Вакансии

Задачи: — Администрировать, поддерживать и оптимизировать облачные платформы и инфраструктуру. — Настраивать, конфигурировать, поддерживать и совершенствовать CI/CD- и GitOps-пайплайны. — Внедрять и поддерживать практики Infrastructure as Code (IaC) с использованием таких инструментов, как Ansible, Terraform, Pulumi. — Управлять контейнеризированными средами с использованием Docker, Docker Swarm и Kubernetes. — Обеспечивать надежную инфраструктуру и процессы развертывания для BI-сервисов и приложений, включая ClickHouse, SQL, Airflow, Tableau, Superset. — Тесно взаимодействовать с командами разработки и BI для повышения надежности развертывания, консистентности окружений и операционной эффективности. Требования: — Уверенные навыки настройки и администрирования как минимум одной облачной платформы. — Уверенные навыки построения и автоматизации процессов развертывания с использованием CI/CD и GitOps. — Опыт построения масштабируемой IT-инфраструктуры. — Уверенные навыки настройки Linux-серверов и устранения неисправностей. — Практический опыт работы с Kubernetes. — Понимание сетевой модели OSI. — Понимание принципов построения надежной и масштабируемой инфраструктуры, а также автоматизированных процессов развертывания. — Знание принципов информационной безопасности и защиты данных. — Интерес к работе с инфраструктурой для Business Intelligence и data-related решений либо соответствующий практический опыт.

Задачи: — Отвечать за всю AI-часть продукта: архитектура AI-системы от выбора LLM-моделей до построения RAG-pipeline и интеграции компьютерного зрения, принимать все ключевые технические решения — Обеспечивать качество рекомендаций, повышая конверсию на каждой итерации — Проводить быстрые итерации с выкатыванием изменений каждую неделю, сбором метрик, анализом и улучшением — Проводить эксперименты: A/B тесты промптов, гибридный поиск (текст + визуал + отзывы), мультимодальные модели, быстро проверять гипотезы на реальных пользователях — Масштабировать систему с 2000 туров на Мальдивы до 50,000+ туров по трём направлениям с тысячами запросов в день — Строить продукт с нуля, быстро экспериментировать и влиять на архитектуру Требования: — Опыт с продакшен LLM-приложениями, построение RAG-систем или чат-ботов на основе GPT/Claude — Экспертный уровень промпт-инжиниринга: правильная структура промптов, few-shot examples, chain-of-thought — Опыт работы с эмбеддингами и векторным поиском, понимание similarity search, hybrid search, reranking — Python на уровне продакшена: чистый, быстрый, поддерживаемый код Будет плюсом: — Опыт с компьютерным зрением и мультимодальными моделями (CLIP, GPT-4o, Claude 4.5 Sonnet) — Опыт с high-load системами и оптимизацией latency — Понимание рекомендательных систем — Понимание MLOps: мониторинг моделей, версионирование, A/B тестирование — Опыт построения recommendation систем и MCP для LLM систем — Личный опыт использования LLM для автоматизации задач Софт-скиллы: — Продуктовое мышление: AI как инструмент решения бизнес-задач — Умение работать с метриками: конверсия, время сессии, escalation rate — Быстрота принятия решений: выкатывать несовершенное решение и тестировать — Умение объяснять сложное простым языком для команды и бизнеса Условия: — Официальное оформление по ТК РФ — График 5/2, офис, сокращённый рабочий день по пятницам до 15:30 — Корпоративные программы обучения и развития — Медицинское обслуживание: ДМС и собственная медсанчасть — Специальные предложения от компаний-партнеров (рестораны, магазины, отдых, мероприятия) — Организация отдыха сотрудников и их детей, оплата детского сада — Аккредитованная IT компания — Офис на станции м. Курская — Корпоративные условия на приобретение туров — Дополнительный оплачиваемый отпуск 3 дня, оплата больничного — ДМС для членов семьи по корпоративным условиям — Корпоративные условия на изучение английского и занятия спортом

Location: Warsaw Workplace: OnSite ROLE HIGHLIGHTS: - Title: AIT Engineer – Optical Systems - Department: Global Manufacturing Organization - Reports to: Head of MAITE, Optics - Location: Warsaw, Poland - Type of Contract: Permanent - Working model: On-site - Employment is subject to applicable security screening (incl. SUPO, where required) ABOUT THE ROLE ICEYE is seeking an AIT Engineer to support the assembly, integration, and testing of satellite systems, including the integration of optical payloads into the spacecraft platform. This is a hands-on technical role in an early-stage production environment, where systems are still evolving and processes are not yet fully defined. You will work directly with flight hardware in cleanroom conditions, supporting the assembly, integration, and testing of the satellite bus, as well as the integration and validation of optical payloads provided by external suppliers. You will contribute to bringing the full satellite system from design into production, ensuring that optical payloads are successfully integrated with the satellite platform (bus), and that the system can be built, tested, and scaled reliably. This includes supporting troubleshooting and continuous improvement during production ramp-up. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. WHAT YOU WILL DO - Execute assembly, integration, and testing (AIT) of satellite subsystems and optical payloads - Perform optical alignment and integration activities (focus, tilt, centering, boresight) using precision equipment - Conduct hands-on inspection, assembly, and verification of satellite hardware in cleanroom environments - Support integration of externally supplied optical payloads into the satellite system - Identify, contain, and drive root cause analysis of non-conformances; implement corrective actions and feedback into design and production processes - Define and execute test and verification activities, including integration and acceptance testing at subsystem and system level - Support optical and system-level performance validation - Define, develop, and maintain process plans, procedures, and technical documentation, supporting implementation and continuous improvement of manufacturing and integration processes - Contribute to AIT process definition and improvement, enabling scalable production - Interface with optical, mechanical, and electrical engineering teams to ensure system-level integration - Collaborate with external suppliers during payload integration and validation - Support setup of tooling, fixtures, and test setups (GSE) required for production - Apply system-level understanding to anticipate integration risks across subsystems and ensure successful builds WHAT WE’RE LOOKING FOR MUST HAVE - 3+ years of hands-on experience in integration, testing, or production of complex hardware systems, with relevant experience in optical systems, optomechanics, physics, or other high-precision hardware - Hands-on experience with optical systems integration and alignment (focus, tilt, centering, boresight) - Experience working with optical payloads or Earth Observation systems - Familiarity with optical metrology tools (e.g. interferometers, collimators, optical benches, MTF setups) - Good system-level understanding across multiple disciplines (optical, mechanical, electrical) - Experience working with precision hardware in cleanroom environments - Experience working in structured production environments (e.g. MES or similar systems) - Strong troubleshooting skills with structured root cause analysis - Ability to analyze and interpret test data to support integration and validation activities - Experience developing or working with process plans and technical documentation - Ability to work in fast-paced and evolving production environments - Proactive, hands-on approach to problem-solving - Strong written and spoken English communication skills NICE TO HAVE - Experience supporting environmental testing (e.g. thermal vacuum, vibration) - Experience working with external suppliers or partners - Experience supporting systems from prototype through production ramp-up - Experience working in lean manufacturing or continuous improvement environments APPLICATION PROCESS - Talent Acquisition Interview - Hiring Manager General Interview - Technical Interview (onsite or virtual), including a Technical Challenge - Hiring Team + Director-level Interview - Offer Decision WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. Base salary range for this position is dependent on experience, and will be negotiated individually. