Вакансии

Location: London, United Kingdom About the company Our mission is that “Any financial application can onboard any user, anywhere in the world, in 1 click.” Transak provides onboarding to financial applications through authentication, KYC, risk checks, and fiat on/off ramps. This is a next generation of infrastructure for the next generation of financial applications that are built on blockchain and stablecoin rails. Our API and widget-based solutions are used by top partners like MetaMask, Coinbase, Ledger, and Trust Wallet to enable seamless onboarding of over 10 million users across over 450 active applications. We have raised over $37M from top-tier investors including Consensys, Tether, and Animoca Brands About the role Transak's Fiat/Payments team builds and operates the rails that move money between traditional banking systems and crypto — ACH, SEPA, Faster Payments, wires, virtual accounts, and card rails. As an SDE 3, you will own critical, high-throughput payment microservices end-to-end: design, build, scale, and operate systems that move real money for users across multiple currencies and jurisdictions, with US,UK/EU regulatory and global banking-partner requirements as a core part of the job. This is a senior individual-contributor role calibrated against SDE 3 / Senior Engineer, driving architecture decisions, mentoring engineers, and being the go-to owner for a payments domain, while staying hands-on in code daily. Key Responsibilities Payment Systems Ownership & Architecture Own payment microservices end-to-end — design, build, deploy, and operate Node.js services (orders, payment, reconciliation, virtual accounts, payout orchestration) handling real-time financial transactions at scale. Design for correctness and failure: idempotent, retry-safe, reconciliable systems where every transaction is traceable, auditable, and recoverable (partial failures, webhook replays, duplicate detection, distributed state machines). Architect for scale and resilience across a distributed microservices architecture; make service-boundary and build-vs-buy decisions; address root causes rather than symptoms. Banking & Partner Integrations Drive integrations with banking and payment partners (e.g. banking and card providers / risk providers) — API contracts, webhook handling, sandbox-to-production rollout, and reconciliation logic across multiple rails (ACH, SEPA, Faster Payments, wires). Work with Risk, Compliance on KYC, AML, and fraud-control touchpoints in the payment flow. Infrastructure, CI/CD & Operations Build and maintain CI/CD pipelines (Jenkins) — automated testing, blue/green or canary deployments, and rollback strategies for services that cannot tolerate downtime or data loss. Operate infrastructure on AWS (ECS/EKS, Lambda, SQS/SNS, RDS, CloudWatch); contribute to infra-as-code, monitoring, alerting, and on-call runbooks for payment-critical systems. Optimize the data layer: schema design and query performance in MongoDB, caching and rate-limiting strategies with Redis, and safe migration patterns for high-volume transactional collections. Participate in on-call for payment-critical services, including incident response and postmortems. Technical Leadership & Collaboration Lead technical roadmaps — break down large, ambiguous payments initiatives into shippable milestones; write design docs/RFCs; drive consensus across Engineering, Product, Risk, and Operations. Mentor and raise the bar — review code and designs, coach mid-level engineers, and help hire and grow the team. Uphold security and compliance best practices for handling PII/financial data in a regulated, PCI-DSS-adjacent environment. What We're Looking For 6+ years of professional software engineering experience, with a significant portion building backend/distributed systems; prior experience in fintech, payments, on-and-offramp provider, or banking infrastructure strongly preferred . Strong hands-on expertise in Node.js (TypeScript preferred) for performant, production-grade backend services. Deep experience with MongoDB — schema design, aggregation pipelines, indexing strategy, and performance tuning at scale. Proficiency with Redis — caching, distributed locks, rate limiting, and pub/sub patterns. Proven experience designing and operating microservices architectures , including inter-service communication (REST/gRPC/event-driven via SQS/Kafka,ELK,New relic, Mixpanel), service discovery, and API contract design. Solid understanding of CI/CD pipelines , with hands-on experience using Jenkins (pipeline-as-code, multi-stage builds, automated test gates). Working knowledge of AWS infrastructure — ECS/EKS/Lambda, VPC networking basics, IAM, S3, RDS, CloudWatch; infra-as-code (Terraform/CloudFormation) is a plus. Strong grasp of distributed systems fundamentals: idempotency, eventual consistency, retries/backoff, circuit breaking, and failure isolation. Track record of owning a service or domain end-to-end in production, including on-call responsibility. Excellent written communication — comfortable authoring design docs/RFCs and explaining trade-offs to engineers and non-technical stakeholders (Risk, Ops, external partners). Nice-To-Haves Experience with payment rails (ACH, SEPA, Faster Payments, SWIFT/wires) or card processing. Familiarity with banking partner integrations, webhook-driven reconciliation, or ledger/double-entry accounting systems. Exposure to KYC/AML/fraud tooling. Experience at a fintech/crypto-native company, payments processor, or Big Tech payments org. Prior experience operating in a regulated environment (FCA, EMI/PI licensing context), given the UK/EU banking scope of this role.

