
Telesens
We are a reliable partner in the development and delivery of effective software solutions that always deliver results.
All Telesens products and services are created according to European development standards and are certified according to ISO 9001 and ISO 27001, 27701.
Our 26 years of experience and expertise are confirmed by the high appreciation and feedback from our customers, with whom we build long-term relationships.
Since the company was founded, our client list has been growing and we are very proud to create products for industry leaders.
Our clients are leading Ukrainian companies such as Kyivstar, Lifecell, Ukrtelecom, Vodafone Ukraine, Farlep-Invest, as well as foreign ones: Kazakhtelecom, KCELL, Tele2, Ucell, Jusan Mobile, Ucom Unitel (Beeline UZ).
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Β· 36 views Β· 7 applications Β· 9d
Data Scientist (AI area)
Full Remote Β· Worldwide Β· Product Β· 5 years of experience Β· IntermediateTelesens is looking for Data Scientist with experience in Artificial Intelligence field. Skills and qualifications: β masterβs in Computer Science, Data Science, Artificial Intelligence, or a related field, or equivalent work experience; β strong...Telesens is looking for Data Scientist with experience in Artificial Intelligence field.
Skills and qualifications:
β masterβs in Computer Science, Data Science, Artificial Intelligence, or a related field, or equivalent work experience;
β strong experience in NLP and LLMs, including expertise in large-scale language model architectures (e.g., GPT, BERT, T5);
β hands-on experience with LangChain or similar frameworks for building sophisticated NLP pipelines and applications;
β expertise in Speech-to-Text (STT) and Text-to-Speech (TTS) technologies;
β proficiency in programming languages such as Python, with expertise in NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK);
β solid understanding of machine learning frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience in model training, fine-tuning, and optimization;
β familiarity with cloud platforms and services for deploying machine learning models (e.g., Azure is preferrable);
β strong problem-solving skills and ability to work with complex datasets and large-scale systems;
β excellent communication skills with the ability to collaborate across teams and present complex technical concepts to non-technical stakeholders;
Key Competencies:
β innovation: continuously seek out new technologies and methodologies to enhance NLP and LLM capabilities;
β collaboration: ability to work effectively in a collaborative, cross-functional team environment;
β research excellence: strong focus on staying up-to-date with industry trends and contributing to advancing knowledge in the field;
β results-sriven: deliver high-quality solutions in a timely manner with measurable impact on the business;Responsibilities:
β design, develop, and deploy cutting-edge NLP models, particularly leveraging LLMs (e.g., GPT, BERT, T5) and LangChain, to solve complex real-world problems;
β build and optimize AI Assistants, RAG Assistants, Speech-to-Text (STT) and Text-to-Speech (TTS) systems, improving the quality and performance of voice-based applications;
β develop, fine-tune, and evaluate models in NLP, ensuring that they are scalable, robust, and suitable for real-time applications;
β collaborate with cross-functional teams to understand business problems and translate them into technical solutions using LLMs, NLP, STT, TTS, and related frameworks;
β use LangChain and other tools to create custom NLP pipelines, workflows, and language agents that can integrate into larger systems;
β stay up-to-date with the latest research in LLMs, NLP, STT, TTS, and other emerging AI technologies, and apply this knowledge to improve product offerings;
β conduct performance testing, benchmarking and implement model improvements to ensure high efficiency and reduced latency in deployed models;
β mentor junior team members, providing guidance in model development, research, and best practices in AI/NLP;Will be a plus:
β PhD degree in Computer Science, Data Science, Artificial Intelligence, or a related field, or equivalent work experience;
β experience in deploying NLP models to production environments at scale;
β published research in NLP, LLMs, or related fields (e.g., at top AI conferences such as ACL, EMNLP, NeurIPS);