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Location: Warsaw, Mazowieckie, Poland; Sofia City, Bulgaria; Limassol, Cyprus Workplace: hybrid Capital.com's Product Security team protects our web and mobile applications, infrastructure, and external perimeter in a highly regulated environment. As Senior/Staff Application Security Engineer, you will raise the bar for application security across the organisation. This role is measured by leverage: how well you design, automate, and scale security processes so that many engineering teams can build securely by default. You will lead security architecture reviews and threat modelling, increasingly with the help of AI tooling, and turn one-off security work into repeatable, self-service capabilities. The role combines deep hands-on offensive and defensive security expertise with the engineering mindset needed to automate at scale. You will work closely with development, QA, DevOps, and platform teams. Responsibilities: Security Architecture & Threat Modelling: Lead security architecture reviews and threat modelling for new and existing systems, using AI tools to make reviews faster, more consistent, and scalable across teams Act as a security force multiplier by influencing the standards, patterns, and guardrails that let teams move fast and stay secure Security Automation & Tooling: Design, build, and automate scalable security processes that engineering teams can self-serve, covering secure design review, threat modelling, testing, and remediation workflows Integrate and automate security checks across the SDLC and CI/CD pipelines (SAST, DAST, SCA, secrets, and IaC scanning), tuned for strong signal and low friction Own and evolve security tooling such as DefectDojo and SAST, DAST, and SCA platforms, maximising automation, coverage, and integration Apply AI and LLM-based tooling to architecture review, threat modelling, code review, and vulnerability triage, and help define how the team adopts these tools safely Security Testing & Vulnerability Management: Conduct and oversee security assessments of web and mobile applications, APIs, and cloud infrastructure, including manual testing and PoC development Run vulnerability scans across internal infrastructure and the external perimeter, then analyse findings, define remediation, and track issues to closure Support and triage the Bug Bounty Program and external vulnerability reports, automating triage where possible Participate in and help lead red teaming and offensive security exercises Enablement: Drive knowledge sharing on secure development, mentor engineers, and deliver training for development and QA teams Requirements: Experience: 5+ years in application or product security, or equivalent depth, with a track record of senior or staff-level impact Demonstrable experience leading security architecture reviews and threat modelling (e.g. STRIDE, attack trees, data-flow analysis) across multiple teams or products Proven ability to automate and scale security processes by building tooling, integrations, and self-service workflows that reduce manual effort Technical: Strong hands-on security testing skills, including code review and web, mobile, and API application security assessments, as well as the ability to triage and validate external vulnerability reports and bug bounty submissions Strong software engineering ability in at least one language (e.g. Python, Go, JavaScript), with the ability to build automation, not just scripts Deep understanding of the OWASP Top Ten, secure design, and secure coding best practices Experience with SAST, DAST, SCA, and vulnerability management platforms, and integrating them into CI/CD Strong understanding of modern application architectures: REST APIs, microservices, cloud-based systems, and containers Practical experience applying AI and LLM tooling to security work, or clear enthusiasm and aptitude to do so Collaboration: Excellent communication and influencing skills: you can explain security concepts to technical and non-technical stakeholders and drive change without direct authority A self-starter who enjoys solving complex problems, building leverage through automation, mentoring others, and strengthening security culture Nice to have: Experience securing the AI harness: hardening LLM and agent pipelines, prompts, tool and MCP integrations, and model endpoints against prompt injection, data leakage, and insecure agent actions Experience securing Kubernetes, including cluster hardening, RBAC, network policies, admission control, workload isolation, and image and supply-chain security Experience securing AWS infrastructure, including IAM, network and account architecture, key and secret management, and CSPM Experience building AI-assisted security tooling or internal self-service security platforms Experience mentoring or technically leading a security team Offensive or advanced security certifications such as OSAI, OSEP, OSCP, or OSWE What you'll get in return: You will join the company, that cares about work and life balance Annual Bonus based on the performance review cycle Generous Annual Leave Policy Medical Insurance and Pension fund, with additional benefit packages based on the location Hybrid working model (3 days from our modern office and 2 days fully remotely) Comprehensive Workation Policy with 30 more remote days available. Possibility of taking two additional days of paid leave per year to dedicate to volunteering efforts.