Вакансии

Location: Москва Мы - команда инженеров SRE в составе инфраструктурной платформы. Отвечаем за отказоустойчивость нашей системы, прорабатываем различные теории и решения для оценки их внедрения и использования. Ищем в команду коллегу, который поможет нам усилиться и решать новые, сложные задачи. Обязанности •    администрирование и сопровождение облачной платформы Банка в соответствии с принципами ITIL\\ITSM •    управление операционными мощностями, развертывание новых контуров, управление конфигурацией платформы и доступами •    исполнением релизного цикла ПО платформы Частного облака, автоматизирование процессов управления жизненного цикла, сопровождение циклы тестирования и вывод в промышленную эксплуатацию ПО платформы •    обеспечение требуемого уровня надежности и отказоустойчивости платформы, участвовать в проектах по развитию облачной платформы Банка •    автоматизация процессов сопровождения облачной платформы •    работать с дефектами/системой багтрекинга, взаимодействие с разработчиками платформы и смежными подразделениями •    заниматься ведением технической документации. Требования * опыт работы в командах прикладной поддержки в части Ops в процессах DevSecOps, понимал принципы CI/CD, Agile, ITIL\\ITSM * уверенные практические знания Linux на уровне администратора * опыт работы с контейнерной изоляцией (Docker, Kubernetes, OpenShift) или большое желание научиться * опыт работы c платформами виртуализации (VMWare, OpenStack), понимал принципы IaaS, PaaS, IaC * опыт с ELK, Opensearch, Grafana, Zabbix, Prometheus, VictoriaMetrics, PostgreSQL, ClickHouse, Kafka, Redis, Ansible, Jenkins, Bitbucket * уверенное чтение код на Python, bash * инструментальное владение AI для анализа, генерации и автоматизации. Условия * офисный формат работы рядом с м. Кожуховская по адресу: 2-й Южнопортовый проезд,12А * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Cyprus; Finland; Ireland; Malta; Montenegro; Sweden What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: European Union What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Estonia; Greece; Latvia; Lithuania; Poland; Slovakia; Ukraine What you'll be solving A platform engineer opens their AI client of choice, connects it to CAST AI, and types: "Why did our spend jump 40% in eu-west last week?" Thirty seconds later they have an answer, pulled from live cluster state and cost data, with links back to the evidence. No dashboards. No YAML archaeology. Just a question and a correct, permission-checked answer. Your job is to make that interaction boring. Reliably, securely, at production scale. Behind it sits the hard part: an AI assistant that reasons over thousands of production Kubernetes clusters, a platform that safely exposes company infrastructure to external AI clients, and quality pipelines that tell us when the agent is wrong before a customer does. Get it right, and operators stop clicking through consoles entirely. Get it wrong once, and an agent gives a confidently wrong answer to someone managing production. CAST AI already runs Kubernetes infrastructure autonomously. Our automation makes thousands of cost-and-reliability decisions a day. Cast Pilot is the team building the intelligence layer on top of that: AI assistants for Kubernetes and the cloud itself . Our assistant already answers thousands of questions a month from hundreds of organizations. Now we're opening the platform up: a public, permission-aware MCP server so customers can plug CAST AI straight into their own AI clients and agents, deeper connectivity across all three major clouds (AWS, GCP, Azure), and a continuous push to make our agents smarter, better grounded, and more capable. This is greenfield AI platform work on top of battle-tested infrastructure. Most features ship in 1 to 4 weeks. This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices, not just make something work. You're a generalist who is as comfortable debugging a distributed system as designing an auth flow or tuning an agent's behavior. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience building or operating large-scale SaaS platforms in production: multi-tenant systems, high volumes, and the failure modes that only show up at scale. Solid understanding of Kubernetes. Our entire platform runs on it, and the assistants we build answer questions about it. You should be at home with autoscaling, scheduling, and networking concepts. You've personally driven a complex project end-to-end. Hands-on experience with AI coding agents and agentic development workflows. This is how we build, not just what we build. You've used observability tooling in production. CI/CD and DevOps practices experience. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. What will make you stand out You've built agentic systems that shipped : MCP servers or clients, agent gateways, tool-use orchestration, RAG pipelines, evaluation frameworks, and you can talk about what broke in production and how you found out. This is the single biggest differentiator for our team. Deep hands-on experience with one or more of AWS, GCP, or Azure, with real understanding of IAM, compute, networking, and their APIs, not just console-level usage. Experience with LLM application quality: evaluations, prompt engineering at scale, latency and cost optimization of agent loops. Knowledge of OAuth 2.0 / OIDC and multi-tenant authorization design. Deep knowledge of EKS, GKE, or AKS internals. Kubernetes or cloud-native OSS contributions. Responsibilities Design and build the systems behind our AI assistant: agent flows, context retrieval, and the data connections that let it reason about live Kubernetes infrastructure. Build and evolve our public, permission-aware MCP server : curated tools, identity, audit, and strict safety gates, so customers can use CAST AI from their own AI clients. Develop and maintain cloud connectivity across AWS, GCP, and Azure, and the data foundations our agents build on. Write production Go services that interact with cloud provider APIs, the Kubernetes control plane, and LLM APIs in real time. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1 to 4 weeks). Debug novel problems: an agent giving a wrong answer, a cross-cloud permission edge case, a data freshness issue that only appears at scale. Build the quality harness: evals, telemetry, feedback loops, that let us ship agent improvements without regressions. Contribute to product direction and backlog. Shape what gets built next, not just how it's built. Participate in the team's on-call rotation. Tools We Use Daily Programming Languages: Go AI & Agents: MCP (servers and clients), agent gateways, LLM provider APIs, RAG, evaluation pipelines Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Workflows & APIs: Temporal, GCP Pub/Sub, gRPC, REST Observability & Product Analytics: Prometheus, Grafana, Loki, Tempo, PostHog CI/CD & GitOps: GitLab/GitHub CI with ArgoCD and Kargo What's in it for you? Competitive salary (€6,500 to €9,000 gross, depending on the level of experience) Work on genuinely new problems: production MCP platforms and AI assistants for Kubernetes and cloud infrastructure are not solved domains. You'll be defining them, not following a playbook. Equity options. Real users, fast: your work ships to hundreds of organizations in weeks, not quarters. Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development, including access to international conferences and courses. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Требования: — Опыт в CRM-аналитике 2–3+ года в ритейле / e-commerce. — Уверенный Python, продвинутый SQL. — Знание Яндекс Метрики, AppsFlyer, AppMetrica. — Опыт работы с PostgreSQL, Greenplum, ClickHouse. — Понимание CRM-коммуникаций и промо-кампаний. — Анализ временных рядов, pre/promo/post, контрольные группы. — Опыт проведения A/B-тестов. — Высшее математическое или техническое образование. Локация: Москва, гибридный формат работы.

