Вакансии

Задачи: — создавать e2e- и API-тесты в Playwright или похожем инструменте — запускать тесты в CI — устранять нестабильные тесты — разрабатывать тест-планы для рискованных изменений — составлять баг-репорты с шагами воспроизведения — помогать разработчикам в разборе дефектов — фиксировать ошибки с помощью записей экрана Требования: — от 3 лет опыта автоматизации тестирования веб-приложений — уверенное программирование на TypeScript или Python — опыт работы с CI-системами, например GitHub Actions — внимательность и умение понятно описывать ошибки Отбор включает короткую заявку, письменный этап из трёх вопросов, видеособеседование с руководителем разработки и небольшое задание с тестами для учебного приложения. Работа удалённая, только в пределах США.

Задачи: — Использовать AI-инструменты для анализа требований, подготовки тестовых сценариев и ускорения создания автотестов. — Работать в тесном взаимодействии с разработчиками, QA... Требования: — От 5 лет коммерческого опыта в QA Automation. — Уверенный опыт разработки и поддержки автотестов. — Практический опыт работы с TypeScript.

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

Responsibilities: — Build and evolve developer-facing APIs, SDKs, documentation, and agent tools. Requirements: — Experience with developer platforms and SDKs. — Proficiency in Python and TypeScript. — Knowledge of REST APIs, versioning, rate limiting, and CLI tools. Benefits: — Remote work opportunity. — Competitive salary range from $215,000 to $285,000. The role involves working on developer products to enhance APIs and tools for developers, focusing on backend technologies and developer experience.

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

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

Задачи: — Отвечать за надёжность, производительность и масштабирование production PostgreSQL-кластеров в 24/7 среде. Требования: — 5+ лет hands-on опыта с PostgreSQL в production. — Глубокое понимание PostgreSQL: WAL, VACUUM/autovacuum, locking, memory management. — Performance tuning: execution plans, индексы, оптимизация запросов, partitioning. — HA/DR: replication, failover, backup/recovery, Patroni или аналоги. — Linux + Python для автоматизации. — Опыт работы с high-load / highly available 24/7 системами. — Английский Upper-Intermediate+. Условия: — Работа в международной технологической компании. — Mission-critical продукт и high-load production. — Влияние на архитектуру и развитие database-инфраструктуры. — Много reliability engineering, performance tuning и автоматизации - не только классический DBA. — Международная сильная инженерная команда. — Формат работы: гибридный в Минске.

Location: Москва Отдел занимается разработкой AI-агентов для автоматизации бизнес-процессов. В фокусе — задачи NLP и CV: работа с текстовыми и визуальными документами, извлечение информации, принятие решений на основе содержимого. Требуется усилить отдел ML-экспертизой в области языковых моделей, промпт-инжиниринга и качества агентных решений. На этой позиции нужен Data Scientist, который отвечает за смысл и качество решений агента и обработки документов. Это возможность участвовать в создании агента enterprise-уровня с высокими требованиями к качеству и стабильности. Обязанности * развивать промпты агентов: системные и ролевые промпты, few-shot, схемы рассуждения, tool calling, извлечение структурированных знаний из документов * строить пайплайны эволюции промптов: версионирование, оффлайн-оценка (golden set, side-by-side, LLM-as-judge), итерации по ошибкам * решать задачи классификации и маршрутизации документов: разделение входного пакета по классам, подготовка релевантного контекста для агента * работать с RAG и эмбеддингами: chunking, выбор и тюнинг эмбеддингов, retrieval / rerank, оценка качества поиска * работать с open-source LLM и GigaChat во внутреннем контуре; предлагать и обосновывать стек под задачу Требования * опыт в Data Science / NLP / LLM от 3 лет * опыт prompt engineering на продакшн-задачах * понимание tool calling / function calling * понимание RAG-архитектур * опыт классификации текстов и документов * уверенный Python (эксперименты, скрипты, оценка качества) * понимание метрик качества LLM и подходов к оценке (eval-наборы, precision / recall по кейсам) **Будет преимуществом** * богатый опыт работы с эмбеддингами: выбор модели, fine-tune, contrastive learning, оценка retrieval * опыт пайплайнов эволюции промптов (DSPy, GePA и аналоги, Langfuse / PromptLayer) * опыт LangChain / LangGraph / LlamaIndex на уровне логики агента * опыт в доменах: банки, комплаенс, документооборот, юридические тексты * опыт LoRA / SFT * опыт CV / мультимодальных моделей Условия * комфортный современный офис рядом с м. Кутузовская * формат работы – офис/гибрид * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