Location: Yerevan, Armenia Workplace: hybrid About Webb Fontaine Founded in 2002, Webb Fontaine is a global trade technology company headquartered in Dubai, with projects spanning the Middle East, Africa, Asia, South America and beyond. We partner with governments worldwide, providing cutting-edge solutions to boost their revenue by streamlining trade and logistics operations across the entire trade spectrum. At Webb Fontaine, we're crafting a legacy of innovation with a mission to transform the landscape of trade through technology. This wouldn’t be possible without our team of exceptional individuals who are at the core of our success. Build the technology powering international trade. We're looking for a Mid-Level Java Software Engineer to help build a modern, scalable platform supporting mission-critical Customs operations. You'll work on real distributed systems, grow your architectural skills alongside experienced engineers, and use modern AI tools to deliver reliable, maintainable software. Our Tech Stack Java 17+, Spring Boot, Apache Kafka, PostgreSQL, Oracle, Elasticsearch, Amazon S3, Kubernetes, and AI coding assistants. Key responsibilities Build and maintain scalable, reliable backend services using Java, Spring Boot, and event-driven architectures. Apply best practices in software design, testing, code reviews, and CI/CD. Troubleshoot production issues and optimize application performance. Use AI coding assistants and agents to accelerate development, generate tests, refactor code, and debug issues. Review and validate AI-generated code for correctness, security, and maintainability. Collaborate with the team. Travel to our project offices when necessary. Qualifications 3+ years of professional Java development experience, including Spring Boot. Solid knowledge of SQL databases, Kafka, microservices, and event-driven architecture. Understanding of JVM performance, multithreading, and concurrency. Experience with automated testing, CI/CD, and containerized applications. Practical experience with AI coding assistants such as Claude Code or Codex, with the ability to critically evaluate generated code. Strong analytical and problem-solving skills. Fluency in English . Availability and willingness to travel to project offices are mandatory. Nice-to-have qualifications Experience with AWS, GCP, or Azure. Kubernetes, Elasticsearch, or observability tools (Grafana, Prometheus). Experience with Customs, trade, or government systems. Benefits Equal opportunity advocacy: We promote equality, creating a diverse and inclusive environment. Competitive compensation: Enjoy a competitive salary that rewards your contributions. Health and Wellness: We provide comprehensive medical coverage. Global collaboration: Join a world-class team with a global presence and international clients. Investment in you: We invest in your growth and development, valuing our employees as top talent. Work-life balance: We support a healthy work-life balance for your well-being. Training support: We offer a comprehensive learning and development program. We offer benefits tailored to each location, considering the specific regulations and conditions of each country. These will be discussed with candidates during the selection process.

Location: Arlington, VA, United States Job Title Cyber Virtualization Engineer Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors solutions for a diverse range of government, military, nonprofit, and public-sector clients. Locations Arlington, VA Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description SITE 525 is seeking a highly skilled Cyber Virtualization Engineer to support the development and sustainment of advanced cyber training environments. This role involves hands-on engineering of secure, scalable, and AI-enabled virtual ranges that emulate realistic, adversarial network conditions across IT and OT domains. These environments are used for cyber mission rehearsals, red/blue/gray team operations, and full-spectrum cybersecurity exercises. Must be willing to travel up to 25%. Responsible for designing, deploying, and maintaining advanced virtualized training environments that replicate realistic, large-scale, and adversarial network conditions. This position focuses on engineering and integrating dynamic, hypervisor-driven platforms and virtualization technologies to support cyber mission rehearsals, red/blue/gray team operations, and full-spectrum training exercises. Key Duties Engineer and implement scalable virtualized environments leveraging hypervisors (KVM, VMware, Hyper-V), virtual machines, containers, and software-defined networking across hybrid, edge, and cloud infrastructures. Implement and manage virtualization stacks including private cloud platforms, hypervisor clusters, and orchestration frameworks for large-scale, multi-tenant environments. Develop automation and orchestration tooling for provisioning, snapshotting, and lifecycle management of virtualized assets using Infrastructure-as-Code and CI/CD pipelines. Integrate advanced traffic simulation capabilities (burst, steady-state, geo-distributed, AI/ML-driven) to emulate realistic user and system behaviors within virtual ranges. Build and maintain frameworks and tooling for user and NPC emulation across virtualized environments to enhance operational realism, including threat emulation and defensive toolsets for network monitoring, incident detection, and response. Implement observability pipelines for performance monitoring, traffic replay, autoscaling validation, and centralized logging in production-grade virtual infrastructures. Administer and secure hypervisor platforms and virtual networking components, ensuring isolation, resiliency, and compliance for mission-critical environments. Manage network and server infrastructure including Active Directory, identity management systems, and virtualized security controls. Integrate third-party virtualization and orchestration tools to improve fidelity and scalability of training environments. Support exercise operations including setup, execution, troubleshooting, and real-time scenario management for White Cell operations. Collaborate with technical working groups and stakeholders to validate and enhance virtualization strategies for cyber training environments. Apply knowledge of OT systems (SCADA, ICS, PLCs, IoT/IIoT) within virtualized contexts for realistic emulation. Relevant Technologies & Tools: Virtualization & Hypervisors: VMware ESXi/vSphere, KVM/QEMU, Microsoft Hyper-V, Proxmox, OpenStack Virtual Infrastructure Management: VM lifecycle management, snapshotting, cloning, orchestration frameworks Cloud & Containerization: Private cloud platforms, AWS, Azure, Kubernetes (K8s), Docker, Podman, hybrid and edge deployments Networking & SDN: Virtual switches (vSwitch, vDS), software-defined networking, network segmentation, VPNs, dynamic Network-as-Code tools Automation & IaC: Infrastructure-as-Code (Terraform, Ansible, Packer, Helm, Nomad ), CI/CD integration for infrastructure Performance & Observability: Metrics collection, centralized logging, traffic replay, load simulation, autoscaling validation Security in Virtualized Environments: Identity management, Active Directory (GPOs, tiered admin scripts), secure isolation of virtual ranges Cyber Range Engineering: Virtualized cyber training environments, adversarial network simulation, AI/ML-driven traffic emulation Traffic Simulation & User Emulation: Lariat, CMU GHOSTS, MITRE Caldera, Red Canary, Atomic Red Team, TRex, BreakingPoint, Locust, k6, custom Python/TypeScript scripts, AI-enabled agents Compliance & Assurance: NIST 800-series, ISO 27001, FedRAMP, CUI-compliant controls Monitoring & Control Interfaces: Custom dashboards for exercise operations, centralized scenario orchestration Requirements Bachelor’s or Master’s degree in Cybersecurity, Computer Engineering, or related field. 5+ years of experience in cyber engineering, network operations, or cyber range development. Top Secret security clearance. Proficiency in virtualization, containerization, and cloud technologies. Experience with offensive and defensive cybersecurity tools and frameworks. Familiarity with AI/ML integration in cyber environments. Strong scripting and automation skills (e.g., Python, Bash, PowerShell). Experience with infrastructure-as-code tools (e.g., Terraform, Ansible). Knowledge of OT systems and protocols. Security certifications (e.g., CISSP, CEH, OSCP) are a plus. Compensation Competitive Hourly Pay Benefits Questions? Please reach out to lolney@idsinternational.com for additional questions or information.