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building high-load products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Lead ML Engineer to own a new ML stream focused on fast delivery of applied machine learning solutions across different product and business domains. The stream will work with a broad range of ML challenges. Some initiatives may be relatively small and delivered within a few weeks, while others may prove their value and grow into larger dedicated projects. This role combines hands-on ML engineering with end-to-end technical delivery ownership. You will receive product problems and expected outcomes from Product or internal stakeholders, clarify the technical requirements and constraints, define the implementation approach, coordinate execution within the stream, and bring solutions to production readiness and launch. This is a highly hands-on role. The stream will not have a dedicated software engineer for every initiative, so we expect Data Scientists and ML Engineers to be comfortable working beyond experimentation and contributing directly to production code. The role is not tied to a single ML domain. We value strong ML fundamentals, engineering skills, pragmatism, and the ability to quickly understand new problem areas more than deep specialization in one particular class of models. Job Responsibilities Technical Delivery Ownership Turn product and business problems into concrete ML implementation plans. Clarify requirements, constraints, available data, integrations, and success criteria together with Product and relevant stakeholders. Define technical scope, milestones, dependencies, risks, and delivery estimates. Select appropriate ML approaches and determine the fastest reliable way to validate and implement them. Drive technical delivery through experimentation, implementation, integration, deployment, and launch readiness. Keep delivery on track, proactively identify blockers, and coordinate dependencies with other teams. Provide Product with clear technical options, trade-offs, estimates, risks, and experiment results required for product decisions. Support production rollout and iteration based on observed results. Hands-on ML & Engineering Design, train, evaluate, and deploy ML models across different domains and problem types. Write production-quality Python and contribute directly to implementation. Build APIs, batch jobs, data-processing pipelines, and ML services required to deliver solutions where appropriate. Work with classical ML, deep learning, and foundation-model-based approaches depending on the problem. Process and transform large production datasets using Python and SQL. Integrate models into existing production systems. Implement appropriate testing, monitoring, logging, and observability for delivered ML solutions. Work within the shared ML infrastructure, architecture, and engineering practices used across the company. Collaborate with Data Science, Backend, Data Engineering, and MLOps specialists when deeper domain expertise or infrastructure changes are required. Stream Execution Break initiatives down into concrete technical tasks and coordinate execution within the stream. Coordinate the work of Data Scientists and ML Engineers contributing to stream initiatives. Review technical approaches, experiments, and implementation. Keep the team focused on the agreed scope, priorities, and delivery timeline. Identify technical risks and dependencies early and drive them to resolution. Escalate architectural, infrastructure, or methodological questions when broader alignment is required. Help prepare successful initiatives for scaling or transition into longer-term ownership if they grow beyond the scope of the stream. Cross-functional Collaboration Work closely with Product throughout the delivery lifecycle. Independently gather the technical details and constraints required to execute on a product request. Communicate estimates, dependencies, technical trade-offs, and delivery status clearly. Work directly with Engineering and other internal teams to unblock implementation. Challenge technically unclear, contradictory, or infeasible requirements and propose practical alternatives. You’ll thrive here if you have 5+ years of commercial experience in Machine Learning, Data Science, or ML Engineering. Strong hands-on Python programming and software engineering skills. Experience taking ML solutions from a product requirement through experimentation, implementation, integration, and production. Strong understanding of machine learning methods, statistics, experimentation, and model evaluation. Experience writing maintainable production code rather than working exclusively in notebooks. Experience building APIs, services, batch processing, or data pipelines. Strong SQL skills and experience working with large production datasets. Practical experience with Docker and production deployment environments. Ability to turn partially defined problems into concrete technical plans. Ability to estimate work, identify dependencies and risks, and drive technical execution against a timeline. Experience owning technical delivery involving several contributors and coordinating work across dependencies. Experience reviewing code and technical approaches. Ability to work effectively within established engineering and ML practices while independently owning delivery within a stream. Strong communication skills and the ability to work directly with Product and technical stakeholders. Ability to balance speed and engineering quality: validate ideas quickly when uncertainty is high and build robust solutions when moving towards production. Nice to Have Previous experience as a Tech Lead, Stream Lead, or technical owner of ML initiatives. Experience with Kubernetes and CI/CD. Experience with Kafka or other streaming platforms. Experience with Airflow, MLflow, experiment tracking, model monitoring, or similar tooling. Experience building real-time or high-load ML services. Experience with FastAPI or similar Python service frameworks. Experience across several ML domains, such as recommendation systems, ranking, NLP/LLMs, Computer Vision, anomaly detection, forecasting, or classification. Experience with LLM inference, fine-tuning or other GenAI systems. Experience in teams where Data Scientists and ML Engineers own a substantial part of production implementation themselves.

Задачи: — Разработка и поддержка пайплайнов. — Проектирование ETL/ELT-процессов для переноса данных из PostgreSQL и других источников в ClickHouse. — Написание надёжных и идемпотентных DAG в Airflow для регулярного обновления витрин данных. — Построение слоёв данных с использованием dbt. — Обеспечение качества данных: тесты, проверка свежести, мониторинг аномалий. — Оптимизация хранилища и производительности. — Тюнинг ClickHouse: настройка схем таблиц под конкретные бизнес-запросы, устранение узких мест. — Оптимизация SQL-запросов для снижения нагрузки на БД. — Управление ресурсами кластера ClickHouse: CPU, RAM, Disk I/O. — Контроль стоимости хранения. — Администрирование и надёжность. — Обеспечение отказоустойчивости: настройка репликации и бэкапов. — Мониторинг состояния пайплайнов и баз данных. — Оперативное реагирование на инциденты. Требования: — Глубокое знание ClickHouse. — Проектирование схем: знание семейства движков MergeTree, выбор ключей партиционирования и сортировки для оптимального сжатия и скорости чтения. — Оптимизация запросов: умение читать планы запросов, оптимизировать потребление памяти, настраивать материализованные представления (Materialized Views) и проекции. — Администрирование: настройка шардирования и репликации, управление TTL, мониторинг слияний. — Инструменты ETL/ELT и оркестрация. — Оркестрация: управление сбором данных через Apache Airflow. — Трансформация: опыт работы с dbt для построения слоев данных. — Языки и инфраструктура. — Python: разработка ETL-скриптов, работа с Pandas, интеграция с API. — SQL: владение на уровне эксперта (аналитические запросы, оптимизация). — Инфраструктура: Docker (для развертывания ClickHouse), Git. Условия: — Удаленная работа из любой точки мира. — Конкурентная зарплата + performance премия 2 раза в год. — Гибкий график и фокус на результат. — Оплата обучения, курсов и конференций. — Возможность реально влиять на продукт и команду.