β experience with reinforcement learning or unsupervised learning techniques in NLP;
β familiarity with conversational AI frameworks (e.g., Rasa, Botpress) or tools for chatbots and virtual assistants;
β knowledge of voice user interface (VUI) design and human-computer interaction (HCI) in the context of TTS/STT systems;
β experience with containerization and orchestration tools like Docker, Kubernetes;
β familiarity with modern DevOps practices, including continuous integration and deployment (CI/CD) for ML systems;
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ΠΠ°ΠΏΡΠ°Π²Π»ΡΡΡΠΈ ΡΠ΅Π·ΡΠΌΠ΅, Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ βΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ β Π²ΡΠ΄ 01.06.2010 β 2297-VI, Π² ΡΠΊΠΎΡΡΡ ΡΡΠ±βΡΠΊΡΠ° ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π½Π°Π΄Π°Ρ Π’ΠΠ βΠ’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’β ΡΠ²ΠΎΡ ΠΏΠΎΠ²Π½Ρ, ΠΎΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½Ρ, Π΄ΠΎΠ±ΡΠΎΠ²ΡΠ»ΡΠ½Ρ ΡΠ° ΡΠ½ΡΠΎΡΠΌΠΎΠ²Π°Π½Ρ Π·Π³ΠΎΠ΄Ρ Π½Π° ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΠΌΠΎΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π·Π°Π·Π½Π°ΡΠ΅Π½ΠΈΡ Π² ΡΠ΅Π·ΡΠΌΠ΅ Π· ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎΡ, ΡΡΠΎΡΠΌΡΠ»ΡΠΎΠ²Π°Π½ΠΎΡ ΡΠ° ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½ΠΎΡ ΠΌΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΡ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ ΠΊΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΡ ΡΡΠ±βΡΠΊΡΠ° Π½Π°ΡΠ²Π½ΠΈΠΌ Ρ Π’ΠΠ βΠ’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’β Π²Π°ΠΊΠ°Π½ΡΡΡΠΌ ΡΠ°/Π°Π±ΠΎ Π·Π°Π½Π΅ΡΠ΅Π½Π½Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ ΡΡΠ±βΡΠΊΡΠ° Π² Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ΠΏΠΎΡΠ΅Π½ΡΡΠΉΠ½ΠΈΡ ΠΊΠΎΠ½ΡΡΠ°Π³Π΅Π½ΡΡΠ² Π’ΠΠ βΠ’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’β. -
Β· 57 views Β· 4 applications Β· 10d
Data Analyst (AI experience)
Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 4 years of experienceTelesens is looking for a Data Analyst with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and Linguistics to support data-driven insights and model evaluations in AI and language technology projects. The ideal...Telesens is looking for a Data Analyst with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and Linguistics to support data-driven insights and model evaluations in AI and language technology projects.
The ideal candidate will have a strong background in linguistics, text analytics, and NLP pipelines, along with the ability to analyze, interpret, and optimize language model performance.
This role involves working closely with data scientists, computational linguists, and AI software engineers to extract insights from textual data, assess LLM outputs, and improve AI-driven applications such as chatbots, speech systems, and knowledge retrieval tools.Qualifications:
- bachelorβs or Masterβs degree in Linguistics, Computational Linguistics, Data Science, AI, or a related field;
- strong understanding of LLMs, NLP concepts, and text analytics;
- experience with Python and NLP libraries (spaCy, NLTK, Hugging Face Transformers, OpenAI API);
- proficiency in SQL and working with structured and unstructured text data;
- familiarity with data visualization tools and reporting dashboards;
- ability to conduct quantitative and qualitative linguistic analysis.
Key Competencies:
- analytical thinking: ability to extract meaningful insights from large-scale text data;
- linguistic expertise: deep understanding of language structures and variations;
- technical proficiency: hands-on experience with NLP tools, LLM APIs, and data visualization;
- collaboration: work effectively with data scientists, engineers, and linguists;
- problem-solving: address challenges in AI-generated text accuracy, fairness, and efficiency.Responsibilities:
Data Analysis & NLP Evaluation:
- analyze large-scale textual and linguistic datasets to identify patterns, biases, and areas for improvement in LLMs;
- evaluate NLP model performance, including sentiment analysis, named entity recognition (NER), text classification, and summarization;
- develop and apply linguistic metrics to assess model fluency, coherence, and grammatical correctness;
- conduct error analysis on AI-generated text to refine model training data and fine-tune outputs.