Location: Annapolis Junction, MD, United States Job Title Senior‑Level Systems Engineer Why IDS? IDS believes in resolving conflict, building innovative approaches to do so. Combining operational expertise with an intimate understanding of today’s greatest challenges, we bring our customers the solutions required for success in a complex and multidimensional world. IDS tailors solutions for a diverse range of government, military, nonprofit, and public‑sector clients. Locations Annapolis Junction, MD Shifts Available Please note, candidates must be flexible. Shift times are general hours; some projects may require earlier or later reporting based on customer requirements. Job Description IDS is seeking a Senior‑Level Systems Engineer to support the definition and implementation of system architecture for an Agent Knowledge Management System utilizing an agentic framework for automated knowledge extraction. The engineer will work closely with project leadership to manage system integration, deployment strategy, compliance, testing, validation, and lifecycle sustainment. Key Duties • Collaborate with project leadership to manage system integration efforts across multiple components and teams • Develop, maintain, and execute deployment strategies and processes to ensure smooth product delivery • Coordinate technical efforts across engineering, data science, and UX teams to support integrated delivery • Ensure compliance with system standards and best practices through testing, validation, and lifecycle sustainment • Decompose project requirements into actionable technical tasks and specifications • Develop and maintain technical plans, milestones, and support code review activities • Maintain system architecture, integration, and deployment documentation • Conduct security, performance, and quality audits to ensure compliance Requirements • Bachelor’s degree with nine (9) years of relevant experience, or Master’s degree with seven (7) years, or Doctoral degree with five (5) years • Degree in Engineering, Physics, Astronomy, or a related technical field (e.g., Computer Science, Mathematics) • Experience designing and sustaining engineering systems across the full system lifecycle • Experience decomposing requirements and supporting system integration efforts • Familiarity with Agile development and CI/CD practices • Active TS/SCI with Polygraph Compensation • Salary range: $150,000 – $170,000 • Benefits

Location: Chisinau, Moldova We are seeking a Mid-Level Mobile QA Engineer to ensure the quality, reliability, and usability of iOS and Android mobile applications, including FinTech functionalities, through manual testing and an increasing focus on test automation. The role involves planning and executing functional, regression, integration, usability, compatibility, and exploratory testing across mobile devices, operating-system versions, backend services, and third-party integrations. The QA Engineer will also design, develop, and maintain automated tests that provide stable and meaningful coverage of critical user journeys. The Mobile QA Engineer will analyze business and technical requirements, identify risks and acceptance criteria, prepare test scenarios and test data, and communicate defects clearly to developers, business analysts, product owners, and other stakeholders. The role includes planning and tracking quality activities in Jira within an Agile delivery framework. Additionally, the QA Engineer is expected to contribute to release readiness, continuous quality improvement, and shift-left testing practices. The candidate demonstrates solid mobile testing experience, an automation-oriented mindset, attention to detail, and the ability to investigate issues across the mobile application, APIs, backend services, and device environment. Basic Requirements • Ability to understand mobile application architecture, user journeys, business rules, and integrations with backend services. • Capability to plan and execute manual testing independently and to develop or maintain automated tests with limited guidance. • Strong discipline in test design, defect reporting, test evidence, traceability, and quality documentation. • Ability to reproduce, isolate, and investigate defects using logs, API responses, device information, and test data. • Willingness to maintain reusable test cases, automation code, test data, and release-quality documentation. • Familiarity with Agile methodologies (Scrum/Kanban) and cross-functional teamwork. • Understanding of mobile usability, accessibility, performance, network conditions, and device/OS fragmentation. Key Responsibilities Mobile QA Testing Responsibilities • Review requirements, user stories, designs, and acceptance criteria to identify ambiguities, risks, dependencies, and test conditions early in the delivery lifecycle. • Design, maintain, and execute test plans, checklists, test cases, exploratory charters, and regression suites for iOS and Android applications. • Perform functional, integration, end-to-end, regression, smoke, sanity, usability, compatibility, and localization testing. • Validate