Задачи: — Проектировать и разрабатывать AI-агентов; — Разрабатывать и оптимизировать промпты, учить агентов взаимодействовать с продуктами компании; — Решать задачи NLP: классификация, суммаризация, NER, семантический поиск, кластеризация и другие; — Писать поддерживаемый, читаемый код в рамках разработки AI-агентов (Python 3.12+); — Участвовать в разработке на всех этапах жизненного цикла AI/ML (от предобработки данных до деплоя и мониторинга в проде); — Выводить GenAI-приложения в прод совместно с DevOps-командой. Требования: — Опыт создания агентов на современных фреймворках (LangChain, LangGraph, LlamaIndex, Agno, Pydantic AI Harness и др.); — Знание стратегий планирования AI-агентов (ReAct, Plan-and-Execute и т.д); — Уверенная работа с LLM API (OpenAI, vLLM, Anthropic и др.); — Понимание агентских протоколов (MCP, A2A, AG-UI); — Сильный prompt engineering + chain/tool/function calling; — Опыт работы с векторными БД (Weaviate, Pinecone, Qdrant, Milvus и др.); — Опыт оценки качества LLM-систем (RAGAS, DeepEval, LLM-as-a-Judge или аналоги); — Опыт работы с Linux, Git, Docker, умение упаковать своего агента в контейнер. Условия: — Официальное оформление по ТК РФ; — Профессиональные митапы и встречи для обмена опытом; — Сообщества по интересам: спорт, игры, книги, аниме; — Гибкий график без контроля времени работы; — ДМС со стоматологией с первого месяца; — Обучение: сертификация, профильные курсы, конференции, митапы, хакатоны, CTF-ы; — Свободная атмосфера без дресс-кода и бюрократии; — Поддержка креатива и возможность профессионального роста; — Скидки на фитнес, покупки и многое другое; — Корпоративные мероприятия, спортивные старты, мерч и подарки; — Команда экспертов, выступления на конференциях, публикации; — Забота о здоровье и регулярные синки по проектам; — Прозрачные коммуникации и свобода от бюрократии; — Финансирование сертификации, обучения и участия в мероприятиях.

Location: Armenia; Bulgaria; Spain; Albania; Ukraine; Greece; Croatia; Serbia; Poland; Moldova; Portugal; Italy; Türkiye; Montenegro; Romania Workplace: Remote Location: Fully remote, EU timezone (CET ±2h) Start date: ASAP Languages: Fluent English required Industry: Cloud Computing / GPU Infrastructure ABOUT THE OPPORTUNITY Pragmatike is hiring a Senior SRE / Infrastructure Engineer to help operate and scale a distributed infrastructure platform spanning bare-metal GPU nodes, Kubernetes, virtualization, networking, and multi-site environments. You’ll work close to the infrastructure itself, from BMCs, hardware and MAAS provisioning through Kubernetes, networking, observability, automation, and site operations. This is a hands-on role for someone who enjoys owning infrastructure end-to-end, building reliable systems, and automating everything that can be automated. Startup or hyper-growth experience is a strong plus: autonomy, ownership, and speed matter here. WHAT YOU’LL DO - Operate and maintain large-scale Linux infrastructure across Debian/Ubuntu-based bare-metal and virtualized environments. - Own MAAS-based bare-metal provisioning, including region/rack controllers, PXE, commissioning, cloud-init, node lifecycle, and API/CLI automation. - Operate and maintain production Kubernetes clusters, including upgrades, node pools, networking, storage, security hardening, and troubleshooting. - Design and maintain multi-site networking across VLANs, L2/L3 routing, bonded interfaces, VPNs, firewalls, and DNS. - Automate infrastructure provisioning and operations using Ansible, Bash/Python, OpenTofu/Terraform, and Git-based workflows. - Build and maintain automated deployment workflows including PXE, Preseed, and cloud-init. - Operate observability platforms using Prometheus, Grafana, Alertmanager, VictoriaMetrics/VictoriaLogs, or comparable tooling. - Define and improve SLIs, SLOs, alerting, and reliability practices across infrastructure and platform services. - Lead infrastructure incident response, troubleshooting, escalation, and post-incident improvements. - Maintain on-call processes and operational coverage across distributed environments. - Work close to the hardware layer, including IPMI/Redfish, BMCs, RAID, storage, hardware diagnostics, and GPU infrastructure. - Manage virtualization platforms including Proxmox, KVM/libvirt, OpenStack, or VMware, including GPU passthrough where required. - Build and maintain internal infrastructure tooling for host discovery, configuration, IPAM, hardware health, and operational automation. - Own infrastructure lifecycle activities including site onboarding, maintenance, decommissioning, drift detection, and operational runbooks. - Work closely with engineering and cross-functional teams to improve reliability, resource utilization, and operational efficiency. WHAT WE’RE LOOKING FOR - 5+ years of hands-on SRE, Infrastructure, Systems, or Platform Engineering experience. - Expert-level Linux administration, particularly Debian/Ubuntu. - Strong production experience with MAAS and bare-metal provisioning. - Expert-level, hands-on experience operating Kubernetes in production, including cluster lifecycle, networking, storage, upgrades, and troubleshooting. - Strong network engineering skills across VLANs, L2/L3 routing, bonding, VPNs, firewalls, and DNS. - Strong automation skills with Ansible, Bash and/or Python. - Experience with Terraform/OpenTofu and Git-based infrastructure workflows. - Production experience with Prometheus/Grafana or comparable observability platforms. - Experience with incident response, on-call operations, monitoring, alerting, and reliability practices. - Experience with Proxmox, KVM/libvirt, OpenStack, VMware, or comparable virtualization technologies. - Experience with bare-metal hardware, BMCs, IPMI/Redfish, storage, and hardware troubleshooting. - Strong understanding of distributed systems, container orchestration, and infrastructure reliability. - Experience with infrastructure security including RBAC, firewalls, network policies, secrets management, and security hardening. - Ability to create SOPs, runbooks, and operational processes from scratch. - Comfortable working autonomously in a fast-paced, engineering-driven environment. NICE TO HAVE - Experience operating GPU infrastructure or GPU-heavy Kubernetes/bare-metal environments. - Proxmox VE with ZFS/Ceph and GPU passthrough. - VictoriaMetrics / VictoriaLogs or similar large-scale observability platforms. - NetBox or other IPAM / infrastructure inventory platforms. - Vault, SOPS, Atlantis, or similar infrastructure security and automation tooling. - Experience with Cloudflare APIs, DNS automation, or tunnels. - Experience with UniFi or comparable site networking platforms. - Experience with service mesh or advanced CNI implementations. - Go experience, particularly for infrastructure tooling or custom exporters. - Experience with Ceph or distributed databases running on bare metal. - Experience operating infrastructure across multiple sites and timezones. - Experience establishing SRE frameworks and reliability practices in growing organizations. WHY JOIN US - 100% remote with flexible working hours - High-impact role with significant technical ownership and autonomy - Work directly with bare-metal, Kubernetes, networking, and GPU infrastructure - International, engineering-driven team - Strong focus on automation, reliability, and infrastructure at scale - Opportunity to shape the architecture and operational foundations of a growing cloud platform Pragmatike is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation. In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration.