Data Processing & Visualization:
- clean, preprocess, and structure unstructured text data for AI/ML applications;
- use data visualization tools (Tableau, Power BI, matplotlib, seaborn) to present linguistic trends and NLP model performance insights;
- assist in feature engineering for NLP tasks, including tokenization, lemmatization, and vectorization.
LLM & NLP Model Support:
- work with LLMs (e.g., GPT, BERT, LLaMA, T5) to analyze output quality and linguistic behavior;
- collaborate with engineers on prompt engineering, retrieval-augmented generation (RAG), and knowledge base integration;
- contribute to the development of multilingual NLP applications, ensuring high accuracy across different languages and dialects.
Linguistic Expertise & Research:
- apply linguistic principles (syntax, semantics, pragmatics, phonetics) to optimize NLP pipelines;
- conduct research on bias detection, fairness, and ethical AI in language models;
- assist in annotating and curating linguistic datasets for fine-tuning models in specific domains.Will be a plus:
- experience with LangChain and vector databases for NLP-driven applications;
- knowledge of speech processing (STT, TTS) and phonetics-based text analysis;
- background in multilingual NLP, including working with low-resource languages;
- experience with A/B testing and user experience analysis for AI-driven applications;
- understanding of ethical AI concerns, including bias mitigation and responsible AI practices.ΠΠ°ΠΏΡΠ°Π²Π»ΡΡΡΠΈ ΡΠ΅Π·ΡΠΌΠ΅, Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ Β«ΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Β» Π²ΡΠ΄ 01.06.2010 β 2297-VI, Π² ΡΠΊΠΎΡΡΡ ΡΡΠ±βΡΠΊΡΠ° ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π½Π°Π΄Π°Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» ΡΠ²ΠΎΡ ΠΏΠΎΠ²Π½Ρ, ΠΎΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½Ρ, Π΄ΠΎΠ±ΡΠΎΠ²ΡΠ»ΡΠ½Ρ ΡΠ° ΡΠ½ΡΠΎΡΠΌΠΎΠ²Π°Π½Ρ Π·Π³ΠΎΠ΄Ρ Π½Π° ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΠΌΠΎΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π·Π°Π·Π½Π°ΡΠ΅Π½ΠΈΡ Π² ΡΠ΅Π·ΡΠΌΠ΅ Π· ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎΡ, ΡΡΠΎΡΠΌΡΠ»ΡΠΎΠ²Π°Π½ΠΎΡ ΡΠ° ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½ΠΎΡ ΠΌΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΡ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ ΠΊΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΡ ΡΡΠ±βΡΠΊΡΠ° Π½Π°ΡΠ²Π½ΠΈΠΌ Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» Π²Π°ΠΊΠ°Π½ΡΡΡΠΌ ΡΠ°/Π°Π±ΠΎ Π·Π°Π½Π΅ΡΠ΅Π½Π½Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ ΡΡΠ±βΡΠΊΡΠ° Π² Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ΠΏΠΎΡΠ΅Π½ΡΡΠΉΠ½ΠΈΡ ΠΊΠΎΠ½ΡΡΠ°Π³Π΅Π½ΡΡΠ² Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β».