mobile application behavior across supported devices, screen sizes, operating-system versions, orientations, permissions, and installation or upgrade paths. • Test application behavior under variable network conditions, interrupted sessions, background/foreground transitions, notifications, deep links, and offline or low-connectivity scenarios. • Validate REST APIs, backend integrations, authentication flows, and data consistency using tools such as Postman, Swagger/OpenAPI, or comparable solutions. • Design, develop, execute, and maintain reliable automated tests for critical mobile user journeys using Appium or comparable mobile automation frameworks. • Improve automation coverage, test stability, execution time, reporting, and maintainability while investigating flaky tests and failed runs. • Prepare and manage test data and test environments, including mocks or stubs where appropriate. • Log defects with clear reproduction steps, expected and actual results, severity, evidence, environment details, and relevant diagnostic information. • Perform defect verification, regression impact analysis, root-cause collaboration, and quality sign-off recommendations for releases. • Collaborate closely with mobile developers, backend engineers, business analysts, UX/UI designers, DevOps engineers, product owners, and business stakeholders. Quality, Security & Release Responsibilities • Apply risk-based testing and contribute to quality criteria, test strategy, release gates, and Definition of Done. • Validate secure authentication, authorization, session handling, permissions, sensitive-data exposure, and other relevant mobile security controls. • Integrate automated tests into CI/CD pipelines and review execution results to provide timely feedback on build quality. • Support release validation for development, test, staging, and production environments, including app-store candidate builds when required. • Monitor production quality indicators, logs, crash reports, analytics, and customer-reported issues to identify regression risks and improvement opportunities. • Track and communicate testing progress, coverage, defect trends, residual risks, and release-readiness recommendations. Required Skills & Qualifications • 3+ years of hands-on software testing experience, including practical testing of native or cross-platform iOS and Android applications. • Strong knowledge of software testing principles, test design techniques, defect lifecycle, and risk-based testing. • Demonstrated experience in manual functional, regression, integration, exploratory, and compatibility testing. • Practical experience developing or maintaining mobile UI automation using Appium or a comparable framework. • Working knowledge of at least one programming or scripting language used for test automation, such as Java, C#, JavaScript/TypeScript, Python, or Kotlin. • Experience testing REST APIs and analyzing JSON data, HTTP requests, responses, status codes, and authentication mechanisms. • Experience with Git-based version control and familiarity with CI/CD workflows. • Experience using Jira or a comparable work-management and defect-tracking system. • Strong analytical, troubleshooting, and problem-solving skills, with consistent attention to detail. • Good communication skills and the ability to collaborate across technical and non-technical teams. Preferred Qualifications • Experience with native automation frameworks such as XCTest/XCUITest or Espresso/UI Automator. • Familiarity with cross-platform technologies such as Flutter, React Native, or .NET MAUI. • Experience with device farms and cloud testing platforms such as BrowserStack, Sauce Labs, Firebase Test Lab, or comparable services. • Exposure to performance, accessibility, security, or resilience testing for mobile applications. • Familiarity with log analysis, crash-reporting, monitoring, and analytics tools such as Firebase Crashlytics or comparable solutions. • Experience validating push notifications, deep links, biometrics, payments, or other mobile-specific integrations. • Familiarity with ISTQB practices or relevant testing certifications is considered an advantage. Additional Information • Work environment: Agile, collaborative, cross-functional, with a strong focus on customer experience, product quality, reliability, and continuous improvement. • Location: Office-based or hybrid, depending on project and team needs. • Team structure: Cross-functional mobile product team with direct collaboration across engineering, product, design, business analysis, and operations. Summary This role contributes directly to delivering reliable, secure, and user-friendly mobile applications that support the company’s digital customer journeys. The Middle Mobile QA Engineer will combine disciplined manual testing with sustainable automation, provide clear visibility into product quality and release risk, and help embed quality throughout the mobile development lifecycle.

● Опыт тестирования АТ от 1 года. ● Уверенная работа с API: знание структуры HTTP-запроса (заголовки, тело, методы, коды статусов).