Задачи: — Построение и руководство командой инженеров машинного обучения, включая найм, коучинг и формирование чувства ответственности и влияния. — Определение технического видения и дорожной карты Safety ML в сотрудничестве с командой и партнерами из Trust & Safety, Product, Policy, Legal и Data Science. — Управление полным жизненным циклом производственных моделей безопасности: определение новых возможностей, измерение производительности и мониторинг состояния систем, принимающих миллионы решений по обеспечению безопасности ежедневно. — Управление процессами и применение технической экспертизы для повышения качества работы команды. — Сотрудничество с Trust & Safety по вопросам качества меток, золотых наборов и автоматизации ручных расследований. — Работа с другими менеджерами по инженерии для постоянного улучшения организации и поддержания философии рабочего места. Требования: — Опыт работы не менее 5 лет в качестве инженера машинного обучения, дата-сайентиста или прикладного учёного. — Опыт работы не менее 3 лет в роли инженерного менеджера с успешным управлением командой из 5 и более инженеров. — Глубокие практические знания в одной или нескольких областях: обнаружение злоупотреблений/мошенничества, классификация контента, поведенческое моделирование, графовое моделирование или классификация на основе больших языковых моделей (LLM). — Сильные коммуникативные навыки и умение эффективно работать в кросс-функциональных командах. — Способность работать в условиях неопределённости, находить решения сложных проблем и реализовывать их. — Мыслить с позиции первых принципов и совместно с другими находить прагматичные решения. — Подтверждённый опыт вывода ML-систем в продакшн в масштабах. — Страсть к коучингу и лидерству, а также готовность при необходимости активно участвовать в кодировании. — Постоянное отслеживание отраслевых трендов и внедрение новых технологий для решения технических задач. Условия: — Полная занятость. — Удалённая работа из США или офис в районе залива Сан-Франциско. — Годовой базовый оклад от $272,000 до $340,000 плюс акции и социальные гарантии. — Зарплата определяется уровнем роли, навыками, опытом и образованием. — Компенсация указана без учёта акций и дополнительных льгот.

Joi Lab (joilab.ai) is an open research arm building open-source generative models, agent architectures, and training infrastructure. All code, weights, and data are public. The focus is on true AI agency with persistent memory, self-modification, and self-authored capabilities, not just ChatGPT wrappers. The role involves working with huge models up to 1 trillion+ parameters, ensuring fast and cheap production inference, and technologies like SGLang, caching, distributed inference, and post-training. The candidate will also set the technical direction for NLP and CV engineers. Требования к кандидату: — 5+ years of experience in ML engineering — Deep hands-on experience optimizing LLM inference — Proficiency with PyTorch and related libraries — Experience with distributed inference/training of large models — Strong understanding of inference optimization techniques — Proven technical leadership in guiding engineers — Backend engineering experience (Python, Go, C#) — Advanced English or Russian language skills

Workplace: remote Location : Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world. Responsibilities : Provision AWS infrastructure with Terraform and configure Linux hosts in AWS and the external data center with Ansible, so every environment can be rebuilt from code. Build and run a Kubernetes cluster for shared platform services (observability, Keycloak, HashiCorp Vault, web applications), delivered through GitOps with Argo CD and Helm. Build and maintain GitLab CI pipelines for infrastructure and platform services. Integrate corporate SSO through Microsoft Entra ID and keep user and group IDs consistent across all sites and compute pools. Set up monitoring and alerting across compute pools and platform services with Prometheus and Grafana. Implement encryption, key management, least-privilege access and audit logging, and support the client's security review. What we expect : 5+ years of experience in DevOps, Platform, or Cloud Engineering, including ownership of production environments. Strong hands-on experience with AWS (VPC, IAM, EKS, EC2, S3, KMS) and Terraform. Strong Linux administration skills and Ansible experience. Production experience with Kubernetes, Helm, and Argo CD. Experience building CI/CD pipelines with GitLab CI or GitHub Actions. Experience with Prometheus and Grafana. Experience with SSO integration (OIDC/SAML) using Keycloak and Microsoft Entra ID. Experience with HashiCorp Vault for secrets management. Solid networking knowledge: routing, DNS, firewalls, site-to-site IPSec VPN and hybrid cloud connectivity. Python and Bash scripting for automation. Ability to work independently and communicate directly with client IT, network and security teams. Nice to have : Experience with HPC environments: Slurm, AWS ParallelCluster, Open OnDemand. Experience with Argo Workflows. Experience with hybrid storage and data transfer: NetApp ONTAP, AWS DataSync, rclone. Experience in pharma, life sciences, or other regulated industries. AWS certifications. We offer : Competitive compensation Remote or office work Flexible working hours Healthcare benefits: medical insurance and paid sick leave Continuous education, mentoring, and professional development programs A team with an excellent tech expertise Certifications paid by the company

Location: Australia, Adelaide Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Service Reliability Engineer Our Site Reliability Engineering team plays a significant role in delivering on the promise of a great cloud gaming experience to our customers. We do this by influencing design and operational decisions towards the overall stability of the gaming service. Our SREs focus on three main things: overall ownership of production, production code quality, and deployments. The successful candidate will be self-directed and able to participate in the way we make decisions at different levels. We expect our SREs to have opinions on the state of our service and provide critical feedback during different phases of the operational lifecycle. We are engaged throughout the software development lifecycle, ensuring operational readiness and stability. Requirements Minimum of 7+ years working experience in Software Development and/or Linux Systems Administration role. Strong interpersonal, written and verbal communication skills. Available to be scheduled in on-call rotation. Skills & Knowledge Proficient as a Linux Production Systems Engineer, with experience managing large scale Web Services infrastructure. Development experience in one or more of the following programming languages: Python (preferred) Bash, Go, Java, C++, or Rust In addition, experience with at least 3 of the following topics: Distributed data storage at scale (Hadoop, Ceph) NoSQL at scale (MongoDB, Redis, Cassandra) Data aggregation