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Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we're interested in candidates based in the US or Canada. Residents of Quebec are not eligible for this role. Senior Full-Stack Software Engineer, Grafana Data Source Plugins The Opportunity: As a Senior Full-Stack Engineer in the Grafana Data Source Plugins squad, you will take a leading role in developing and enhancing a diverse portfolio of data source plugins that retrieve the data powering Grafana dashboards used by teams worldwide. Our team focuses on continuously improving data source plugins, ensuring seamless experience for human and agent users alike. A key aspect of this role is guaranteeing the smooth operation and reliability of our plugins in the Grafana Cloud, helping us deliver on our commitment to world-class observability tools. What You’ll Be Doing: Some data source plugins we own: Prometheus, Loki, Infinity, MySQL, PostgreSQL, AWS Cloudwatch, and Clickhouse.  The full catalog is listed here . A typical “day in the life” could include: Building or improving Grafana plugins to integrate third party services or databases into Grafana Supporting the operations and reliability of our plugins in Grafana Cloud Coming up with suggestions for process improvements Integrating data sources with agentic workflows such as Grafana Assistant Providing technical support in customer escalations Working closely with the rest of the Grafana Division What Makes You a Great Fit: You know how to transform ideas into working code, you are able to design a solution, get feedback and deliver large projects. You are a self-driven individual who understands the power of feedback loops in making roadmap decisions and driving our product forward. You are a motivated self starter with a bias towards action, and willing to take on any challenge You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You are an excellent communicator and you enjoy collaboration You are comfortable working in a remote-first company Requirements: Solid experience with Golang & Typescript Experience with Kubernetes & microservices Experience writing clean, robust, and performant software that is easily maintained by others Experience participating in an on-call rotation and performing operations/SRE tasks Bonus Points For: You have been a user of Grafana and Grafana Data Sources You have expertise in one of the underlying databases we support You have strong experience working with a Product Manager or external stakeholders In the United States, the Base compensation range for this role is USD $ 167,143 - $200,572 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . #LI-Remote #LI-Remote *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Задачи: — Проектировать и разрабатывать сервисные модули (расписание, учетные блоки, маршрутизация, отчетность) — Разрабатывать сквозные обмены данными и интеграции, обеспечивать связность данных без дублирования — Выстраивать процесс разработки и тестирования с использованием AI-агентов — Настраивать обработку ошибок, механизмы повторных запросов и логирование — Проводить сквозную проверку сценариев и сопровождать релизы от постановки задачи до вывода в Production Требования: — Опыт разработки: уверенный уровень Middle, прочная инженерная база — Стек: глубокое владение одним из языков — PHP / Python / JavaScript — Архитектура и инфраструктура: понимание stateful-приложений, асинхронности, многопоточности, работы с базами данных — DevOps / CI: базовое понимание Docker, Kubernetes, CI/CD, балансировки нагрузки — AI-инструменты: практический опыт разработки с AI-агентами — Софт-скиллы: системность, ответственность, ориентированность на конечный рабочий результат Условия: — Полная занятость — Формат работы: гибрид (Караганда)

Требования: — Опыт коммерческой разработки на Java от 4 лет. — Java 11+, Spring Boot, Spring Cloud, Spring Data JPA, Hibernate. — SQL (PostgreSQL/Oracle), оптимизация запросов. — Многопоточность, REST API, JWT, Swagger/OpenAPI. — JUnit 5, Mockito, Git, CI/CD. — SOLID, Clean Code, паттерны проектирования. — Узбекский язык - обязательно, английский - желательно. — Умение проверять банковские продукты и воспроизводить реальные сценарии. — Будет преимуществом: Docker, Kubernetes. — Prometheus, Grafana. — Опыт с высоконагруженными интеграционными сервисами. — Понимание распределенных систем и TDD. — Настройка CI/CD (Jenkins, GitLab CI, CircleCI). Локация: Только для кандидатов с гражданством Узбекистана.