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Β· 20 views Β· 1 application Β· 14d
Head of IT Infrastructure
Office Work Β· Ukraine (Kharkiv) Β· Product Β· 8 years of experience Β· IntermediateΠΠΎΠΌΠ°Π½Π΄Π° Telesens Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΡΡΡ Ρ ΠΏΠΎΡΡΠΊΠ°Ρ Head of IT Infrastructure Π² ΠΌΡΡΡΡ Π₯Π°ΡΠΊΡΠ² (ΠΌΠ°Ρ Π±ΡΡΠΈ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π·Π° ΠΏΠΎΡΡΠ΅Π±ΠΈ Π²ΠΈΠΉΡΠΈ Π² ΠΎΡΡΡ). ΠΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΠΉΠ½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ: - Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΌ Π°Π΄ΠΌΡΠ½ΡΡΡΡΠ°ΡΠΎΡΠΎΠΌ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΠΎΠΌ Π²ΡΠ΄ 8 ΡΠΎΠΊΡΠ² ΡΠ° ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΈΠΌ ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΡΡΠΊΠΈΠΌ...ΠΠΎΠΌΠ°Π½Π΄Π° Telesens Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΡΡΡ Ρ ΠΏΠΎΡΡΠΊΠ°Ρ Head of IT Infrastructure Π² ΠΌΡΡΡΡ Π₯Π°ΡΠΊΡΠ² (ΠΌΠ°Ρ Π±ΡΡΠΈ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π·Π° ΠΏΠΎΡΡΠ΅Π±ΠΈ Π²ΠΈΠΉΡΠΈ Π² ΠΎΡΡΡ).
ΠΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΠΉΠ½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ:
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΌ Π°Π΄ΠΌΡΠ½ΡΡΡΡΠ°ΡΠΎΡΠΎΠΌ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΠΎΠΌ Π²ΡΠ΄ 8 ΡΠΎΠΊΡΠ² ΡΠ° ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΈΠΌ ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΡΡΠΊΠΈΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ Π²ΡΠ΄ 2 ΡΠΎΠΊΡΠ²;
- Π²ΠΈΡΠΎΠΊΠΈΠΉ ΡΡΠ²Π΅Π½Ρ IT Π΄ΠΎΡΠ²ΡΠ΄ΡΠ΅Π½ΠΎΡΡΡ ΡΠ° Π·Π½Π°Π½Π½Ρ IT Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ²;
- Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΡΡΡΡ, Π±Π°ΠΆΠ°Π½Π½Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ, Π°Π½Π°Π»ΡΡΠΈΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ, Π²ΠΌΡΠ½Π½Ρ ΡΠ²ΠΈΠ΄ΠΊΠΎ ΡΠ΅Π°Π³ΡΠ²Π°ΡΠΈ Π½Π° ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ;
- Π·Π½Π°Π½Π½Ρ ΠΠ‘ Windows Server, Linux (Ubuntu, CentOS ΡΠΎΡΠΎ);
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΌΠ΅ΡΠ΅ΠΆΠ΅Π²ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π°ΠΌΠΈ ΡΠ° ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ (TCP/IP, VLAN, VPN);
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ (Zabbix ΡΠΎΡΠΎ);
- Π±Π°Π·ΠΎΠ²Ρ Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π·Ρ ΡΠΊΡΠΈΠΏΡΠ°ΠΌΠΈ (PowerShell, Bash);
- ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² ΠΊΡΠ±Π΅ΡΠ±Π΅Π·ΠΏΠ΅ΠΊΠΈ;
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΌΠ΅ΡΠ΅ΠΆΠ΅Π²ΠΈΠΌ ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ (Mikrotik, Ubiquiti ΡΠΎΡΠΎ) ΡΠ° Π· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ Π²ΡΠ΄Π΅ΠΎΠ½Π°Π³Π»ΡΠ΄Ρ;