Задачи: — Разработка и оптимизация Python-бэкенда — Архитектура микросервисов и API (LLM, OCR/CV, клиент и админки) — Создание пайплайнов для LLM-агентов, harness и мультиагентные системы — Автоматизация процессов через RPA — Поддержка CI/CD и DevOps-процессов Требования: — 8+ лет в разработке, из них 4+ Python — Понимание архитектуры, системного дизайна и API — Опыт с LLM-агентами, OCR/CV или похожими AI-модулями — Prompt engineering, context engineering, тюнинг LLM и датасеты — Понимание / применение RPA — Опыт с CI/CD, Docker, продакшен-развёрткой — Бонус: опыт в healthcare и AI-комплаенсе Условия: — Удалённая работа (вне России/Украины/Беларуси), внж/пмж в локации проживания — Remote (timezone +-2-3 часа от CET) — Офлайн-встречи (EU, другие локации)

Задачи: — Развертывание и оркестрация микросервисных приложений стрима в кластерах Kubernetes — Автоматизация CI/CD пайплайнов (создание и поддержка конвейеров сборки и деплоя с использованием Groovy) — Администрирование Kafka, PostgreSQL с помощью cloud — Подготовка документации Требования: — Опыт работы на позиции DevOps/SRE от 3х лет — Глубокие знания Kubernetes, понимание архитектуры, опыт работы с helm, абстракциями (Pod, Deployment и т.п.) — Опыт работы с Kafka, понимание принципов работы брокера, опыт конфигурации — Опыт администрирования PostgreSQL, знание SQL, базовое понимание оптимизации запросов и индексов — Уверенное владение Groovy, Bash/Python — Знание Git-систем — Будет преимуществом: опыт работы в финтехе или банковских проектах (понимание специфики ИБ, работы с критичными финансовыми данными) Условия: — Удалённая работа с оформлением по ТК РФ в IT-аккредитованную компанию или ИП — ДМС (включая стоматологию) — Компенсация фитнеса — Скидки на обучение английскому (Skyeng) — Индексация заработной платы — Современная техника — IT-аккредитация компании

Location: Georgia; Belarus; Serbia; Armenia; Kyrgyzstan; Uzbekistan; Azerbaijan; Czech Republic; Montenegro; Poland; Portugal; Romania; Spain; UAE; Slovakia Workplace: remote About the Team We are Quadcode, a fintech company excelling in financial brokerage activities and delivering advanced financial products to our global clientele. Our flagship product, an internal trading platform, is offered as a Software-as-a-Service (SaaS) solution to other brokers. We are looking for a Mobile QA Engineer for our iOS team. We are currently undertaking a major redesign of our flagship trading platform, used by millions of users worldwide, with three key goals: delivering an adaptive UI across different screen sizes and device families, expanding automated regression coverage, and transitioning to native Swift-based test automation. We follow an AI-first approach, actively integrating AI tools into our daily engineering workflows, including test design, automation development, code reviews, and debugging. We work in 2-week Scrum sprints, with daily meetings at 11:00 EET/EEST. Your role will involve owning the testing process end to end, from reviewing requirements and identifying potential risks to designing test cases, executing manual tests, and automating them where appropriate. Our ideal candidate has a strong product mindset, takes ownership of features, proactively identifies issues and opportunities for improvement, collaborates with different teams, and drives features through testing to a successful release. Tasks Manual Testing: Perform functional, regression, smoke, end-to-end and integration testing of new and existing iOS functionality. Review specifications, identify risks and edge cases, prepare test cases and checklists, and validate the redesigned UI across different screen sizes, device families, and iOS versions. Test Automation: Develop and maintain automated tests to expand regression coverage across product domains. Contribute automated tests for new functionality, including end-to-end tests, and add coverage for features that are not yet covered by developer-written tests. Automation Migration: Help migrate the existing test automation framework to Swift-based automation, improving maintainability, reliability, and regression coverage. API Testing and Debugging: Test REST APIs and JSON responses, validate integrations and real-time data flows, analyze network traffic using Charles Proxy or Proxyman, and investigate issues using device logs and debugging tools. Cross-Platform Testing: Collaborate with the Android team to verify cross-platform functionality and identify inconsistencies between iOS and Android implementations. CI/CD: Integrate and maintain automated tests in CI/CD pipelines, helping ensure reliable execution and timely feedback on product changes. AI-Assisted Workflows: Use AI tools in day-to-day QA activities, including test design, test automation, code reviews, and debugging. Requirements Mobile Testing Experience: 3+ years of experience testing native mobile applications, with a focus on iOS. Understanding of platform-specific features, guidelines, and limitations (Apple Human Interface Guidelines, Material Design). Test Automation: Hands-on experience building and maintaining mobile automated tests using Appium, XCUITest, and/or Espresso. Ability to design a scalable test automation framework from scratch using patterns such as Page Object or Screenplay. Programming Skills: Proficiency in at least one programming language used for test automation: Kotlin, Java, Swift, Python, or TypeScript. Ability to write clean, readable, and maintainable test code. Testing Theory and Test Design: Solid understanding of functional, regression, smoke, integration, and end-to-end testing. Experience with test design techniques, including equivalence partitioning, boundary value analysis, decision tables, and pairwise testing. Ability to write clear test cases, checklists, and bug reports. API Testing: Experience testing REST APIs and working with JSON. Familiarity with Postman, Swagger, API automation tools such as REST Assured, Retrofit, or requests, etc.). Basic understanding of WebSockets and real-time data testing. Debugging and Traffic Analysis: Experience using Charles Proxy, Proxyman, or Fiddler for traffic interception and mocking. Ability to inspect logs using Xcode Console, Android Studio Logcat, and adb. CI/CD and Test Infrastructure: Experience integrating automated tests into CI/CD pipelines using tools such as GitLab CI, GitHub Actions, Jenkins, or Bitrise. AI Tools: Willingness to use AI-assisted tools in everyday engineering workflows, including test design, test automation development, and debugging. Languages: English at B1 level or above and Russian at C2 level. Nice to have Experience writing mobile automated tests in Swift using XCUITest. Experience migrating legacy automation frameworks or transitioning between programming languages and testing technologies. Experience testing financial applications, trading platforms, or other products where data accuracy and reliability are critical. We offer Full-time remote work (service provider contract). Competitive compensation (EUR). Flexible working hours. Corporate AI subscriptions (Claude, Gemini, GPT, etc.). Access to a rewards marketplace offering products and language courses, redeemable using the company’s internal currency. A strong team of engineers. Positive and friendly atmosphere. With a team of 500+ creative and tech-driven people across the globe, Quadcode is the place where ideas turn into impact, where every project is a chance to grow, innovate, and make your mark. Join us today, and let's shape the future of fintech together! Note: All applications will be treated with strict confidence. We thank all applicants for their interest, however, only those candidates selected for interviews will be contacted. #LI-JM1

• Опыт руководства ML- или LLM-платформой либо инфраструктурной командой. • Практическое понимание LLM-инфраструктуры: serving (vLLM, TGI, Triton или аналоги), ограничения и утилизация GPU.