Задачи: — Работа с ядром платформы на Python: сессии, ходы агента, политики заказчика, учёт; агентный цикл под бюджет хода. — Перевод пользователей с пилотной архитектуры на целевую без остановки работы. — Снижение стоимости хода: состав входа, кэш префикса, лимиты инструментов, роутинг моделей, учёт по пользователю и ходу. — Оценка качества: эталон из реальных трасс, сравнение российских моделей, регресс на каждый промпт, инструмент, модель. — Работа с данными компании через MCP с правами пользователя: 1С, КХД, СЭД, HR, поиск по документам с ACL. — Надёжные фоновые процедуры и запись во внешние системы: расписания, подтверждение человеком, ровно одна запись. — Песочница для кода агента: на сессию, без секретов и исходящих соединений. — Команда: декомпозиция, ревью, работа с ИИ-агентами для кода, найм. — Согласование требований и ИБ с заказчиком. Требования: — Опыт backend-разработки от 7 лет, из них от 2 лет — техлид/ведущий инженер с ответственностью за продакшн. — Опыт работы с Python в продакшене: asyncio, FastAPI, Pydantic, типизация, тесты. — Умение читать и править код на Go. — Опыт работы с LLM-агентами в продакшене с реальными пользователями: tool calling, цикл агента, ограничения, обработка ошибок. — Понимание контекста и стоимости: вход вызова, кэш префикса, сжатие истории, лимиты инструментов, расчёт цены хода по usage. — Опыт с Eval: эталонные наборы, LLM-судья и его проверка, регресс, трассировка (Langfuse, OpenTelemetry). — Знание гибридного поиска, реранкинга, чанкинга, прав доступа к документам. — Опыт работы с MCP, OAuth 2.0/OIDC, token exchange — агент от имени пользователя. — Знание Durable execution (Temporal, Restate или аналог), идемпотентность, повторы. — Опыт работы с PostgreSQL, Redis, S3, Docker, Kubernetes, GitLab CI. — Опыт работы с открытыми моделями через OpenAI-совместимые API, LiteLLM или аналог. — Высшее техническое образование. Условия: — Полная занятость. — График работы 5/2. — Формат работы: удалённо или гибрид.

Задачи: — Встраивать и сопровождать процессы SSDLC / DevSecOps в CI/CD — Настраивать и развивать инструменты SAST, DAST, SCA, Secret Detection, снижать количество ложных срабатываний — Проводить триаж уязвимостей: оценивать риски, приоритизировать задачи, рекомендовать способы исправления и проверять фиксы — Участвовать в ревью кода и архитектуры с точки зрения безопасности, проводить threat modeling — Консультировать разработчиков по вопросам безопасной разработки — Проводить аудит процессов и практик безопасной разработки Требования: — Самостоятельный, убедительный, амбициозный, с лидерскими качествами (или умением сделать так, чтобы управлять не приходилось:), стремящийся к построению защищенной инфраструктуры — Опыт от 1 года опыта в AppSec / ИБ разработке — Понимание OWASP Top 10, основных классов уязвимостей, способов их эксплуатации и защиты — Практический опыт работы с инструментами SAST / DAST / SCA, например Semgrep, Burp Suite, ZAP, Trivy, Dependency-Check — Навыки автоматизации на Python или Bash — Уверенная работа с Git / GitLab — Умение понятно оформлять результаты работы и находить общий язык с разработчиками — Умение читать и писать код хотя бы на одном из языков: Python, Go, PHP, C# Будет плюсом: — Опыт коммерческой разработки — Работа с Docker / Kubernetes в контексте безопасности — Опыт с SonarQube, Jenkins, Ansible, Nexus — Знание Cloud Security и IaC-сканирования — Опыт работы с Terraform, Checkov, tfsec, OPA/Kyverno

Требования: — Практический опыт самостоятельного создания тест‑кейсов/сценариев не менее 3 лет: написание тест‑документации (Test Cases, Test Suites, Test Plans) в соответствии с требованиями, поддержка их в системах управления тестами (TestRail, Zephyr, Xray); — Применение методов тест‑дизайна (эквивалентные классы, граничные значения, парные комбинации, state‑transition, decision‑table) в реальных проектах с доказательством эффективности через покрытие требований и количество найденных дефектов; — Практический опыт ручного тестирования REST‑API (HTTP‑методы, статус‑коды, заголовки, payload) минимум 2 года: построение запросов (Postman, Insomnia, curl), проверка схем (JSON‑Schema, OpenAPI), валидация бизнес‑логики; — Опыт автоматизации тестов backend на Python с использованием pytest (фикстуры, параметризация, плагин‑интеграция) и UI‑тестов на Playwright (selectors, page‑object‑model, CI‑интеграция); — Практический опыт тестирования систем с Apache Kafka: написание продюсеров/консьюмеров, проверка порядка сообщений, гарантии доставки (at‑least‑once, exactly‑once), работа с темами, партициями и схемами (Schema Registry); — Участие в интеграционном, системном и приёмочно‑сдаточном (UAT) тестировании: построение end‑to‑end сценариев, подготовка тест‑окружений, согласование