technologies. (ElasticSearch, Kafka) Scaling and running traditional RDBMS (PostgreSQL, MySQL) with High Availability Monitoring & alerting (Prometheus, Grafana), and Incident Management toolsets Kubernetes and/or AWS (deployment and management) Software distribution (Package management and distribution at scale) Configuration management (ansible, saltstack, puppet, chef) Software performance analysis and load testing (QA or SDET experience: a plus) Responsibilities Taking a leadership role in ongoing improvements in Reliability and Scalability Work closely with SRE Management to define KPIs, processes and drive continuous improvement Influence the architecture and implementation of solutions within the division Mentor more junior SRE staff and enable them for success Act as a voice to represent SRE in the wider organisation Represent the operational scalability of solutions in the wider division Lead small-scale projects from inception to implementation Design platform-wide solutions and provide technical leadership during their implementation Demonstrate a high-level of organizational skills and initiative in the role Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Задачи: — Взять на себя ключевую часть сетевой и VPN-инфраструктуры проекта. Требования: — Senior-уровень в сетях: TCP/IP, UDP, DNS, TLS/HTTPS, маршрутизация, NAT; — серьёзный практический опыт с VPN, туннелированием и Xray; — опыт работы именно с крупными VPN-проектами; — глубокое понимание DPI, фильтрации трафика, блокировок и причин деградации соединений; — сильный Linux и сетевая диагностика; — опыт с dedicated-серверами, VPS/VDS, CDN, дата-центрами и хостинг-провайдерами; — плюсом будет практический опыт колокации собственного оборудования; — умение проектировать отказоустойчивую инфраструктуру, способную переживать сбои и изменения сетевых ограничений без постоянного ручного вмешательства; — способность быстро исследовать изменения в сетях, ставить эксперименты, находить причины проблем и внедрять решения; — постоянная погружённость в VPN-индустрию и понимание того, что в ней происходит прямо сейчас; — опыт работы в крупном VPN-сервисе и знание индустрии изнутри; — хорошее ориентирование в рынке хостингов и дата-центров, понимание особенностей разных провайдеров и умение строить масштабируемую и отказоустойчивую инфраструктуру для сотен тысяч пользователей; — VPN-инфраструктура и сети — основная профессиональная специализация. Условия: — полностью удалённо, full-time; — только основная работа — без параллельной работы и учёбы; — зарплата 350 000–1 000 000 ₽ на руки, итоговая сумма зависит от уровня, опыта и компетенций.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team, focused on using Claude to speed up protein and small-molecule design. You'll work with research partners to apply modern design and structure models to real discovery problems, and build the agents and skills that turn those tools into end-to-end workflows. This role is about applying design models, not building new ones. Responsibilities Work with research partners on protein and molecular design end-to-end with Claude, from advising, to prototyping, to writing production code. Work in a design–make–test loop with wet-lab partners (e.g. antibody-repertoire mining, MD prep / trajectory analysis at proteome scale) and turn the expert steps into reusable agents/skills. Build agents and skills that wrap design and structure tools into end-to-end workflows. Support research efforts aimed at better understanding the protein sequence-to-function relationship Help partners measure where AI speeds up their design cycles, and where it doesn't. Drive product, engineering and research direction from field experience, e.g. benchmarks and evals for design and structure tasks (capabilities and safety). Scale your impact to the long tail of labs through reusable skills, cookbooks and docs. Be an ambassador for Claude in molecular design, from small settings to large conferences. You Might Be a Good Fit If You Have Hands-on experience applying protein or small-molecule design to real drug development programs, in an AI-first biotech, pharma, a rare-disease non-profit, a research institute, or a translational academic design lab. Experience with molecular dynamics (system prep, trajectory analysis) or large-scale antibody/immune-repertoire data, and with closing the loop against experimental results from a partner lab. Hands-on use of modern design and structure tools (e.g. AlphaFold, RFdiffusion, ProteinMPNN, Rosetta) to solve design problems, not only to build new models. Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance. Deep understanding on how to quantitatively measure success in drug design, experimentally and computationally. A scientist's instinct for understanding how AI can, and cannot, facilitate protein research and design Experience working directly with external customers or partners in a technical role. Clear written and verbal communication: docs partners can use without you, and talks that earn researchers' trust. A scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Almaty, Kazakhstan; Astana, Kazakhstan; Belgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Monterrey, Mexico; Montevideo, Uruguay; Odesa, Ukraine; Remote.AR, Remote.LATAM-country; Remote.BR, Brazil; Remote.BG, Bulgaria; Remote.CO, Colombia; Remote.GE, Georgia; Remote.KZ, Kazakhstan; Remote.PL, Poland; Riga, Latvia; Rosario, Remote.LATAM-country; Sofia, Bulgaria; Tbilisi, Georgia; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland; Yerevan, Armenia We are looking for a very senior hands-on Data Engineer with strong SAP BW and Snowflake experience who has led engineering teams. About 70% of the engineering work is extracting data from SAP BW and integrating it into Snowflake. You will work side by side with a recently appointed Engineering Manager who comes from a non-engineering background, helping them build engineering leadership skills. Together you will grow the team toward independent, high-performing delivery: operating model, engineering practices, standards and delivery discipline. The goal is for the client's team to run independently within about a year. You will get there through coaching-by-doing and knowledge transfer rather than long-term vendor dependency. The client is headquartered in Southern California, USA. Working on site for the first 4–6 weeks is mandatory for this role, to build trust and work directly with the Engineering Manager and the team. After that, you will be on site a few days a week during the following weeks. A valid US visa, or the ability to obtain one quickly, is required. The project supports a large international consumer goods company that is scaling its Snowflake-based data platform. Selected datasets are moved from SAP BW into Snowflake one business case at a time. They feed data products for sales and distribution, retail and market analytics, and e-commerce. The platform is already critical to the business: hundreds of business users work every day with AI-powered analytics built on Snowflake Cortex and