- Π·Π½Π°Π½Π½Ρ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΈ Π½Π° ΡΡΠ²Π½Ρ Intermediate Ρ Π²ΠΈΡΠ΅ (Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡΡ ΡΠ° ΡΠΏΡΠ»ΠΊΡΠ²Π°Π½Π½Ρ Π· ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΎΡ);ΠΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ:
ΠΠ»ΠΎΠΊ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ:
- ΡΠ΅Ρ Π½ΡΡΠ½Π° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ² (1st/2nd line support);
- ΡΠ½ΡΡΠ°Π»ΡΡΡΡ ΡΠ° Π±Π°Π·ΠΎΠ²Π΅ Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΠΎΠΏΠ΅ΡΠ°ΡΡΠΉΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ;
- Π²Π΅Π΄Π΅Π½Π½Ρ ΠΎΠ±Π»ΡΠΊΡ ΡΠ° ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΠ’-ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ;
- Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ ΡΠ΅ΡΠ²Π΅ΡΡΠ² Π½Π° Π±Π°Π·Ρ Windows/Linux;
- ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³, Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ ΡΠ° ΡΡΡΠ½Π΅Π½Π½Ρ Π½Π΅ΡΠΏΡΠ°Π²Π½ΠΎΡΡΠ΅ΠΉ Ρ ΡΠΎΠ±ΠΎΡΡ ΠΠ’-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ;
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠΊΠΈΠΌΠΈ ΠΎΠ±Π»ΡΠΊΠΎΠ²ΠΈΠΌΠΈ Π·Π°ΠΏΠΈΡΠ°ΠΌΠΈ ΡΠ° ΠΏΡΠ°Π²Π°ΠΌΠΈ Π΄ΠΎΡΡΡΠΏΡ (Active Directory, Jira, 1C);
- ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅Π·Π΅ΡΠ²Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΏΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π΄Π°Π½ΠΈΡ ;
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΎΠ½ΠΎΠ²Π»Π΅Π½Π½ΡΠΌΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΎΠ³ΠΎ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ;
ΠΠ»ΠΎΠΊ ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½ΡΡ:
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ IT-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ, ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ°, ΠΎΠΏΠΈΡ ΡΠ° ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅Ρ Π½ΡΡΠ½ΠΈΡ ΡΠ΅Π³Π»Π°ΠΌΠ΅Π½ΡΡΠ²;
- ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎΡ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΠΏΡΠ΄ ΠΏΠΎΡΡΠ΅Π±ΠΈ Π±ΡΠ·Π½Π΅ΡΡ;
- Π±ΡΠ΄ΠΆΠ΅ΡΡΠ²Π°Π½Π½Ρ IT-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΡΠ° ΠΏΠ»Π°Π½ΡΠ²Π°Π½Π½Ρ ΡΡ ΡΠΎΠ±ΠΎΡΠΈ;
- ΠΏΡΠ΄Π±ΡΡ ΡΠ° Π·Π°ΠΊΡΠΏΡΠ²Π»Ρ ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½Ρ ΡΠ° ΠΏΠΎΡΠ»ΡΠ³ Π΄Π»Ρ ΠΠ’-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ;
-ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ°, Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΡΠ° Π°ΡΠ΄ΠΈΡ ΠΏΠΎΠ»ΡΡΠΈΠΊΠΈ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ;
- ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ ΡΠ° Π°Π½Π°Π»ΡΠ· Π½ΠΎΠ²ΠΈΡ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² ΠΠ’-ΡΠ½Π΄ΡΡΡΡΡΡΠΆ;ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ:
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- Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ Π²ΡΡΡΡΠ°Π»ΡΠ·Π°ΡΡΡ (Proxmox, VMware);