критериев приёмки с заказчиком; — Практический опыт тестирования баз данных: написание SQL‑запросов для проверки данных, проверка целостности (FK, constraints), проверка миграций, работа с PostgreSQL, MySQL, Oracle, NoSQL (MongoDB, Redis) в тестовых стендах; — Опыт работы с контейнерами и CI/CD: создание Docker‑образов для тестовых окружений, написание пайплайнов в GitLab CI (stages, artifacts, caching), развертывание и управление тестовыми кластерами Kubernetes (kubectl, Helm) для выполнения автотестов; — Практический опыт работы в Linux‑окружении: написание скриптов (bash, sh), работа с пакетными менеджерами, настройка сетевых параметров, мониторинг процессов, отладка тестовых стендов. Задачи: — Проводить ручное тестирование (функциональное, интеграционное, системное); — Разрабатывать и поддерживать в актуальном состоянии тестовую документацию; — Работать с дефектами (обнаружение, анализ, контроль исправления); — Выполнять review артефактов тестирования; — Выполнять анализ и воспроизведение пользовательских дефектов; — Совершенствовать и оптимизировать процессы тестирования; — Автоматизировать функциональное тестирование на Python.

Location: All Cities Workplace: Remote Mobile Wave Solutions is a professional services company specializing in software development as a service. We are committed to delivering scalable, high-quality software solutions that meet our clients' evolving needs. With a growing team of over 120 engineers and a mission to empower businesses globally, we provide expert teams to deliver robust solutions and drive innovation. ROLE OVERVIEW We're looking for a Site Reliability Engineer to own the health, performance, and delivery of the infrastructure of one of our client. You'll sit at the intersection of engineering, operations, and quality measuring how their systems actually behave, automating away manual work, and making their path from commit to production fast and dependable. This is a hands-on role for a seasoned engineer who treats operations as an engineering problem and sets the bar for others. You'll define what "reliable" means for the systems in concrete, measurable terms, establish the practices the team operates by, and use modern tooling, including AI/AIOps, to monitor, alert, and respond intelligently rather than reactively. As a senior member of the team, you'll also mentor other engineers and help shape our reliability strategy. KEY RESPONSIBILITIES - Own the infrastructure. Build, maintain, and scale the systems our product runs on, with reliability and cost-efficiency as first-class concerns - Measure the non-functional. Define and track SLIs, SLOs, and error budgets for availability, latency, throughput, and scalability. Make system behavior visible and quantifiable to the whole team - Automate relentlessly. Identify and eliminate toil. Replace manual operational work with code, infrastructure-as-code, and self-healing systems - Build a seamless delivery process. Design, maintain, and improve CI/CD pipelines so engineers can ship safely and frequently with fast feedback - Collaborate across functions. Partner closely with software engineers and QA to embed reliability and quality early - through testing strategy, deployment practices, and shared ownership of production - Apply AI to operations. Use AI/AIOps to automate remediation, surface anomalies, reduce alert noise, and improve the signal quality of monitoring, reporting, and on-call - Lead incident response. Drive blameless postmortems and turn incidents into systemic improvements - Set the standard. Define reliability and operational best practices, and mentor engineers across the team to raise the bar QUALIFICATIONS - 5+ years of experience in an SRE, DevOps, or Platform Engineering role, with a track record of owning systems end to end - Strong grasp of reliability engineering fundamentals: SLIs/SLOs, error budgets, and reducing toil - Hands-on experience designing modernising and operating CI/CD pipelines - Solid infrastructure-as-code skills (Terraform / Pulumi / CloudFormation) - Experience with cloud platforms (GCP / AWS / Azure) and container orchestration (Kubernetes / Docker) - Proficiency in at least one programming/scripting language for automation (Python / Go / Bash) - Strong observability experience: metrics, logging, tracing, and alerting (NewRelic, Prometheus / Grafana / Datadog / OpenTelemetry) - Applied experience using AI/AIOps to automate, measure, report, and alert - anomaly detection, intelligent alerting, noise reduction, or automated remediation - A collaborative mindset and comfort working alongside engineers and QA toward shared reliability goals - Demonstrated technical leadership—mentoring engineers, driving cross-team