- Тестировать мобильные приложения Android и iOS в продакшен-окружении: функциональность, интеграции и UI;

Задачи: — Тестирование фронтенда и бэкенда: новый функционал, исправления багов и технические задачи — Покрытие автотестами (Selenium и API) сразу по принципу «не покрыто — не релизим» — Участие в процессе выкатки в продакшн. Обеспечение бесперебойного развертывания обновлений и улучшений в продакшн-среде — Ручное тестирование Требования: — Опыт full-stack тестирования от 4 лет — Уверенное владение Python для автоматизации тестирования: опыт написания и поддержки UI- и API-тестов — Экспертиза в автотестировании веб-приложений с помощью Selenium WebDriver — Глубокое понимание паттернов автоматизации тестирования. — Уверенное владение Git — Опыт настройки и использования GitLab CI — Умение разворачивать и настраивать проекты в Docker — Знакомы с написанием Bash-скриптов Условия: — релокационный пакет (перелет и жилье на первый месяц) — ДМС для семьи — ревью дважды в год, обучение, спорт, питание в офисе Работа в офисе в Лимасоле, Кипр с возможностью до 42 дней удалёнки в год.

Требования: — Опыт работы DevOps-инженером от 3 лет, для senior от 5 лет. — Высшее техническое образование. — Уверенные знания Linux (Debian/Ubuntu), сетей и контейнеризации. — Опыт развёртывания и эксплуатации продуктовых Kubernetes кластеров. — Навыки работы с инструментами автоматизации: ansible, terraform, GitOps (Flux, ArgoCD). — Опыт администрирования баз данных и брокеров сообщений: Postgres, Redis, Kafka. — Опыт работы с системами мониторинга: Grafana, Tempo, Prometheus/VM, ELK Stack. — Понимание процессов и опыт работы с инструментами CI/CD (Gitlab ci). Условия: — Локация: Москва, гибридный формат или офис (метро Щукинская).

– Опыт тестирования mobile/web приложений (от 3 лет);