— Разработка модулей планирования снабжения и производства. — Алгоритмы, структуры данных, Big O.

Location: Kyiv; Lviv Workplace: onsite Ajax Systems — міжнародна технологічна компанія і найбільший у Європі виробник охоронних систем. Продуктам Ajax довіряють уже понад 4,5 мільйони кінцевих користувачів і 330 тисяч PRO-користувачів у більш ніж 180 країнах. Компанія пропонує комплексні рішення для захисту житлових і комерційних об'єктів різного масштабу. Нині портфоліо Ajax налічує 280 пристроїв для захисту від вторгнення, відеоспостереження, пожежної безпеки та комфорту й автоматизації. Кожного року ми демонструємо кратне зростання як у чисельності команди, так і в кількості користувачів у всьому світі. Ми шукаємо розумного, технічно грамотного Python  developer  у Machine Learning Team. Video Department. Video Devices Division відповідає за повний цикл розробки відеопристроїв Ajax — від створення початкової концепції до запуску масового виробництва та подальшого масштабування. Команда зосереджена на створенні складних технологічних продуктів, що поєднують механічне проєктування, розробку апаратного забезпечення та інтеграцію низькорівневого програмного забезпечення для забезпечення стабільної роботи систем у режимі реального часу.Про роль Ми — Platform-команда, яка розбудовує інфраструктуру для ML-інженерів.Ми розробляємо пайплайни для збору та підготовки датасетів і тренування моделей,створюємо внутрішні сервіси для автоматизації роботи команди: тестування моделей на реальних пристроях, керування даними та їх перегляд і організовуємо сховище даних. Роль передбачає розвиток внутрішньої платформи, яка допомагає забезпечувати якість і оптимізувати процеси створення нових нейромоделей для камер. Вимоги: комерційний досвід роботи з Python 3 (від 3 року); розробка та впровадження автоматизованих пайплайнів; базове розуміння асинхронного та багатопотокового коду (asyncio, threading); базові знання Unix/Linux; розуміння Docker та контейнеризованих середовищ; досвід роботи з SQL; досвід роботи з Git; англійська на рівні розуміння технічної документації. Буде плюсом: досвід опрацювання великих обсягів даних; досвід роботи в ML-середовищі (розуміння етапів створення моделей); досвід роботи зі S3-сумісними сховищами; досвід роботи з Kubernetes. Задачі на проекті: організація сховища даних та інструментів для роботи з ним; автоматизація збору даних для тренування та збільшення їх обсягу; розробка та впровадження автоматизованих пайплайнів; розробка нових сервісів і підтримка наявних (FastAPI, React); робота з інфраструктурою проєкту: CI/CD (GitHub Actions), Kubernetes, AWS. Що ви отримаєте: можливість пропонувати та реалізовувати власні ідеї, які впливають на продукт та його масове виробництво; місце у стрімко зростаючій компанії з вмотивованою професійною командою; конкурентну заробітну плату; медичне страхування; корпоративні заняття з англійської мови; можливість взяти участь у внутрішньому проєкті бета-тестування систем безпеки Ajax; знижки від компаній-партнерів; знижки на продукти компанії. Ajax Systems — це українська історія успіху, яка виросла в глобальний продукт. Пристроям Ajax довіряють уже понад 4,5 мільйони кінцевих користувачів і 330 тисяч PRO-користувачів у більш ніж 180 країнах. Компанія пропонує комплексні рішення для захисту житлових і комерційних об'єктів різного масштабу. Нині портфоліо Ajax налічує 280 пристроїв для захисту від вторгнення, відеоспостереження, пожежної безпеки та комфорту й автоматизації.