Location: Москва Мы ищем уникального специалиста, который объединит в себе роли Владельца продукта (Product Owner) и Технического лидера (Tech Lead) для нашей команды BI. Вам предстоит не просто управлять бэклогом, а взять на себя полную ответственность за развитие аналитической платформы компании. Ваша миссия — превратить сырые данные в понятные бизнес-инсайты и удобные инструменты для принятия решений. Вы будете работать на стыке бизнеса, аналитики и разработки, определяя стратегию развития отчетности на базе Power BI, управляя сложной архитектурой потоков данных (Apache Airflow) и глубоко погружаясь в специфику нашей внутренней платформы BI. Мы ищем лидера, который сможет выстроить процессы с нуля, задать высокие стандарты качества кода и визуализации, а также сплотить команду вокруг общей цели. Обязанности **В роли Владельца продукта:** * Формирование и приоритизация продуктового бэклога команды BI в тесном взаимодействии с бизнес-заказчиками. * Сбор и формализация требований от стейкхолдеров, их декомпозиция на понятные задачи для команды. * Определение метрик успеха (OKR/KPI) для аналитических отчетов и инструментов, отслеживание их влияния на бизнес-показатели. * Управление ожиданиями заказчиков, планирование релизов и коммуникация о статусе разработки. * Проведение CustDev и интервью с пользователями для выявления реальных потребностей в данных. * Оценка бизнес-ценности задач и защита бюджета на развитие аналитических инструментов. **В роли Технического лида:** * Проектирование архитектуры потоков данных: от источников до витрин и конечных дашбордов. * Разработка и ревью ETL/ELT-процессов на Apache Airflow, оптимизация производительности пайплайнов. * Технический надзор за разработкой дашбордов в Power BI, Navigator BI: контроль соблюдения best practices, оптимизация DAX-запросов и моделей данных, обеспечение читаемости и производительности отчетов. * Настройка и контроль качества данных (Data Quality), управление доступами и ролевой моделью (RBAC). * Внедрение процессов CI/CD для аналитических решений, настройка автоматизированного тестирования данных и отчетов. * Менторинг команды (аналитиков данных и BI-разработчиков), проведение код-ревью, развитие экспертизы сотрудников. * Обеспечение отказоустойчивости и стабильности аналитической платформы, управление техническим долгом. Требования * Опыт работы на стыке Product Owner и Tech Lead (или Lead Data Engineer / Analytics Team Lead) от 3 лет. * Уверенное владение **Power BI** (Desktop и Service): построение сложных моделей данных, оптимизация DAX, разработка сложных мер и расчетных столбцов, настройка Row-level security (RLS). * Глубокое знание **Apache Airflow**: написание кастомных операторов, управление зависимостями (SLA, датчики), работа с XComs, масштабирование исполнителей (Celery/Kubernetes). * Уверенное владение SQL (оконные функции, оптимизация сложных запросов) и Python (Pandas, PyAirflow). * Опыт проектирования хранилищ данных и витрин (DWH/OLAP), понимание подходов Data Vault, Kimball или Inmon. * Понимание принципов работы реляционных и колоночных СУБД (например, Greenplum, ClickHouse, PostgreSQL). * Опыт выстраивания процессов CI/CD для BI (использование Git, dbt или аналогов, автоматизация деплоя отчетов). * Опыт работы с инструментами каталогизации данных и профилирования (например, DataHub, Amundsen или аналоги). **Будет плюсом:** * Опыт работы с Databricks, Spark или другими инструментами Big Data. * Опыт внедрения практик Data Governance и Data Lineage на уровне всей компании. * Знание инструментов продуктовой аналитики (Amplitude, Mixpanel) для обогащения BI-отчетов. * Опыт работы в финтехе, телекоме или крупных e-commerce проектах с высокой нагрузкой на данные. * Опыт работы с **Platform V Navigator BI** (или аналогичным корпоративным BI-конструктором от СберТеха). Понимание принципов работы встроенного оркестратора, каталога данных и механизмов мониторинга платформы. Условия * Гибридный формат работы (современный офис в Москве, м. Кутузовская); * Льготные ипотечные условия кредитования; * Подписка Прайм с возможностью совместного использования на трёх близких; * ДМС с первого дня и скидки на страхование для близких; * Корпоративная пенсионная программа; * Детский отдых и подарки за счет Компании; * Обучение за счет Компании: онлайн курсы, неограниченный доступ к библиотеке и обучение на базе Корпоративного университета, тренинги, митапы и возможность получить новую квалификацию.