Location: London, United Kingdom; Dubai, United Arab Emirates Workplace: fully We are hiring for this position to be based in Dubai (UAE) or Eastern Europe. Praktika is an AI-native education company on a mission to deliver efficient, engaging language learning to billions of people worldwide. We're bridging the gap between traditional learning apps and human tutors through a fully automated tutorship experience powered by generative AI avatars. Since launching our mobile apps in 2023, we've reached over 30 million learners and grown to over 2 million monthly active users, become one of the world's top-4 learning apps, and recently closed a $30M Series A to accelerate our roadmap. We're a fully distributed team of ~50 people across 4 continents and 15+ countries, working asynchronously to ship fast and operate at a high bar. We're hiring a Lead DevOps Engineer to own all of Praktika's infrastructure and all access to it. This is a hands-on role with real leadership: you'll set the direction for our infrastructure, build it, run it, and keep it secure, reliable, cost-efficient and fast as we grow. You'll work with every engineering team and with non-engineering teams too. We are rebuilding how the company works around AI, and infrastructure is where that has to be made safe. What you'll do Own the infrastructure end to end: design, build and run our AWS-based infrastructure, and be the owner when it fails. Own identity and access for the whole company: cloud accounts, vendors, internal tools, onboarding and offboarding. Own infrastructure security (IAM, networks, secrets, audit logs) and the technical part of compliance: ISO 27001, SOC 2, GDPR. Keep costs visible and under control across clouds and AI vendors. Run the hosting and inference infrastructure for our ML and LLM models. Close repeated operational requests with automation and self-service, not with tickets and manual console changes. Rebuild infrastructure processes around AI: code review, monitoring and observability, alert triage, incident investigation. Build the place where internal tools and apps, built with AI by engineers and non-engineers, are deployed safely, reviewed and monitored. Build your own tools with AI too. Give delivery teams golden paths (service templates, CI/CD, safe deploys, alerts) that make the standard way the easy way, without blocking teams. What we're looking for We're looking for outstanding engineers who thrive in a challenging environment, bring a growth mindset, and operate with a high degree of agency, devotion, and autonomy. Required Ownership mindset: you make decisions and finish work without supervision. Deep hands-on AWS experience in production, including containers on ECS. Infrastructure as code (Terraform) as your normal way of working. A solid security foundation and a real interest in security. You have already built working tools with AI coding agents, and you use AI in your daily work. You have changed how other teams work without formal authority over them. You have set a technical direction and split large projects into deliverable parts. Ability to thrive in an async, distributed, written-first culture. Bonus DevSecOps experience and an understanding of how attacks work. Hands-on work on SOC 2, ISO 27001 or GDPR. Experience with clouds other than AWS. Experience with infrastructure for ML / LLM inference. Prior experience at an early-stage or high-growth consumer product company. Our stack AWS (containers, serverless, managed databases, CDN), Terraform, GitHub Actions, Datadog, SQL and NoSQL databases, event streaming, a data warehouse, hosted ML / LLM inference, and others. How we work Mission-driven: we're building the #1 language learning app and competing to win. AI-native: AI isn't a feature; it's how we think, build, and scale. Extreme ownership: every project has a clear owner who drives it to success. Less meetings, more outputs: async first; meetings are a last resort. Speed & excellence: move fast without compromising quality. Truly all-in: impactful work, full commitment, real rewards. Data-driven: decisions are based on evidence, not opinion. User-obsessed: if it doesn't improve the learner experience, it doesn't matter. What we offer Room to grow: as you prove yourself, your scope can grow to Head of Platform (backend team). Equity that grows with your impact (stock options). 26 days of holiday plus bank holidays (34 days per year total). Annual company off-site (last year: Dubai). Health and wellness benefits via SafetyWing. Full AI toolkit access: Claude, Cursor, Codex, and other productivity tools. $1,000 annual education and learning budget. Fully remote, based in Dubai or Eastern Europe. Interview Process: Intro interview with our Head of Talent. Technical interviews with our CTO. Culture interview with a member of the leadership team. Peer interview with an engineer from the team. No take-home task. We will provide you with feedback throughout the interview process.

Location: Remote Web3 Core Engineer Remote About Brave Brave is on a mission to protect the human right to privacy online. We’ve built a free web browser that blocks creepy ads and trackers by default, a private search engine with a truly independent index, a browser-native crypto wallet, and a private ad network (opt-in!) that directly rewards you for your attention. And we’re just getting started. Already 125 million people have switched to Brave for a faster, more private web. Millions more switch every month. The internet is a sea of ads, hackers, and echo chambers. Big Tech makes huge profits off our data, and tells us what’s true and what’s not. Brave is fighting back. Join us! Summary Brave is looking for an experienced Senior Software Engineer with a focus on blockchain integrations with Brave.  You'll work on our Brave Wallet.  This is a high profile and impactful, hands-on position.  Work together with our product designers, developers and privacy/security experts to help us take our wallet to the next level. Your responsibilities: Work closely with the backend team to understand intricacies and help iterate on components used to build our wallet libraries. Integrate new features in brave-core that help our front-end team connect prototypes to live data. Be up-to-date with upcoming protocol upgrades, BIPs, EIPs, etc. Be involved in investigating bugs around blockchain edge cases. Requirements 5+ years experience with application development. Strong C++ development skills required. Some JavaScript / TypeScript development skills are a plus. History of open source contributions. Good understanding of blockchain protocols (Bitcoin, Ethereum, Solana, etc.) and the DeFi ecosystem are a plus. Familiarity with cryptocurrency wallet stack (mechanics, UX, etc.). Experience with software development via distributed development teams. Comfortable working in an open source setting. A passion for helping protect users' privacy and security. Written and verbal communication skills in English. Proven record of getting things done. Working at Brave Industry-leader in privacy, with a research and engineering team that’s innovating everyday to keep people safer online and beat Big Tech Highly competitive salaries & benefits, and generous home-office stipends Fully remote team (no office, no commute) Welcoming, humble, ridiculously smart teammates, and a truly flat org structure Opportunity to get in early at a hyper-growth company, and revolutionize the web Oh, and did we mention Brendan, our CEO & co-founder, invented JavaScript?