Location: Poland; Warszawa, Польща On behalf of CloudTech Client #1 , SD Solutions is looking for a talented Senior DevOps Engineer - MSP to design, build, deploy, and maintain complex cloud environments for our customers using innovative automation tools and cutting-edge technologies. As a Senior DevOps Engineer, you will be responsible for architecting, maintaining, and evolving AWS cloud infrastructures, implementing and optimizing monitoring and alerting, troubleshooting issues, and developing automation to improve efficiency and reliability across environments. At AllCloud, our DevOps Engineers work with the latest and most advanced technologies. Some of the stacks we master daily for our customers include AWS, Docker, Kubernetes, Jenkins, CI/CD, Terraform, Ansible, Lambda, Python, Go, AI/ML, Big Data, IoT, and more - all while occasionally enjoying a game of 8-Ball or Nintendo Switch to keep things fun and collaborative. SD Solutions is a staffing company operating globally. Contact us to get more details about the benefits we offer. Responsibilities: Design and implement tailor-made cloud architectures based on customer needs. Manage multiple customer environments while adhering to industry best practices. Act as a trusted technical advisor to customers, ensuring alignment with business goals. Deploy advanced cloud services and automation solutions. Implement and maintain infrastructure automation and configuration management tools. Maintain a continuous feedback loop with customers to ensure deliveries meet expectations. Debug, troubleshoot, and resolve complex technical issues. Design, set up, and maintain large-scale monitoring and logging solutions. Requirements: 3+ years of hands-on experience with cloud providers (e.g., AWS, GCP). 3+ years of professional IT experience, with a strong Linux and networking background. Proven experience in a customer-facing role. Experience with security products (e.g., Firewalls, Web Gateways, Proxies). Strong experience with container technologies (Kubernetes, EKS, ECS, Swarm, Docker, etc.). Familiarity with Agile methodology. Proficiency in scripting with at least two languages: Python, Java, Bash, or PowerShell. Demonstrated creative troubleshooting and problem-solving skills. Fast learner with the ability to adapt to new technologies and domains. Strong foundations in Git and GitFlow methodologies. Experience with CI/CD platforms (Jenkins, CircleCI, CodePipeline, etc.). Hands-on experience with Infrastructure as Code (IaC) tools (Terraform, CloudFormation, CDK, Serverless Framework). Knowledge of serverless architectures . Advantages: Experience with system monitoring platforms (Datadog, Prometheus). Experience with centralized logging platforms (ELK / OpenSearch). Familiarity with GitOps methodologies (ArgoCD, Flux). Strong information security orientation. AWS certifications (Associate, Professional, or Specialty). Experience managing production-grade environments. Knowledge of AWS security tools and best practices (Security Hub, AWS Config, WAF, Shield, etc.). Familiarity with AWS Landing Zone and multi-account strategy. CKA / CKAD certifications. Eligible for or holding a security clearance. About the company: A global professional services company specializing in cloud enablement and digital transformation. An accredited partner at the highest tier with leading cloud, CRM, and data platform providers, the company helps organizations connect front and back offices through cloud adoption, data strategy, and analytics — delivering end-to-end managed services and consulting. By applying for this position, you agree to the terms outlined in our Privacy Policy. Please take a moment to review our Privacy Policy https://sd-solutions.breezy.hr/privacy-notice , and make sure you understand its contents. If you have any questions or concerns regarding our Privacy Policy, please feel free to contact us.

Location: European Union What you'll be solving A pod is mid-request. The node it's running on is about to disappear - Spot is pulling the instance, or Autoscaler has flagged the node as underutilized and marked it for removal. The safe move is to wait. The profitable move is to act now. Every team in this pipeline is built to close that gap: make the aggressive call and still guarantee nothing breaks. That guarantee is the hard part. Deciding which nodes to kill, which pods to move, and which storage volume to resize is a genuinely hard optimization problem - several of them are P=NP-hard in the general case - and it has to run continuously, in production, faster than a human would ever attempt it by hand. Get it right and clusters run at half the cost. Get it wrong once and you've taken down something live. This posting covers multiple teams working on different pieces of the same automation problem node placement algorithms and provisioning, deep integrations with tools like Karpenter, workload rightsizing (vertical and horizontal), moving running workloads between nodes without interrupting them, storage that scales itself, and GPU capacity optimization across clouds and regions. All of it runs in real time, in production, with no human tuning YAML in the loop. 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. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Understanding of Kubernetes internals – autoscaling and networking. You've personally driven a complex project end-to-end. Experience with AI coding agents and agentic development workflows. 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. Nice-to-haves: Deep hands-on experience with cloud platforms (AWS, GCP, or Azure) – including real understanding of how compute, networking, and storage work under the hood. Deep knowledge of EKS, GKE, or AKS internals. Container runtime experience CRI-O, runc, containerd. Cloud storage depth – block storage, CSI, volume management, filesystem internals. Low-level Linux experience: process internals, packet-level networking (NAT, iptables, conntrack, eBPF, SDN), filesystems, storage. Low-level systems programming experience in C or C++. Kubernetes or cloud-native OSS contributions. Experience with AI coding agents and agentic development workflows. Responsibilities: Design and build distributed systems that operate Kubernetes infrastructure autonomously at scale. Write production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1-4 weeks). Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services. Collaborate with product and other engineering teams to solve problems that don't have textbook solutions. Work with time-series data, cloud provider APIs, and Kubernetes control plane internals. Contribute to product direction and backlog - shape what gets built next, not just how it's built. Participate in on-call rotation for teams that require it. Tools we use daily: Programming Languages: Go Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs Observability: Prometheus, Grafana, Loki, Tempo CI/CD & GitOps: GitLab/Github CI with ArgoCD and Kargo What’s in it for you? Competitive salary (€6,500 - €9,000 gross, depending on the level of experience) 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. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. 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 that elevate your skills. 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, we would like to inform you that 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: Cyprus; Finland; Ireland; Malta; Moldova; North Macedonia; Sweden What you'll be solving A pod is mid-request. The node it's running on is about to disappear - Spot is pulling the instance, or Autoscaler has flagged the node as underutilized and marked it for removal. The safe move is to wait. The profitable move is to act now. Every team in this pipeline is built to close that gap: make the aggressive call and still guarantee nothing breaks. That guarantee is the hard part. Deciding which nodes to kill, which pods to move, and which storage volume to resize is a genuinely hard optimization problem - several of them are P=NP-hard in the general case - and it has to run continuously, in production, faster than a human would ever attempt it by hand. Get it right and clusters run at half the cost. Get it wrong once and you've taken down something live. This posting covers multiple teams working on different pieces of the same automation problem node placement algorithms and provisioning, deep integrations with tools like Karpenter, workload rightsizing (vertical and horizontal), moving running workloads between nodes without interrupting them, storage that scales itself, and GPU capacity optimization across clouds and regions. All of it runs in real time, in production, with no human tuning YAML in the loop. 