Location: Москва Мы приглашаем тебя в команду продукта «Cost IT». Продукт «Cost IT» предназначен для автоматического расчета трудозатрат на change-разработку в рамках инициативы. Инструмент формирует рекомендацию объема трудозатрат в ПШЕ на основе факторов сложности разработки и исторических данных Банка и служит единой объективной точкой отсчета при планировании и согласовании ресурсов. Продукт «Cost IT» реализуется на платформе «EPM» и должен обеспечивать: \* Заполнение владельцем продукта описания инициативы, факторов сложности разработки и ответов на уточняющие вопросы; \* Автоматический расчет рекомендуемого объема трудозатрат в ПШЕ с декомпозицией по видам работ; \* Просмотр и интерпретацию результата расчета, включая объяснимый диапазон трудозатрат; \* Использование результата как референсного значения при заведении инициативы и согласовании с УФК. Обязанности \* Проработка технической архитектуры: проработка интеграционных решений, как компоненты продукта взаимодействуют с друг с другом, описание/тестирование API, проработка интеграционных решений с внешними системами/сервисами \* Проработка продуктовых и технических требований: зафиксировать требования, проработать вместе с командой их реализацию, включая фиксацию алгоритмов и разных сценариев использования \* Настройка платформы инструментами nocode/lowcode в соответствии с бизнес-требованиями: реализация и настройка объектов хранения данных, потоков загрузки данных, настройка мэппингов, настройка бизнес-логики и алгоритмов, разработка форм ввода, разработка отчетов \* Разработка технической документации для backend | frontend разработчиков \* Взаимодействие с аналитиками и архитекторами других команд Платформы \* Контроль реализации требований на всех этапах жизненного цикла разработки \* Консультация разработчиков и других участников команды \* Контроль реализации требований на всех этапах жизненного цикла \* Сопровождение в качестве эксперта в тестировании продукта \* Участие в работе с дефектами и инцидентами для устранения технологических проблем в качестве 3-й линии поддержки \* Применение AI + SDD подхода при проектировании и разработке ПО Требования \* Высшее образование: ИТ, Технические специальности, математика \* Опыт работы от 4 лет в роли ведущего системного аналитика fullstack \* Опыт системного анализа и построения программных продуктов \* Понимание особенностей разных типов БД и принципов хранения данных \* Опыт работы и настройки BI-систем \* Опыт работы с Greenplum и ClickHouse (как преимущество) \* Хорошие знания SQL \* Понимание микросервисной архитектуры \* Умение работать с Rest API (Swagger) \* Понимание принципов работы авторизационных решений (RBAC\\ABAC) \* Опыт работы с системами журналирования, аудита и мониторинга \* Опыт работы с системными и бизнес-требованиями \* Ответственность не только за свою часть, но и за продукт в целом \* Проактивную позицию на каждом этапе жизненного цикла продукта \* Знание технических и технологических решений и тенденций развития в области IT \* Коммуникативные и презентационные навыки Условия * формат работы- офис/гибрид, г. Москва, Кутузовский проспект 32 * ежегодный пересмотр зарплаты, годовой бонус * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE We're looking for an Engineering Manager to lead the Pipelines team at Supabase. Supabase Pipelines is a managed change data capture product. It copies the tables you select from Supabase Postgres to other systems, then streams later changes. The product is in public alpha, with BigQuery, ClickHouse, DuckLake and Snowflake destinations. Pipelines uses Postgres logical replication and Supabase ETL, our open source replication engine written in Rust. The team works close to the database. That means replication slots, WAL retention, initial table syncs, and the load they place on a customer's source database. The team also builds and runs the destination connectors. Correctness, ordering and recovery matter there as much as speed. The Engineering Manager is a people, delivery and technical role. We don't expect you to write production code. We do expect you to join design discussions and help set the bar for engineering quality, testing and operations. WHAT YOU’LL BE RESPONSIBLE FOR Team & People - Build a healthy, high-trust team culture in a remote-first, globally distributed environment. - Run 1:1s, performance management, career development, and onboarding for your direct reports. - Handle people admin (leave, time off, etc.) for your team. Hiring - Own the hiring plan for your team and act as Hiring Manager. First round of interviewer for all roles on the team. - Partner with Talent Acquisition to source, interview, and close strong candidates. - Contribute