β Π΄ΠΎΡΠ²ΡΠ΄ Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ NGINX;
β Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Ρ ΠΌΠ°ΡΠ½ΠΈΠΌΠΈ ΡΠ΅ΡΠ²ΡΡΠ°ΠΌΠΈ (AWS, Azure, Google Cloud);
ΠΠ°ΠΏΡΠ°Π²Π»ΡΡΡΠΈ ΡΠ΅Π·ΡΠΌΠ΅, Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ Β«ΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Β» Π²ΡΠ΄ 01.06.2010 β 2297-VI, Π² ΡΠΊΠΎΡΡΡ ΡΡΠ±βΡΠΊΡΠ° ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π½Π°Π΄Π°Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» ΡΠ²ΠΎΡ ΠΏΠΎΠ²Π½Ρ, ΠΎΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½Ρ, Π΄ΠΎΠ±ΡΠΎΠ²ΡΠ»ΡΠ½Ρ ΡΠ° ΡΠ½ΡΠΎΡΠΌΠΎΠ²Π°Π½Ρ Π·Π³ΠΎΠ΄Ρ Π½Π° ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΠΌΠΎΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π·Π°Π·Π½Π°ΡΠ΅Π½ΠΈΡ Π² ΡΠ΅Π·ΡΠΌΠ΅ Π· ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎΡ, ΡΡΠΎΡΠΌΡΠ»ΡΠΎΠ²Π°Π½ΠΎΡ ΡΠ° ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½ΠΎΡ ΠΌΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΡ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ ΠΊΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΡ ΡΡΠ±βΡΠΊΡΠ° Π½Π°ΡΠ²Π½ΠΈΠΌ Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» Π²Π°ΠΊΠ°Π½ΡΡΡΠΌ ΡΠ°/Π°Π±ΠΎ Π·Π°Π½Π΅ΡΠ΅Π½Π½Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ ΡΡΠ±βΡΠΊΡΠ° Π² Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ΠΏΠΎΡΠ΅Π½ΡΡΠΉΠ½ΠΈΡ ΠΊΠΎΠ½ΡΡΠ°Π³Π΅Π½ΡΡΠ² Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β». -
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Head of IT Infrastructure
Ukraine Β· Product Β· 4 years of experience Β· IntermediateΠΠΎΠΌΠ°Π½Π΄Π° Telesens Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΡΡΡ Ρ ΠΏΠΎΡΡΠΊΠ°Ρ Head of IT Infrastructure Π² ΠΌΡΡΡΡ Π₯Π°ΡΠΊΡΠ² (ΠΌΠ°Ρ Π±ΡΡΠΈ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π·Π° ΠΏΠΎΡΡΠ΅Π±ΠΈ Π²ΠΈΠΉΡΠΈ Π² ΠΎΡΡΡ). ΠΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΠΉΠ½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ: - Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΌ Π°Π΄ΠΌΡΠ½ΡΡΡΡΠ°ΡΠΎΡΠΎΠΌ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΠΎΠΌ Π²ΡΠ΄ 8 ΡΠΎΠΊΡΠ² ΡΠ° ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΈΠΌ ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΡΡΠΊΠΈΠΌ...ΠΠΎΠΌΠ°Π½Π΄Π° Telesens Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΡΡΡ Ρ ΠΏΠΎΡΡΠΊΠ°Ρ Head of IT Infrastructure Π² ΠΌΡΡΡΡ Π₯Π°ΡΠΊΡΠ² (ΠΌΠ°Ρ Π±ΡΡΠΈ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π·Π° ΠΏΠΎΡΡΠ΅Π±ΠΈ Π²ΠΈΠΉΡΠΈ Π² ΠΎΡΡΡ).
ΠΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΠΉΠ½Ρ Π²ΠΈΠΌΠΎΠ³ΠΈ:
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΌ Π°Π΄ΠΌΡΠ½ΡΡΡΡΠ°ΡΠΎΡΠΎΠΌ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΠΎΠΌ Π²ΡΠ΄ 8 ΡΠΎΠΊΡΠ² ΡΠ° ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΎΠ²ΠΈΠΌ ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΡΡΠΊΠΈΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ Π²ΡΠ΄ 2 ΡΠΎΠΊΡΠ²;