Bullish is looking for a Senior Software Engineer to lead end-to-end delivery of full-stack web, mobile, and service-layer features.

Location: Remote Workplace: Remote About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Dragonfly, Bessemer Venture Partners, Galaxy Ventures, FirstMark, Lightspeed, Norwest, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the team & role Security at Rain protects a platform where real money moves every second, across cloud infrastructure, identity, endpoints, partner integrations and smart contracts. The team is small, senior and cross-functional, and it builds most of what it runs. Our engineers use AI agents for alert triage, investigation and response, and they design, tune and supervise those agents. Together we build Rain’s central systems for detection, response, sensors and threat intelligence, working directly with engineering, compliance and leadership. You will secure the systems Rain builds next. The role spans the whole program: you will build security tooling and controls, harden our infrastructure and access, and take on the hardest problems as Rain expands into new products and chains. What you’ll do - Build central security systems and automation the whole company relies on - Secure cloud infrastructure, identity and access across Rain’s growing footprint - Assess new products, partners and vendors before launch, and guide the engineers building them - Build AI agents and tools that make security work faster and more accurate - Lead external security assessments and drive findings to verified fixes - Join the on-call rotation and support incident response WHAT WE’RE LOOKING FOR - 5+ years in security engineering, including building tools and controls that run in production - Strong coding skills in TypeScript, Go, Rust or Python - Experience securing cloud infrastructure, identity and access - Ability to find vulnerabilities, prove them, and drive the fix with the team that owns the code - Experience at a fintech, payments or crypto company Nice to have - Blockchain security: smart contract review, onchain monitoring, custody and multisig controls - AI security: securing LLM applications and agents, or building AI into security workflows - Experience running external audits or a bug bounty program Things that enable a fulfilling, healthy and happy experience at Rain: Unlimited time off 🌴Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace, if you feel comfortable at home please work from home. If you’d like to work with others in an office feel free to come in. We want everyone to be able to work in the environment in which they are their most confident and productive selves. New Rainmakers will have a stipend to create a comfortable atmosphere at home. Easy to access benefits 🧠For US Rainmakers, we offer comprehensive health, dental and vision plans for you and your dependents, as well as a 100% company subsidized life insurance plan. Retirement goals💡Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 We offer every Rainmakers an equity option plan so we can all can benefit from our success. Rain Cards 🌧️ We want Rainmakers to be knowledgeable about our core products and services. To support this mission, we issue a card for our team to utilize the card for testing. Health and Wellness 📚 High performance begins from within. Rainmakers are welcome to use their card for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! Team summits ✨ Summits play an important role at Rain! Time spent together helps us get to know each other, strengthen our relationships, and build a common destiny. Expect team and company offsites both domestically and internationally.

Responsibilities: — Work as a DevOps Engineer for Riorise, a mobile MMO RPG. — Focus on managing containerized infrastructure and orchestration. — Implement monitoring solutions and CI/CD automation.