to headcount planning, org design, and the evolution of engineering leadership at Supabase. Delivery & Roadmap - Own the team's roadmap and project management (Linear), driving accountability and clear milestones. - Manage workflow intake and Slack triage. These are the team’s primary inboxes for cross-team requests. You decide what gets routed where, prioritized, or pushed back on. - Own the team's weekly updates and keep stakeholders aligned without creating overhead. - Organize effort against support tickets and maintain the team's SLO. - Surface risks, dependencies, and tradeoffs early and clearly to leadership. Incident Commander - Train as an Incident Commander. Drive coordination, resolution, and post-incident follow-up. - Lead blameless post-incident reviews YOU MIGHT BE A GOOD FIT IF YOU - Have 5+ years of engineering background, with enough depth to be credible with engineers building complex systems. - Have 3+ years managing remote engineering teams. - Have managed a team that built and ran data pipelines, change data capture, replication or streaming systems. - Have strong technical credibility in data systems. We look for delivery guarantees, ordering, idempotency, schema changes and backfills. - Know Postgres replication well, including logical replication, the WAL and replication slots, and how they affect a production database. - Know analytical destinations such as BigQuery, Snowflake, ClickHouse or lakehouse table formats like Iceberg. - Have led a team through production incidents on a system that holds customer data. You ran the follow-up work and kept the review blameless. - Have shipped a developer-facing data product to customers outside your company. - Have experience with Rust (not required but a plus) - Have managed remote, globally distributed teams that work asynchronously across disparate time zones. - Are technical enough to be credible with strong engineers, but genuinely passionate about people management. This is the work you want to do, not a track you're settling for. - Build psychological safety and a feedback culture. You give feedback often and in the moment, ask for it back, and create space for the team to do the same. - Operate as a multiplier. You help individuals achieve more than they could alone, and you don't need to be the best technical voice in the room. - Coach rather than direct. You remove blockers, connect people to context, and trust your engineers to own how the work gets done. - Have a real track record of performance management and can speak to specific examples of difficult conversations. - Are comfortable with ambiguity and can build structure where there isn't much. - Communicate clearly and write well. You default to async and written, set context early, and surface risks early. - Are collaborative, low-ego and adaptable. You thrive with high-autonomy senior engineers who don't need you to be the smartest person in the room. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Architect on our Data Substrate team About the job Twilio runs on data, and the platform underneath it is entering a major shift. Open table formats, the convergence of lakes and warehouses, tightening privacy regulation, and AI workloads are all changing what a data platform has to do. We’re hiring an Architect to set our direction through that shift and to make sure the systems we build over the next 3-5 years are the right ones. You’ll own the technical strategy for our data platform, spanning storage, lake and lakehouse architecture, catalog and governance, and privacy-by-design. You’ll work across org boundaries, setting standards that dozens of teams build on and raising the technical bar for the engineers around you. Responsibilities In this role, you’ll: Own the architecture and multi-year technical strategy for the data platform, including the lake/lakehouse, ClickHouse, Elasticsearch, and governance, and keep them coherent as one platform rather than separate systems. Define where each engine fits (for example, ClickHouse versus open table formats on object storage) and the migration path between them. Make and document the major design decisions (ADRs, RFCs) on storage and open table formats, catalog strategy, compute engines, tenancy, data placement, and build-versus-adopt tradeoffs, with cost and performance at petabyte scale as explicit design constraints. Set the reference architectures for how our core storage and query engines (ClickHouse, Elasticsearch, and lake engines) are deployed, tuned, scaled and operated as shared platforms, including capacity, cost, tenant isolation, and upgrade strategy. Define the reliability model for the platform: availability targets, failure