initiatives, and influencing engineering practices YOU WOULD IMPRESS US IF YOU HAVE - Prior experience working with Google Cloud Run - Experience introducing AIOps tooling into an existing observability stack - Background in performance and load testing. - Familiarity with security and compliance practices (SOC 2 / ISO 27001 / GDPR) OUR BENEFITS - Remote Office – Option to work remotely or hybrid - Parking Space – Free parking available - Fun Office Space – Game zone and relaxation area - Health Insurance – Private health insurance, including dental care - Holidays – 5 extra days after your 1st and 5th year with us - Personal Development – Company-sponsored training and development - Employee Referral Programme – Competitive bonus for successful referrals - Social Events – Celebrating success together - Family Insurance – Add insurance coverage for a family member - Multisport Card – Fully covered sports pass

Задачи: — проектирование, обеспечение безопасности, автоматизация и оптимизация облачных сред Azure. Требования: — опыт работы с Azure. — знание Kubernetes. — опыт работы с Terraform. — знание Python. — опыт работы с Ansible. Условия: — удалённая работа. — ставка $70 - $80 в час.

Требования: — Опыт работы от 4 лет. — Работа с production-инфраструктурой и AI-сервисами. — Стек: Linux, Docker, Kubernetes, Terraform, Ansible, Gitlab CI/CD, Bare metal, Prometheus, Grafana, Python, Bash. — Опыт с AI/ML инфраструктурой, LLM сервисами, деплоем моделей. — Английский язык для делового общения. Условия: — Удалённый формат работы.

Задачи: — Разрабатывать и поддерживать сервисы и API на C# / .NET — Разрабатывать интерфейсы на React или Vue — в зависимости от проекта — Участвовать в проектировании архитектуры и выборе технических решений — Писать поддерживаемый, тестируемый и понятный код — Проводить code review и помогать команде расти — Работать с базами данных, очередями, кэшами, внешними API — Участвовать в CI/CD, деплое и мониторинге — Декомпозировать задачи, оценивать сроки и влиять на технические решения — Для Senior — брать техническое лидерство, менторить команду и влиять на развитие продукта Требования: — Опыт коммерческой разработки: от 3–4 лет для Middle+, от 5+ лет для Senior — Уверенный C# / .NET: .NET 6+, ASP.NET Core, Entity Framework Core — Опыт разработки REST API, понимание HTTP, JSON, аутентификации и авторизации — Уверенное владение одним из фреймворков: React или Vue — компонентный подход, хуки / composition API, state management — TypeScript — уверенное использование — Опыт работы с базами данных: PostgreSQL, MS SQL, MySQL или аналоги — Понимание SQL и умение писать запросы — Опыт с Docker, Git, Linux, CI/CD — Опыт написания тестов: xUnit/NUnit, Jest/Vitest и аналоги — Понимание принципов SOLID, паттернов проектирования и чистого кода — Технический английский — чтение документации, переписка, созвоны Будет плюсом: — Опыт коммерческой разработки и на React, и на Vue — Опыт миграции между фреймворками (Vue → React, React → Vue) — Fullstack-опыт: самостоятельная разработка от API до интерфейса — Микросервисная архитектура, gRPC, GraphQL — Kafka, RabbitMQ, Redis, NATS — Kubernetes, Helm, Terraform, Ansible — Cloud: AWS / Azure / GCP / Yandex Cloud — Опыт высоконагруженных систем — Опыт миграций, работы с легаси, монорепозиториями — Опыт в финтехе, e-commerce, SaaS, ML, DevTools — Вклад в open source — Опыт менторства, техлидства, архитектурных ревью — Английский B2+ — Опыт работы в продуктовых командах и/или стартапах

Задачи: — Проектирование и поддержка инфраструктуры проектов (Highload / Enterprise). — Настройка и оптимизация CI/CD пайплайнов. — Автоматизация развертывания и управления конфигурациями. — Обеспечение отказоустойчивости и мониторинга систем. — Работа в тесной связке с командами разработки и QA. Требования: — Опыт работы DevOps/SRE/Infrastructure Engineer от 3-х лет. — Понимание принципов CI/CD, Immutable Infrastructure, IaC. — Опыт администрирования Linux-систем. — Знание сетевых технологий (DNS, HTTP/HTTPS, TCP/IP, балансировка). — Опыт работы с контейнеризацией. — Стек технологий (в разных вариациях): Cloud: Yandex Cloud, AWS, Google Cloud или приватные облака. — Оркестрация: Kubernetes (K8s), Docker Swarm, Nomad. — CI/CD: GitLab CI, Jenkins, TeamCity, GitHub Actions, ArgoCD. — IaC: Terraform, Ansible, Pulumi. — Мониторинг: Prometheus, Grafana, Zabbix, ELK/EFK, VictoriaMetrics. — Языки: Python, Go, Bash (для автоматизации). Условия: — Работа через ИП. — Удалённая работа или гибрид по желанию. — В основном заказчики работают по времени МСК. — Разнообразие задач — от стартапов на AWS до энтерпрайза на Yandex Cloud. — Оплата обсуждается индивидуально, зависит от уровня и проекта (выплаты стабильные, без задержек).

