440\u043e\u0446\u0435\u0441\u0456\u0432, \u0449\u043e \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0442\u044c \u0440\u043e\u0431\u043e\u0442\u0443 \u0437 \u0440\u0456\u0437\u043d\u0438\u043c\u0438 AI-\u043c\u043e\u0434\u0435\u043b\u044f\u043c\u0438, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 self-hosted.
\u0420\u043e\u0437\u0443\u043c\u0456\u043d\u043d\u044f \u043f\u0440\u0438\u043d\u0446\u0438\u043f\u0456\u0432 \u043f\u043e\u0431\u0443\u0434\u043e\u0432\u0438 \u0442\u0430 \u0440\u043e\u0431\u043e\u0442\u0438 \u0441\u0443\u0447\u0430\u0441\u043d\u0438\u0445 search \u0456 RAG systems.
\u041f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0440\u043e\u0431\u043e\u0442\u0438 \u0437 \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u043c\u0438 \u043e\u0431\u043c\u0456\u043d\u0443 \u043f\u043e\u0432\u0456\u0434\u043e\u043c\u043b\u0435\u043d\u043d\u044f\u043c\u0438, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 Apache Kafka \u0442\u0430 RabbitMQ.
\u0421\u0438\u043b\u044c\u043d\u0435 \u0440\u043e\u0437\u0443\u043c\u0456\u043d\u043d\u044f \u0440\u0435\u043b\u044f\u0446\u0456\u0439\u043d\u0438\u0445 \u0431\u0430\u0437 \u0434\u0430\u043d\u0438\u0445 (PostgreSQL), \u0430 \u0442\u0430\u043a\u043e\u0436 \u0456\u043d\u0448\u0438\u0445 \u0441\u0438\u0441\u0442\u0435\u043c \u0437\u0431\u0435\u0440\u0456\u0433\u0430\u043d\u043d\u044f \u0439 \u043f\u043e\u0448\u0443\u043a\u0443 \u0434\u0430\u043d\u0438\u0445, \u0437\u043e\u043a\u0440\u0435\u043c\u0430 Elasticsearch, Qdrant\/Milvus \u0456 Neo4j.
\u041f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0440\u043e\u0431\u043e\u0442\u0438 \u0437 Docker, Kubernetes \u0456 CI\/CD-\u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u043c\u0438 (GitHub Actions \u0430\u0431\u043e GitLab CI).
\u0417\u043d\u0430\u0439\u043e\u043c\u0441\u0442\u0432\u043e \u0437 \u0456\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u043c\u0438 \u043c\u043e\u043d\u0456\u0442\u043e\u0440\u0438\u043d\u0433\u0443 \u0442\u0430 observability, \u0442\u0430\u043a\u0438\u043c\u0438 \u044f\u043a Prometheus, Grafana \u0439 ELK Stack.
\u0414\u043e\u0441\u0432\u0456\u0434 \u0440\u043e\u0431\u043e\u0442\u0438 \u0437 on-premise \u0456\u043d\u0444\u0440\u0430\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u043e\u044e.<\/p>\n

\u0427\u043e\u043c\u0443 \u0432\u0430\u0440\u0442\u043e \u043f\u0440\u0438\u0454\u0434\u043d\u0430\u0442\u0438\u0441\u044f
\u0420\u0435\u0430\u043b\u044c\u043d\u0438\u0439 \u0432\u043f\u043b\u0438\u0432 – \u043d\u0430\u0448\u0456 \u0441\u0438\u0441\u0442\u0435\u043c\u0438 \u0432\u0436\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0442\u044c\u0441\u044f \u0432 \u0440\u0435\u0430\u043b\u044c\u043d\u0438\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0439\u043d\u0438\u0445 \u0443\u043c\u043e\u0432\u0430\u0445.
\u0421\u0438\u043b\u044c\u043d\u0438\u0439 \u0442\u0435\u0445\u043d\u0456\u0447\u043d\u0438\u0439 \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442 – \u0432\u0438 \u043f\u0440\u0430\u0446\u044e\u0432\u0430\u0442\u0438\u043c\u0435\u0442\u0435 \u043d\u0430 \u043f\u0435\u0440\u0435\u0442\u0438\u043d\u0456 AI, \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0432\u0435\u043b\u0438\u043a\u0438\u0445 \u0434\u0430\u043d\u0438\u0445 \u0456 \u043a\u0456\u0431\u0435\u0440\u0431\u0435\u0437\u043f\u0435\u043a\u0438.
\u0411\u0440\u043e\u043d\u044e\u0432\u0430\u043d\u043d\u044f – \u0434\u043e\u0441\u0442\u0443\u043f\u043d\u0435 \u0434\u043b\u044f full-time \u043f\u0440\u0430\u0446\u0456\u0432\u043d\u0438\u043a\u0456\u0432.
\u0413\u043d\u0443\u0447\u043a\u0438\u0439 \u0444\u043e\u0440\u043c\u0430\u0442 \u0440\u043e\u0431\u043e\u0442\u0438 – remote-friendly \u0441\u0435\u0440\u0435\u0434\u043e\u0432\u0438\u0449\u0435 \u0437 \u0444\u043e\u043a\u0443\u0441\u043e\u043c \u043d\u0430 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442, \u0430 \u043d\u0435 \u043d\u0430 \u0444\u043e\u0440\u043c\u0430\u043b\u044c\u043d\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a.<\/p>\n","protected":false},"excerpt":{"rendered":"

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