domains, disaster recovery, observability, and incident response patterns that teams can adopt. Build privacy and compliance into the architecture, not onto it. Design deletion and right-to-erasure, retention, data residency, and PII classification so they work across the platform’s storage layers, backups, and derived datasets, including data that arrives from upstream streaming systems. Drive data governance: classification, catalog and metadata, lineage, access control integrated with our authentication and authorization systems, data contracts, quality and integrity standards, and a catalog teams actually use. Review designs and technical direction across the org, and act as the escalation point on hard distributed-systems and performance problems. Mentor principal and senior engineers, and grow architectural judgment across the org, not only within one squad. Partner with product, security, infrastructure and consuming teams to turn business needs into platform roadmaps, and say no or re-sequence when the tradeoffs require it. Track emerging data technologies (such as streaming-first architectures, federated query, and AI-ready data layers) and bring forward the ones worth adopting, with evidence from prototypes or benchmarks. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 15+ years of experience in software development or a related field, with at least 8 years in an architecture or senior technical leadership role. Proven track record of architecting and delivering large-scale data platforms and setting their technical strategy, on cloud infrastructure such as AWS, deployed with Kubernetes, Terraform and Helm. Deep expertise in storage and compute for analytical data: columnar and open table formats, lake and lakehouse architecture, partitioning, indexing, query planning, and how the choices affect cost and performance at petabyte scale. Breadth across data storage and retrieval technologies, with hands-on depth in at least two of: analytical/OLAP engines (e.g., ClickHouse), search engines (e.g., ElasticSearch/OpenSearch), and lake or distributed processing engines (e.g., Spark, Trino, Flink). You can reason about when to use each, how they interoperate, and how to migrate between them. Working knowledge of streaming systems (e.g., Kafka) and how they interact with downstream storage. Practical experience designing data governance at scale: data classification, catalog and metadata management, lineage, and access control integrated with authentication and authorization systems. Practical experience implementing privacy and compliance requirements (deletion, retention, residency) across a large, heterogeneous data estate. Proficiency in one or more of Python, Java, and Go. Track record of writing and driving architecture decisions across multiple teams, and of changing the direction of an organization’s technical roadmap through influence rather than authority. Experience elevating engineering standards and mentoring senior engineers across teams. Demonstrated commitment to operational excellence: architecting for high availability, observability and incident response in distributed systems, and being credible when a platform is failing in production. Strong written and verbal communication, including making a complex tradeoff clear to engineers and to senior leadership. Desired: Experience operating one of these engines (e.g., ClickHouse, ElasticSearch) at scale, including replication, sharding, ingestion behavior, and multi-tenant isolation. Experience with catalog and metadata systems (e.g., Unity Catalog, Glue, Polaris, DataHub) and open table format catalog strategy. Experience with a platform migration across domains or ownership models, such as moving from central to domain-owned data. A track record of measurable cost optimization on large data platforms. Networking and network security knowledge. Location This role will be remote, and based in the United States. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location Compensation *Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $207,200 - $233,100. Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $219,360 - $246,780. Based in the San Francisco Bay area, California: $243,680 - $274,140. This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Application deadline information Applications for this role are intended to be accepted until 1/4/2027 but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken’s Core Infrastructure Engineering team builds and operates the shared data systems behind critical production services. Our estate spans on-premises and cloud infrastructure, with MariaDB at its centre and Kafka, Redis and Elasticsearch across the wider platform. We’re hiring a Principal Database Engineer to bring long-term experience and technical judgment to this estate. You’ll assess it, set the goals and direction, and work hands-on with the team to deliver measurable improvements. This is an individual contributor role with influence across teams and several quarters of work.   