Streamlit. Design, build and run data pipelines from SAP BW into Snowflake, including full and delta loads Do hands-on engineering work while coaching the Engineering Manager and the team Help the Engineering Manager build engineering leadership skills: planning, code quality, technical decision-making, managing engineers and contractors Establish reusable ingestion, modeling and data quality patterns for the team Define and roll out engineering standards: code review, testing, CI/CD, documentation, delivery discipline Deliver data products for sales, distribution and retail analytics in close collaboration with business stakeholders Work with a distributed team of internal engineers and external contractors across time zones Reduce key-person dependency through knowledge transfer and pairing Help introduce AI-assisted and agentic engineering practices across the development lifecycle Work with the Lead Architect to keep delivery aligned with target architecture and governance 7+ years of hands on data engineering experience including lead roles Hands on experience extracting data from SAP BW into a cloud data warehouse Strong hands on experience with Snowflake including data loading performance cost awareness security and access model Experience with data modeling approaches such as dimensional modeling or Data Vault Experience with data quality practices Experience with dbt Experience leading a team of around 10 engineers Experience coaching a manager or team lead into an engineering leadership role through hands on collaboration Experience working with distributed teams and external contractors or vendors Experience applying AI in engineering or data work with a concrete example of problem solution tools and outcome English Upper Intermediate or higher Readiness to work on site in Southern California for 4–6 weeks at the start of the engagement Experience with SAP BW/4HANA, SAP Datasphere or migrations from SAP to cloud platforms Snowflake Cortex, Streamlit or semantic layer experience CPG, retail or distribution domain; retailer data platforms or syndicated market data (POS, Nielsen-type datasets) Experience building an engineering operating model or data engineering maturity roadmap Exposure to Microsoft Fabric or Databricks Experience with international client-facing engagements

Location: France; Poland; Romania; Bulgaria; Italy; Hungary Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the Role We are looking for an experienced Aircraft Maintenance Engineer holding a valid EASA Part-66 B1 License to join an international technical operations team. In this role, you will perform and certify complex aircraft maintenance activities, coordinate on-site technical interventions, and ensure compliance with strict aviation safety and quality standards. CONTRACT: Permanent COMMITMENT: Full-time LOCATION: Relocation to France needed, worldwide missions NOTES: EU passport is mandatory Requirements Valid EASA Part-66 B1 License 2+ current aircraft type ratings 5+ years of experience in aircraft maintenance or certifying roles Experience certifying maintenance activities on commercial aircraft Strong knowledge of aviation maintenance procedures and safety regulations Professional working proficiency in English Willingness to travel internationally for customer support assignments Ability to work effectively in a fast-paced operational environment

Location: New York, NY (HQ); San Francisco, CA; Remote (US) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT PRODUCTION ENGINEERING Production Engineering is Ramp's infrastructure ownership layer. We exist to make Ramp faster, more reliable, and more scalable — and we do that by being embedded in the problems, not adjacent to them. A few things that define how we operate: - One team, one company, one objective. There is no "infra team" and "product team" — there is Ramp. We share the company's goals as our own. When a product team struggles with reliability or scalability, that is our struggle. - If reliability or scalability is at risk, we own it. We don't wait to be invited, and we don't ask whose code it is. If a system is slow, if it breaks, if it won't scale — that's ours to lead, regardless of where it lives in the stack. - We go first, and we go fast. When the path isn't obvious, we don't wait for someone else to find it. We move with urgency, propose the solution, align the stakeholders, and stay in until it's done — not until our ticket is closed. - We lead the way. We find the next problem before it finds us. And when we solve it, we don't just fix it for ourselves — the patterns and standards we establish become the foundation the rest of Ramp builds on. That's not a side effect of the job; it's the job. - We stay calibrated. Speed means nothing if we're moving in the wrong direction. We regularly stop and ask honestly whether what we're working on is still the highest-leverage thing we could be doing — the discipline that makes sure our effort compounds toward what actually matters. You cannot build the future of finance on shaky infrastructure. OUR TEAMS Production Engineering is organized into teams — but we think about teams differently. Teams are mutable. We build them around what needs to be done, not around what we need to do given the teams we already have. The structure below reflects our current priorities; it will evolve as Ramp does. Right now, we operate across four areas: - Compute — the foundation everything runs on: container orchestration, networking, load balancing, edge infrastructure, and the deployment systems that get code from engineers' laptops to production reliably and at scale - Storage — databases, caching, object storage, and the data infrastructure that underpins everything - Workflows & Messaging — the systems that power Ramp's financial workflows and event-driven architecture - Developer Infrastructure — the platform that makes every builder at Ramp faster and more autonomous: observability, cost attribution, and CI/CD systems that give teams visibility into what they build and what it costs WHAT YOU'LL DO Production Engineers at Ramp are full software engineers who happen to specialize in infrastructure. You write production code, you own systems end-to-end, and you drive technical outcomes across the organization — not just within your team. As a Tech Lead & Manager, you are a hands-on player-coach: you will lead and grow a team while remaining directly engaged in the technical work. Management at Ramp does not mean stepping away from the technology or the code. You will help set direction, develop engineers, and work alongside the team to deliver consequential infrastructure outcomes. Day to day, you will: - Build, coach, and grow a high-performing team. Create clarity, give direct feedback, mentor engineers, and help each person expand their technical judgment, ownership, and leadership. - Set technical direction for your team’s domain. Identify the highest-leverage problems, define a path forward, bring the right people along, and stay engaged with the team until