- Π²ΠΈΡΠΎΠΊΠΈΠΉ ΡΡΠ²Π΅Π½Ρ IT Π΄ΠΎΡΠ²ΡΠ΄ΡΠ΅Π½ΠΎΡΡΡ ΡΠ° Π·Π½Π°Π½Π½Ρ IT Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ²;
- Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΡΡΡΡ, Π±Π°ΠΆΠ°Π½Π½Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ, Π°Π½Π°Π»ΡΡΠΈΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ, Π²ΠΌΡΠ½Π½Ρ ΡΠ²ΠΈΠ΄ΠΊΠΎ ΡΠ΅Π°Π³ΡΠ²Π°ΡΠΈ Π½Π° ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ;
- Π·Π½Π°Π½Π½Ρ ΠΠ‘ Windows Server, Linux (Ubuntu, CentOS ΡΠΎΡΠΎ);
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΌΠ΅ΡΠ΅ΠΆΠ΅Π²ΠΈΠΌΠΈ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π°ΠΌΠΈ ΡΠ° ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ (TCP/IP, VLAN, VPN);
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ (Zabbix ΡΠΎΡΠΎ);
- Π±Π°Π·ΠΎΠ²Ρ Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π·Ρ ΡΠΊΡΠΈΠΏΡΠ°ΠΌΠΈ (PowerShell, Bash);
- ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² ΠΊΡΠ±Π΅ΡΠ±Π΅Π·ΠΏΠ΅ΠΊΠΈ;
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΌΠ΅ΡΠ΅ΠΆΠ΅Π²ΠΈΠΌ ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ (Mikrotik, Ubiquiti ΡΠΎΡΠΎ) ΡΠ° Π· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ Π²ΡΠ΄Π΅ΠΎΠ½Π°Π³Π»ΡΠ΄Ρ;
- Π·Π½Π°Π½Π½Ρ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΈ Π½Π° ΡΡΠ²Π½Ρ Intermediate Ρ Π²ΠΈΡΠ΅ (Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡΡ ΡΠ° ΡΠΏΡΠ»ΠΊΡΠ²Π°Π½Π½Ρ Π· ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΎΡ);
ΠΠ±ΠΎΠ²'ΡΠ·ΠΊΠΈ:
ΠΠ»ΠΎΠΊ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ:
- ΡΠ΅Ρ Π½ΡΡΠ½Π° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΡΠΏΡΠ²ΡΠΎΠ±ΡΡΠ½ΠΈΠΊΡΠ² (1st/2nd line support);
- ΡΠ½ΡΡΠ°Π»ΡΡΡΡ ΡΠ° Π±Π°Π·ΠΎΠ²Π΅ Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΠΎΠΏΠ΅ΡΠ°ΡΡΠΉΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ;
- Π²Π΅Π΄Π΅Π½Π½Ρ ΠΎΠ±Π»ΡΠΊΡ ΡΠ° ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΠ’-ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½ΡΠΌ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ;
- Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ ΡΠ΅ΡΠ²Π΅ΡΡΠ² Π½Π° Π±Π°Π·Ρ Windows/Linux;
- ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³, Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ ΡΠ° ΡΡΡΠ½Π΅Π½Π½Ρ Π½Π΅ΡΠΏΡΠ°Π²Π½ΠΎΡΡΠ΅ΠΉ Ρ ΡΠΎΠ±ΠΎΡΡ ΠΠ’-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ;
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠΊΠΈΠΌΠΈ ΠΎΠ±Π»ΡΠΊΠΎΠ²ΠΈΠΌΠΈ Π·Π°ΠΏΠΈΡΠ°ΠΌΠΈ ΡΠ° ΠΏΡΠ°Π²Π°ΠΌΠΈ Π΄ΠΎΡΡΡΠΏΡ (Active Directory, Jira, 1C);
- ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅Π·Π΅ΡΠ²Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΏΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π²ΡΠ΄Π½ΠΎΠ²Π»Π΅Π½Π½Ρ Π΄Π°Π½ΠΈΡ ;
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΎΠ½ΠΎΠ²Π»Π΅Π½Π½ΡΠΌΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΎΠ³ΠΎ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ;