THE OPPORTUNITY - Review the estate against business needs and production evidence. Judge reliability, scale, cost and operational complexity, identifying what should be preserved and where investment or simplification would make a difference. - Define the target architecture and measurable goals. Agree a prioritised roadmap with engineering leads and dependent teams, explaining the trade-offs and sequencing work around delivery risks. - Execute that roadmap with the team through design, implementation and adoption. Stay personally involved in difficult migrations and scaling decisions, with representative benchmarks, data-integrity checks and credible cutover and rollback plans. Adapt the plan as evidence changes and verify the results in production before calling the work complete. - Investigate difficult MariaDB failures and performance limits through the engine, storage and application behaviour. Improve fleet reliability through useful observability, safer changes and tested backup, restore and disaster recovery procedures. Set recovery objectives with service owners and prove them through exercises. - Build and maintain production software for database provisioning, upgrades and routine maintenance. Make self-service workflows safe and auditable, incorporating access controls and change evidence with Security and Compliance. - Work with application teams on schemas, transaction boundaries, queries and data-store choices. Make the operational consequences clear and resolve dependencies that span teams. - Mentor engineers across the team through design reviews, pairing and incident analysis. Help them deepen their database expertise and take ownership of technical decisions. - Participate in on-call and incident response, leaving clear operational ownership and following through on lessons from production.   WHAT YOU BRING - 8+ years operating and evolving production database estates at scale. You have assessed inherited systems, set technical direction and delivered improvements with engineering teams, and can explain how those decisions held up over time. - Strong understanding of high availability, replication and distributed database failure modes. You can explain consistency and availability trade-offs and reason about transaction boundaries and reliable event delivery, including transactional outbox patterns. - Deep, recent hands-on MariaDB expertise, including InnoDB, MVCC and transaction isolation, locking, query optimisation, binary logs and MariaDB GTID replication. You can explain the mechanisms and diagnostic evidence behind your decisions. - Personal ownership of MariaDB incident diagnosis, performance tuning and tested restore or point-in-time recovery. You can explain what you did, how you established data integrity and what remained uncertain. - Strong software engineering skills in Python, Go, Rust or a comparable language. You have personally built and maintained production software or automation for database workflows such as provisioning, failover, online schema changes and self-service operations, using version control, code review and delivery pipelines, with tested failure handling. - Strong low-level Linux, Kernel, storage and networking fundamentals, with the ability to investigate problems beyond the database process. - Clear written technical judgment and demonstrated delivery across teams without reporting-line authority. You help stakeholders make sound database design and lifecycle decisions, and develop experienced engineers through shared delivery.   NICE TO HAVES - Experience operating databases in containerised, hybrid on-premises/cloud or multi-region environments. Familiarity with Kubernetes, infrastructure as code or GitOps, including their operational trade-offs. - Experience with database proxies or load-balancing layers (MaxScale, HAProxy, ProxySQL, or similar). - Experience with PostgreSQL, Vitess, TiDB, ScyllaDB, ClickHouse or internal database platforms; operational knowledge of Kafka, Redis/Valkey or Elasticsearch/OpenSearch. - Experience in regulated environments or contributions to database engines, operators and other infrastructure software. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

- Уверенный опыт работы с данными на позиции аналитика от 4-5 лет. - Опыт работы с аналогичным функционалом в Retail/ FMCG в разрезе продаж, категорий.