the work is delivered. - Build and operate critical infrastructure across Ramp's compute, storage, messaging, and observability stack — owning the systems that handle real financial transactions at scale. - Drive architectural change — not just flag problems. When you surface a reliability or scalability issue, you own the path forward: you propose the solution, find the owners across engineering, and stay in until it's resolved. - Partner with product teams at the design phase — reviewing architectures, embedding golden paths, and making it easy to build correctly the first time. - Build Ramp's next level of scale — you'll be a hands-on contributor to the most consequential infrastructure shift happening right now: our move to a cellular architecture, enabling Ramp to scale, reach international markets, operate in highly regulated and constrained environments (e.g. FedRAMP), and deliver on enterprise-grade SLAs. - Enable AI-native engineering — as Ramp builds increasingly AI-powered products, PE is the team that makes sure the platform can support them. You'll proactively partner with product teams on AI infrastructure patterns, define the golden paths that turn one-off solutions into reusable foundations, and stay ahead of emerging challenges before they become blockers. - Build developer tooling and self-service infrastructure — so that other teams can answer their own questions (cost, performance, reliability) without involving PE. - Participate in on-call rotation — and more importantly, use every incident as a signal to eliminate the root cause, not just resolve the symptom. - Lead across the company — PE doesn't just review designs or show up when called. We proactively initiate cross-team architectural reviews, and we take full ownership of company-wide reliability and scalability initiatives: identifying the problem, proposing the solution, aligning the stakeholders, and staying in until it's done. WHAT WE LOOK FOR We don't hire for a checklist. We hire for the instincts that make someone exceptional on this team. The mindset we're looking for: - You love building teams, mentoring engineers, and helping people grow—and you are equally energized by writing code, reviewing designs, and digging into complex distributed systems. - You are a true player-coach. You know when to coach, delegate, and create space for others to lead; you also know when your direct technical involvement will create the most leverage. - You can set a technical direction, bring people along, and then lock in with the team to make it happen. - You do not believe managing engineers means stepping away from the technology or the code. - You can't walk past something broken without wanting to fix it — and you don't stop at the workaround. You find the root cause and eliminate the class of problem. - You think in systems, not tasks. You understand that "fixing the bug" is step one; making it so the bug can't happen again is the job. - You move with urgency but without chaos. You know when to go fast and when to slow down and do it right. - You treat product teams as your users. You build for them, communicate with them proactively, and measure success by how much faster they can ship. But you're also an owner — when something is broken or blocking, you don't wait to be asked. We win when our customers win. - You leave things better than you found them. Every system you touch, every process you encounter — you move it forward. Not always dramatically, but always directionally. You picked it up in a certain state; you leave it in a better one. - You are equally comfortable reading a database query plan, reviewing a system design doc, writing a Terraform module, and jumping into an incident at 2am. Experience profile: - 8+ years of software engineering experience, including a track record of shipping high-quality architectures for critical systems. - Staff+-level technical leadership: experience setting technical direction and leading complex, multi-quarter technical initiatives from ambiguous problems through durable production outcomes. - Experience managing, mentoring, and developing engineers. You create clarity, give direct feedback, and help people grow in technical judgment, scope, and leadership. - A sustained hands-on engineering track record. You are comfortable writing and reviewing production code, evaluating system designs, debugging incidents, and making difficult technical tradeoffs. - Hands-on experience building and operating distributed systems at production scale. - Strong software engineering fundamentals — you write clean, well-tested, production-ready code and set that standard for the team. - Experience with at least one major cloud provider (AWS preferred). - Familiarity with observability and reliability practices, including SLOs, error budgets, alerting, dashboards, and incident response. - Track record of delivering through cross-functional coordination: aligning stakeholders, unblocking teams, and staying accountable for the outcome. - Comfortable using AI tooling and coding agents as part of your everyday engineering workflow — and helping a team use them to move faster and think bigger. Bonus (not required): - Experience with cellular or multi-tenant architecture patterns - Prior work on workflow orchestration systems (Temporal) - Contributions to developer experience or internal platform tooling - Experience in fintech, payments, or regulated industries (FedRAMP, SOC 2) BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Задачи: — взять на себя ключевую часть сетевой и VPN-инфраструктуры проекта. Требования: — Senior-уровень в сетях: TCP/IP, UDP, DNS, TLS/HTTPS, маршрутизация, NAT; — серьёзный практический опыт с VPN, туннелированием и Xray; — опыт работы именно с крупными VPN-проектами; — глубокое понимание DPI, фильтрации трафика, блокировок и причин деградации соединений; — сильный Linux и сетевая диагностика; — опыт с dedicated-серверами, VPS/VDS, CDN, дата-центрами и хостинг-провайдерами; — плюсом будет практический опыт колокации собственного оборудования; — умение проектировать отказоустойчивую инфраструктуру, способную переживать сбои и изменения сетевых ограничений без постоянного ручного вмешательства; — способность быстро исследовать изменения в сетях, ставить эксперименты, находить причины проблем и внедрять решения; — постоянная погружённость в VPN-индустрию и понимание того, что в ней происходит прямо сейчас; — опыт работы в крупном VPN-сервисе и знание индустрии изнутри; — хорошее ориентирование в рынке хостингов и дата-центров, понимание особенностей разных провайдеров и умение строить масштабируемую и отказоустойчивую инфраструктуру для сотен тысяч пользователей. Условия: — зарплата 350 000–1 000 000 ₽ на руки, итоговая сумма зависит от уровня, опыта и компетенций; — полностью удалённая работа, full-time; — только основная работа — без параллельной работы и учёбы. Для отклика нужно написать кратко о своём опыте: в каких VPN-проектах работали, их масштаб, ваша зона ответственности, стек и наиболее сложные задачи, которые приходилось решать.