ΠΠ»ΠΎΠΊ ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½ΡΡ:
- ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ IT-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ, ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ°, ΠΎΠΏΠΈΡ ΡΠ° ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅Ρ Π½ΡΡΠ½ΠΈΡ ΡΠ΅Π³Π»Π°ΠΌΠ΅Π½ΡΡΠ²;
- ΡΠΎΠ·Π²ΠΈΡΠΎΠΊ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΎΡ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΠΏΡΠ΄ ΠΏΠΎΡΡΠ΅Π±ΠΈ Π±ΡΠ·Π½Π΅ΡΡ;
- Π±ΡΠ΄ΠΆΠ΅ΡΡΠ²Π°Π½Π½Ρ IT-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΡΠ° ΠΏΠ»Π°Π½ΡΠ²Π°Π½Π½Ρ ΡΡ ΡΠΎΠ±ΠΎΡΠΈ;
- ΠΏΡΠ΄Π±ΡΡ ΡΠ° Π·Π°ΠΊΡΠΏΡΠ²Π»Ρ ΠΎΠ±Π»Π°Π΄Π½Π°Π½Π½Ρ ΡΠ° ΠΏΠΎΡΠ»ΡΠ³ Π΄Π»Ρ ΠΠ’-ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ;
- ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ°, Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΡΠ° Π°ΡΠ΄ΠΈΡ ΠΏΠΎΠ»ΡΡΠΈΠΊΠΈ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ;
- ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ ΡΠ° Π°Π½Π°Π»ΡΠ· Π½ΠΎΠ²ΠΈΡ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² ΠΠ’-ΡΠ½Π΄ΡΡΡΡΡΡΠΆ;
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ:
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- Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ Π²ΡΡΡΡΠ°Π»ΡΠ·Π°ΡΡΡ (Proxmox, VMware);
- Π΄ΠΎΡΠ²ΡΠ΄ Π½Π°Π»Π°ΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ NGINX;
- Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Ρ ΠΌΠ°ΡΠ½ΠΈΠΌΠΈ ΡΠ΅ΡΠ²ΡΡΠ°ΠΌΠΈ (AWS, Azure, Google Cloud);
ΠΠ°ΠΏΡΠ°Π²Π»ΡΡΡΠΈ ΡΠ΅Π·ΡΠΌΠ΅, Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ Π΄ΠΎ ΠΠ°ΠΊΠΎΠ½Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ Β«ΠΡΠΎ Π·Π°Ρ ΠΈΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ Β» Π²ΡΠ΄ 01.06.2010 β 2297-VI, Π² ΡΠΊΠΎΡΡΡ ΡΡΠ±βΡΠΊΡΠ° ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π½Π°Π΄Π°Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» ΡΠ²ΠΎΡ ΠΏΠΎΠ²Π½Ρ, ΠΎΠ΄Π½ΠΎΠ·Π½Π°ΡΠ½Ρ, Π΄ΠΎΠ±ΡΠΎΠ²ΡΠ»ΡΠ½Ρ ΡΠ° ΡΠ½ΡΠΎΡΠΌΠΎΠ²Π°Π½Ρ Π·Π³ΠΎΠ΄Ρ Π½Π° ΠΎΠ±ΡΠΎΠ±ΠΊΡ ΠΌΠΎΡΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , Π·Π°Π·Π½Π°ΡΠ΅Π½ΠΈΡ Π² ΡΠ΅Π·ΡΠΌΠ΅ Π· ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½ΡΠΎ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½ΠΎΡ, ΡΡΠΎΡΠΌΡΠ»ΡΠΎΠ²Π°Π½ΠΎΡ ΡΠ° ΠΏΠΎΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½ΠΎΡ ΠΌΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΡ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡΡΡ ΠΊΠ²Π°Π»ΡΡΡΠΊΠ°ΡΡΡ ΡΡΠ±βΡΠΊΡΠ° Π½Π°ΡΠ²Π½ΠΈΠΌ Ρ Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β» Π²Π°ΠΊΠ°Π½ΡΡΡΠΌ ΡΠ°/Π°Π±ΠΎ Π·Π°Π½Π΅ΡΠ΅Π½Π½Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ ΡΡΠ±βΡΠΊΡΠ° Π² Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ΠΏΠΎΡΠ΅Π½ΡΡΠΉΠ½ΠΈΡ ΠΊΠΎΠ½ΡΡΠ°Π³Π΅Π½ΡΡΠ² Π’ΠΠ Β«Π’Π΅Π»Π΅ΡΠ΅Π½Ρ ΠΠ’Β».