Разработка и поддержка интеграций с партнёрами: синхронные REST-вызовы, вебхуки/callback, асинхронные сценарии через Redis-очереди и Kafka; Багфикс и инциденты: разбор по трафик-логам ClickHouse, Sentry/Loki/Grafana, история переходов state machine, сверки с партнёрами;

Workplace: Москва и Краснодар (гибрид/офис), другие города - удаленно Мы ищем ведущего ML-инженера, который возьмёт на себя развитие ML-направления в команде, работающей над продуктами для управления ценами, прогнозирования спроса и формирования коммерческих рекомендаций. Один из основных проектов — система рекомендаций регулярных цен на уровне SKU × магазин. Система анализирует исторические продажи, цены, промо, остатки, будущие поставки, характеристики товаров и магазинов, а также внешние данные, после чего: прогнозирует спрос при различных ценовых сценариях; оценивает ценовую эластичность рекомендует повышение, снижение или сохранение цены прогнозирует влияние решения на продажи, оборот, маржу и EBITDA рассчитывает уверенность модели и риск падения продаж позволяет сравнивать прогноз с фактическим эффектом после применения рекомендации Задачи Развивать модели прогнозирования спроса и ценовой эластичности Исследовать подходы к causal inference и оценки эффекта изменения цены Проектировать временную валидацию, backtesting и бизнес-метрики качества Работать с uncertainty, confidence, intermittent demand, cold start и long-tailSKU Разрабатывать логику выбора оптимальной цены с учётом бизнес-ограничений Организовать оценку plan/fact и мониторинг качества моделей Участвовать в проектировании feature engineering, batch training и batchinference на больших объёмах данных Проводить design review, code review Требования Сильную базу в классическом ML, статистике и работе с табличнымиданными Опыт с forecasting, временными рядами и gradient boosting: LightGBM,CatBoost или XGBoost Понимание causal inference и экспериментального дизайна Опыт доведения ML-моделей до production Уверенное владение Python и SQL Понимание временной валидации, data leakage, calibration и uncertaintyestimation. Опыт работы с Airflow или аналогичным оркестратором Понимание принципов распределённой обработки данных, партиционирования и оптимизации вычислений Умение связывать ML-метрики с измеримым бизнес-эффектом Будет плюсом Опыт в retail, e-commerce, pricing или demand forecasting Практический опыт с PySpark, Trino, Iceberg, S3, dbt или ClickHouse Опыт с price optimization, hierarchical forecasting или operations research Опыт построения ML-мониторинга и проведения A/B-тестов Текущий стек: Python, LightGBM, Airflow, dbt, Trino, Apache Iceberg, Parquet,S3, PostgreSQL, ClickHouse, Kubernetes и gRPC Условия Оформление в аккредитованную ИТ-компанию Конкурентоспособную заработную плату (обсуждается индивидуально) ДМС со стоматологией и льготными условиями для членов семьи Технику для работы График работы 5/2 с гибким началом Работу в максимально уютном офисе в Москве на ст. м. Савеловская, в Краснодаре или удаленно из других городов РФ, так же есть ИТ офисы в Санкт-Петербурге и Иннополисе Возможность проведения и участия в митапах, хакатонах, где есть возможность познакомиться с работой других подразделений Возможность реализовать свой опыт и потенциал в интересных и многоплановых проектах, получить новый интересный опыт в решении сложных задач Наличие корпоративных скидок и программ лояльности Наличие корпоративной библиотеки курсов Формат работы Москва и Краснодар (гибрид/офис), другие города - удаленно

• Опыт в CRM-аналитике 2–3+ года в ритейле / e-commerce.

• модели ставок под CPA/ROAS, а не просто под CTR; • pacing, bid shading, exploration/exploitation на живом аукционе;

-Проектировать архитектуру и разрабатывать ключевые сервисы высоконагруженной платформы. -Развивать асинхронную, событийно-ориентированную архитектуру на базе Apache Kafka.

🏗️ Design robust backend architecture and scalable microservices. ⚙️ Develop high-performance REST APIs and real-time WebSockets.

Задачи: — Разработка low-latency архитектуры и кода на Rust — Реализация дельта-нейтральных стратегий от идеи до запуска в продакшен — Работа с сетью, железом и proximity к бирже — Обработка потоковых данных с использованием Kafka и ClickHouse — Разработка ончейн/DeFi компонентов и бэкенда под AI-агентов Требования: — Опыт создания торговых движков или low-latency торговых систем (свои стратегии или по техническому заданию) — Минимум 3 года опыта работы с production Rust или сильный опыт в low-latency C++ и уверенное владение Rust — Глубокое понимание задержек (latency) как в коде, так и в железе и сети — Опыт запуска стратегий, которые реально приносили доход — Способность самостоятельно ставить задачи и доводить их до результата Условия: — Полностью удалённая работа — Частичное пересечение по времени с часовым поясом UTC+3