Задачи: — Создавать высокопроизводительные edge-сервисы на Go — Проектировать архитектуру с офлайн-режимом и синхронизацией между облаком и edge — Разрабатывать системы обмена сообщениями с использованием NATS, Kafka или MQTT — Управлять развертываниями в Kubernetes с Helm — Оптимизировать сервисы для работы на edge-оборудовании — Участвовать в архитектурных и код-ревью Требования: — Опыт разработки ПО не менее 7 лет — Уверенные знания Golang — Опыт работы с распределёнными системами и event-driven архитектурой — Знания Kubernetes, Helm, Docker — Опыт работы с системами обмена сообщениями NATS, Kafka или аналогичными — Знание OAuth2 и JWT — Опыт работы с CI/CD Будет плюсом: — Опыт с MQTT — Знание Spectro Cloud Palette — Опыт работы с POS или ресторанными технологиями — Знание GraphQL federation

Location: Paris; New York; London Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud. Frontier models, developer tools, and now the compute to run them: the cloud is where Mistral's strategy comes together. Our customers in finance, healthcare, and the public sector run frontier models on our infrastructure, and the Cloud & Inference product team owns the products that make that possible: managed Kubernetes and GPU clusters, the pay-as-you-go inference APIs for our first-party models, and the fast-growing set of services around them. The portfolio runs on our own metal, in our own datacenters, backed by our own model research: the full stack under one roof. We are scaling toward a gigawatt of compute by 2030. Every layer of that build needs a product behind it: orchestration, storage, networking, serverless containers, training, and inference. The product team is small and the mandate is company-sized. As VP Product you will build the PM org this portfolio needs, set its strategy, and carry it to market with the GTM, marketing, and partnerships teams. The products you define are how Mistral's sovereign AI strategy meets its customers. THE ROLE We are hiring a VP of Product to own our cloud and inference portfolio end to end: the foundational systems that power Mistral's data centres, and the inference platform that brings the world's most advanced generative AI models to production. You will define the vision and strategy, and you will own the business results: adoption, revenue contribution, and gross margin. This is a broad mandate. You will build the product organisation and, as the business scales, bring in the stream leadership to delegate its parts. You will set the operating rhythm that lets a fast-moving org deliver with focus, and your remit grows with the portfolio: what you run hands-on in year one, you lead through others as the org grows. The portfolio runs in production today. The job ahead of you is the scale-up: a gigawatt of compute to fill, a product surface that keeps expanding, and a major new line of business to build on the foundation already in place. This is a highly visible role, with the opportunity to shape how Mistral's technology is adopted globally. WHAT YOU WILL DO - Strategy & vision. Define and evangelise the product vision, strategy, and annual goals for our Cloud and Inference products, aligned with customer needs, company objectives and market trends. - Go-to-market. Own adoption, revenue contribution, and gross margin. Partner with marketing and GTM teams on positioning, pricing and packaging, launch plans, and adoption strategy. - Team leadership. Build the product organization for these products: hire product managers and stream leads, set the operating cadence (quarterly product reviews, roadmap reviews), and develop PMs through clear growth paths. - Customer & market fit. Work directly with AI-native startups and enterprises running advanced AI workloads to drive product-market fit across the portfolio. - Delivery & execution. Partner with engineering leadership to build a world-class compute infrastructure and inference platform delivering high-performance, cost-efficient AI at scale, with reliability, SLAs, and cost-per-token economics as first-class product concerns. - Market & technology insights. Track the competitive landscape and emerging technologies across AI infrastructure and managed inference to inform product strategy and identify new opportunities. - Research & open source. Partner with research and engineering teams to turn emerging model architectures and advances in open-source inference into product opportunities that improve performance and efficiency. WHAT WE'RE LOOKING FOR - Extensive experience in tech and infrastructure, including significant time leading product organisations with a proven track record of bringing cloud infrastructure, large-scale distributed systems, or inference products to market. - You've scaled a cloud or inference product line to $1B+ in revenue: built the line, priced it, taken it to market, and owned the number. - Engineering background prior to moving into product management. - Proven people leadership: you've hired and developed senior PMs, grown the leaders under you, organised teams around clear stream ownership, and built durable operating cadences. - Fluency in the economics of the business: comfortable owning gross margin, unit economics, and the tradeoffs behind pricing and capacity. - Ability to align and inspire cross-functional teams without direct authority, and to communicate credibly with executives, engineers, and customers. - Low ego, high bias for action, comfort in ambiguity, and hands-on by instinct. We are scrappy: you write the strategy memo, then dig into the pricing model, the product spec, or the customer escalation yourself. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Задачи: — Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants. — Develop recommendation, ranking, classification, and predictive ML models. — Own end-to-end ML pipelines from data processing and training to deployment and monitoring. — Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure. — Work with Product and Engineering to measure business impact through KPIs and experiments. — Improve AI system scalability, reliability, cost, governance, and performance. Требования: — 4–5+ years in AI, ML, or Data Science. — Strong Python, SQL, and production ML experience. — Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering. — Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex. — Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform. — Experience with Kafka, ETL pipelines, vector databases, and search systems. — Ability to independently take AI projects from idea to production. Плюсом будет: — Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership. — Candidate should be able to work on US time schedule. — Good English conversation skill is much much preferred.

Location: Sydney, Australia Riot Games is looking for a Systems Engineer to join the Game Operations team supporting Wild Rift. You will help operate and improve the infrastructure, services, and tools that support reliable live-service operations for the game. This is a hands-on role focused on automation, production support, incident response, observability, data integrity, and continuous improvement. You will work with engineering, platform, data, and operations teams to reduce risk, improve efficiency, and protect player experience. Internal Job Title: Systems Engineer II. Responsibilities: Operate and improve the production infrastructure, cloud services, data platforms, and operational systems that support Wild Rift. Build automation and tooling for deployments, migrations, validation, capacity management, and routine operations. Troubleshoot distributed systems and participate in incident response, root-cause analysis, and follow-up improvements. Support releases and operational changes while maintaining service continuity and data integrity. Improve monitoring, alerting, dashboards, runbooks, and other operational documentation. Identify opportunities to improve reliability, scalability, capacity, and infrastructure cost. Collaborate with global technical partners and provide day-to-day support and guidance to operations teams. Required Qualifications: BS in Computer Science or equivalent experience, RHCE, RHCSA. 2+ years of industry experience or an advanced degree. Professional experience in systems engineering, infrastructure engineering, site reliability engineering, software engineering, or a related field. Experience supporting production services, preferably in a high-availability or live-service environment. Working knowledge of Linux, networking, cloud infrastructure, storage, compute, and distributed systems. Experience with AWS Cloud and/or Tencent Cloud. Ability to write maintainable automation or production code in Python, Go, Java, or a comparable language. Working knowledge of SQL and data-platform concepts, including data movement, replication, validation, and operational integrity. Familiarity with Git-based configuration management, infrastructure as code, or deployment automation. Experience with monitoring, alerting, incident response, and root-cause analysis. Strong communication, collaboration, and documentation skills. Professional fluency in Mandarin and English, with the ability to work across time zones and technical disciplines. Desired Qualifications: Experience with distributed data technologies, object storage, Kubernetes, Redis, OpenSearch/Elasticsearch, or similar platforms. Experience supporting high-volume online services, game telemetry, or player data. Experience with capacity planning, cloud cost optimization, or infrastructure decommissioning. Experience working in a multi-region or follow-the-sun operations environment. Interest in games and the relationship between technical systems and player experience. Our Perks: At Riot we strongly believe in work / life balance, and we encourage that with our open paid time off policy, paid parental leave (for both primary and secondary carers) and flexible work schedules to fit your lifestyle. We also believe that work should be fun, we have co-op gaming areas, a play fund so you can broaden and deepen your knowledge of players and community, and all the snacks you would ever need to power through your day (even healthy snacks!). And that’s not all we offer, there’s also: Medical Insurance that covers you and your dependents Employee Assistance Program Wellness fund Donation matching of time and money to registered charities Learning and Development opportunities Riot Games fosters a player and workplace experience that values teamwork embodied by the Summoner's Code and Community Code . Our culture embraces differences as a strength, and our values are the guiding principles for how we approach work. We are committed to putting diversity and inclusion (D&I) at the center of everything we do and promoting a fair and collaborative culture where Rioters treat one another with dignity and respect. We encourage you to read more about our value of thriving together and our ongoing work to build the most inclusive company in Gaming .