Location: Espoo Workplace: Hybrid ROLE HIGHLIGHTS - Senior Software Engineer, Flood Risk - Location: Espoo, Finland (relocation supported) - Team: Flood Risk, Flood Solutions - Reports to: Flood Risk Team Lead - Workplace model: Hybrid (minimum 3 days per week in the office) - Employment is subject to applicable security screening (incl. SUPO, where required) WHY THIS ROLE MATTERS We are looking for a Senior Software Engineer to turn ICEYE's flood observation history into data products that help customers understand flood risk at their locations and areas of interest. ICEYE has observed floods worldwide with its synthetic aperture radar (SAR) satellite constellation for years, so we know where water has gone, how deep it got, and how often it returns. We are turning our analysis catalog into predictive insights and building a product that gives customers near real-time understanding of flood risk for a location of interest. You will join a senior team where the data scientists and machine learning engineers build the flood models, and you make them work in production, 24/7. YOUR DAY-TO-DAY RESPONSIBILITIES You will own how flood risk gets from our models and data into customers' hands. In practice, that means: - Design and build the services and pipelines that compute, store, and serve flood risk for any location or area of interest. - Take models from notebooks to production with the data scientist and the ML engineer: tested, versioned code; reproducible inference; staged rollouts; and drift monitoring. A big part of the job is deciding what gets pre-computed and what runs at request time. - Design API-first. The contract is agreed before the code; the OpenAPI specification is the source of truth, and the documentation (reference, examples, changelog) lives in the repository as code, reviewed and validated in CI like everything else. - Build security and privacy in as a day 0 item: authentication, authorization, tenant isolation, least privilege, data minimization, and audit trails, so we can reproduce and explain every response we have served. You take part in threat modeling. - Run what you build, with automated tests and deployments, SLOs, dashboards and alerts, and automating away toil. This role includes an on-call rotation. - Design for data at scale (years of observations, customer portfolios of any size): data models, storage formats, partitioning and the batch versus streaming trade-offs, watching cost per request as closely as latency. - Make architecture decisions with our Staff Engineers (they work across the teams) and write them down as lightweight ADRs. - Mentor teammates and help the data and ML colleagues with production engineering practices (they will teach you flood science in return). WHAT WE ARE LOOKING FOR Must have - 5+ years building and running production software in the cloud (AWS, Kubernetes, Docker), owning design and delivery at senior level. - You have operationalized machine learning models: taken research or notebook code into a production service or batch pipeline, and kept it versioned, reproducible, and monitored after launch. - You have architected and built API-first products for external customers, and evolved them without breaking callers (versioning, error contracts, backward compatibility). - API documentation as code is normal for you: OpenAPI with real examples, generated references, docs checked in CI. - You design with security and privacy as the default, backed by practical experience in OAuth 2.0 and OIDC, authorization models, the OWASP API Security Top 10, and protecting customer data. - You have operated software 24/7; high automation, test automation, and observability (metrics, logs, tracing, SLOs, alerting) are what you live and breathe, and you have learned from real incidents. - Experience designing data-intensive applications: data modeling, storage formats, partitioning, and performance and cost at scale. - Deep proficiency in Python for production services and data processing, and you are comfortable reading (and refactoring) a data scientist's notebook. - Good communication; you can explain a technical trade-off to an engineer, a data scientist, a product person, or a customer, and you are comfortable shaping a product while it is still being defined. - Hands-on use of AI coding assistants and agents in your daily work, with judgment on where they help and where they do not. Nice to have - Go for the services where raw performance matters. - MLOps and model serving tooling (MLflow, ONNX, SageMaker, feature stores and the like). - Geospatial data at scale: rasters, xarray, rasterio, GDAL, PostGIS, Cloud Optimized GeoTIFF, Zarr. - Insurance, catastrophe modeling, or flood risk; knowing what an insurer does with a risk score at quote time helps a lot. - ISO 27001, SOC 2, DORA, or GDPR in a regulated data environment, including customer security reviews. - Terraform. APPLICATION PROCESS 1. Talent Acquisition Partner screening 2. Director interview 3. Live Coding and Whiteboarding 4. SVP interview   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.   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.