Location: Singapore Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Provide first- and second-line support for LLM gateway platform, investigating and resolving issues raised by engineering and business users across the firm Monitor and maintain the platform's underlying infrastructure to ensure availability, stability and predictable performance under rapidly growing load Support and troubleshoot model-serving backends and provider integrations, model providers, covering latency, throughput, error-rate and capacity issues Triage incidents affecting model availability — provider instability, connection resets, timeouts, regional slowness — determine whether the cause is platform-side or upstream, and drive to resolution with vendors where required Support the tooling layer built on top of LLM gateway: integrations, developer workspaces (e.g. Coder), coding assistants and API clients, including diagnosing issues introduced by upstream vendor releases running against a gateway-fronted API Coordinate with platform engineering, cloud infrastructure and end-user teams to resolve incidents and minimise disruption Support release management and change processes to keep production stable, including staged rollouts, non-prod validation and rollback Build tooling and automation to improve monitoring, diagnostics and operational visibility, and to reduce repetitive manual work Contribute to the design and implementation of monitoring, dashboards and alerting — for example extending Grafana dashboards covering TTFT, TPOT, percentile latency and failure-rate reporting Own and improve operational documentation, runbooks and user-facing status communication Your present skillset Experience in a production support, SRE or platform operations role within a fast-paced environment, with strong ownership of issue resolution end to end Strong Linux and Windows system administration skills Proficiency scripting and automating in Python, Bash and/or PowerShell Solid experience with relational databases such as PostgreSQL or SQL Server, including writing queries for investigation and supporting routine operational processes Practical understanding of monitoring and observability: metrics, logs, traces, dashboards and alerting, and the ability to analyse system data to distinguish a platform-wide problem from a localised one Comfortable debugging distributed, API-driven services: HTTP status and error semantics, timeouts, retries, connection resets, rate limiting, caching and latency percentiles Familiarity with large language model concepts and hosting environments — inference APIs, model gateways/proxies, prompt and context handling, token accounting, streaming responses, prompt caching Exposure to public cloud, ideally AWS (Bedrock, networking, IAM, logging/metrics), and to containerised or Kubernetes-based workloads Ability to communicate clearly with both engineers and non-technical users, and to manage expectations of senior stakeholders during live incidents Awareness of data-sensitivity and access-control considerations when routing workloads to third-party model providers Beneficial Experience supporting developer tooling and AI coding assistants (e.g. Claude Code, OpenCode) or IDE/workspace platforms Experience with Grafana, Prometheus or equivalent observability stacks, including building dashboards and alert rules Experience with CI/CD and infrastructure-as-code (Terraform, Ansible, or similar) Experience operating multi-region services and troubleshooting region-specific performance issues (e.g. APAC latency) Experience acting as the operational interface to third-party vendors and cloud providers during degradations QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Описание проекта: Масштабный проект цифровой трансформации, влияющий на ключевые производственные процессы. Задачи: — Проектирование архитектуры данных: разработка и описание целевой архитектуры хранилищ (OLAP/OLTP), определение моделей данных, выбор форматов хранения и стратегий партиционирования. — Разработка Data Pipelines: проектирование и реализация ETL/ELT-пайплайнов: построение DAG в Apache Airflow, написание кастомных операторов и сенсоров на Python, настройка ретраев, алертинга и зависимостей. — Стриминг и батч-обработка: разработка стриминговых джоб на Apache Flink и батч-процессинга на Apache Spark. — Оптимизация производительности: практический опыт поиска и устранения узких мест, оптимизация медленных SQL-запросов (анализ execution plans, индексы, партиционирование), тюнинг конфигурации движков обработки (Flink, Spark) и баз данных для минимизации потребления ресурсов (CPU, RAM, I/O). — Обеспечение качества данных: организация тестирования трансформаций данных, внедрение механизмов проверки целостности и актуальности данных, реализация процессов нормализации и дедупликации. — Интеграции: разработка и поддержка интеграций между системами: REST/gRPC API, базы данных, message brokers (Kafka, MQTT), файловые хранилища (S3), Timeseries DB. — Работа с Jira: ведение задач, управление статусами и связями между задачами. — Поддержка технической и бизнес-команд: обработка заявок на поддержку существующих потоков данных или разработку новых, заведение и контроль исполнения заявок внутренних команд. — Поддержка команды в систематизации и автоматизации процессов. — Взаимодействие с разработчиками и тестировщиками для уточнения технических ограничений и требований. — Обеспечение прозрачности статуса технических задач и процессов для всей команды. Требования: — Опыт работы на позиции Data Engineer от 4 лет в сфере разработки ПО. — Опыт работы с ключевыми компонентами нашего стека: DBMS & Warehouses: уверенная работа с Postgres и MSSQL; опыт настройки и оптимизации OLAP-движков (Trino, StarRocks) и современных хранилищ (Cassandra, Redis). — Data Flow Tools: практический опыт работы с Apache Airflow (написание DAG, кастомные операторы); опыт использования Apache Kafka (producer/consumer) и Apache Flink (разработка стриминговых джоб, состояние, чекпоинты). — Data Lake / Lakehouse: опыт работы с Apache Iceberg, понимание архитектуры lakehouse, использование Lakekeeper для управления метаданными, работа с объектным хранилищем S3. — CDC: опыт реализации Change Data Capture паттернов для синхронизации данных между системами. — Глубокие знания в области архитектуры данных и баз данных: понимание принципов нормализации и денормализации, проектирование relational и columnar моделей, стратегии управления данными (lifecycle, retention, versioning). — Уверенное владение Python: написание скриптов, модулей, работа с асинхронностью при необходимости; опыт написания DAG в Apache Airflow, включая кастомные операторы, hooks, sensors. — Навыки оптимизации: умение профилировать процессы, находить bottlenecks, оптимизировать SQL-запросы и настраивать ресурсы кластеров под нагрузку. — Владение Jira и Confluence на уровне confident user (структура страниц, шаблоны, макросы, связки задач и документации). — Опыт организации хранения данных для последующих задач OLAP / OLTP с учетом требований (consistency / integrity). — Опыт организации обработки данных в рамках задач OLAP / OLTP с применением различных паттернов (batch processing, CDC). — Понимание ключевых особенностей и сценариев применения различных паттернов организации интеграционных потоков (batch processing, CDC) с учетом их характеристик (3V+). — Опыт заведения и сопровождения заявок в сервис-деске. Будет плюсом: — Опыт работы с Timeseries базами данных (InfluxDB, TimescaleDB, TDengine и др.). — Глубокий опыт эксплуатации кластеров (Hadoop, YARN, Kubernetes) в production-среде. — Знание SQL на продвинутом уровне (оптимизация сложных запросов, window functions, CTE). — Опыт работы с CI/CD для data-пайплайнов. — Понимание принципов DDD, event-driven архитектуры. — Опыт работы с Apache NiFi.

Задачи: — строить и оптимизировать масштабируемые системы обучения с подкреплением, конвейеры, инфраструктуру наблюдаемости и оценки. Требования: — опыт работы с reinforcement learning, machine learning. — знание Jax, Kubernetes, Grafana, Prometheus, Slurm, PyTorch, OpenTelemetry. Условия: — работа в офисе в Сан-Франциско, Калифорния. — зарплата $425,000 - $475,000 в год.