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. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Understanding of Kubernetes internals – autoscaling and networking. You've personally driven a complex project end-to-end. Experience with AI coding agents and agentic development workflows. 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. Nice-to-haves: Deep hands-on experience with cloud platforms (AWS, GCP, or Azure) – including real understanding of how compute, networking, and storage work under the hood. Deep knowledge of EKS, GKE, or AKS internals. Container runtime experience CRI-O, runc, containerd. Cloud storage depth – block storage, CSI, volume management, filesystem internals. Low-level Linux experience: process internals, packet-level networking (NAT, iptables, conntrack, eBPF, SDN), filesystems, storage. Low-level systems programming experience in C or C++. Kubernetes or cloud-native OSS contributions. Experience with AI coding agents and agentic development workflows. Responsibilities: Design and build distributed systems that operate Kubernetes infrastructure autonomously at scale. Write production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management. Own features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1-4 weeks). Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services. Collaborate with product and other engineering teams to solve problems that don't have textbook solutions. Work with time-series data, cloud provider APIs, and Kubernetes control plane internals. Contribute to product direction and backlog - shape what gets built next, not just how it's built. Participate in on-call rotation for teams that require it. Tools we use daily: Programming Languages: Go Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs Observability: Prometheus, Grafana, Loki, Tempo CI/CD & GitOps: GitLab/Github CI with ArgoCD and Kargo What’s in it for you? Competitive salary (€6,500 - €9,000 gross, depending on the level of experience) 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. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. 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 that elevate your skills. 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, we would like to inform you that 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; Finland; Greece; Latvia; Romania; Sweden Why Cast AI? Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production. The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation. Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Global team, diverse perspectives We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. Unicorn momentum In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started. Join us as we build the future of autonomous infrastructure. 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. About the role A team ships a new service, and getting it from a laptop to production - built, tested, deployed, and visible when something goes wrong - shouldn't require that team to become infrastructure experts. It should be a paved road: a CI/CD pipeline that just works, observability that's there by default, and standard ways of doing things that are the obvious best choice, because the alternative is every team reinventing the same solutions on its own. The Platform team builds and maintains that road, and the work is internal - the users are Cast AI's own engineers. The team is a multiplier for the engineering organization: whatever it builds is built once and serves every team, and the time product teams would otherwise spend on infrastructure goes back into developing their products. What the team owns is whether the tools engineers use to build, deploy, and observe their services are good enough that reliability is actually achievable, and with hundreds of engineers and dozens of services leaning on that at once, the platform has to be fast, correct, and boring in the best sense. Requirements: Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices - not just make something work. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience in platform engineering - you've built and operated (not just consumed) most, but not necessarily all of: CI/CD and GitOps systems (GitLab CI, Argo CD, Kargo), infrastructure as code (Terraform), container orchestration (Kubernetes, Helm), observability and monitoring tooling (VictoriaMetrics, Grafana, Loki, Tempo), and cloud platforms (AWS, GCP, or Azure). Experience with AI coding agents and agentic development workflows. You've personally driven a complex project end-to-end. Strong debugging, optimization, and performance-tuning skills. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. Participate in on-call rotation for teams that require it. Nice to have: Kubernetes operators, Helm chart authoring, admission webhooks. Internal developer platform (IDP) design - golden paths, self-service tooling, service catalogs. Local development environment tooling (devcontainers, Tilt, Skaffold, or similar). Kubernetes or cloud-native OSS contributions. Responsibilities: Design, build, and operate the CI/CD pipelines every engineering team ships through. Build and maintain the observability and monitoring tooling other teams use to debug their own systems in production. Build local development environment tooling that lets engineers reproduce production-like conditions on their laptop. Reduce friction for every other team: identify where engineers lose time to infrastructure and fix it at the root, not with a workaround. Debug complex issues that span CI/CD, observability tooling, Kubernetes, and cloud infrastructure. Contribute to the platform roadmap and backlog - shape what gets built next for the engineers who depend on you. Tools we use daily: Programming Language: Go Cloud & Orchestration: Kubernetes, GCP, AWS, Azure Infrastructure as Code: Terraform Databases & Storage: ClickHouse, Cloud Object Storage Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs Observability: Grafana, VictoriaMetrics, VictoriaLogs, VictoriaTraces, Loki, Tempo CI/CD & GitOps: GitLab CI, ArgoCD, Kargo What’s in it for you? Competitive salary (€6,500 – €9,000 gross, depending on the level of experience) plus separate compensation for on-call participation (passive coverage and active interventions) 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. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. 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 that elevate your skills. 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. You'll be expected to travel to Vilnius for onboarding - travel costs are covered by the company. 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, we would like to inform you that 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: Cyprus; Ireland; Malta; Moldova; Montenegro; North Macedonia; Ukraine Why Cast AI? Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production. The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation. Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Global team, diverse perspectives We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. Unicorn momentum In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started. Join us as we build the future of autonomous infrastructure. 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. About the role A team ships a new service, and getting it from a laptop to production - built, tested, deployed, and visible when something goes wrong - shouldn't require that team to become infrastructure experts. It should be a paved road: a CI/CD pipeline that just works, observability that's there by default, and standard ways of doing things that are the obvious best choice, because the alternative is every team reinventing the same solutions on its own. The Platform team builds and maintains that road, and the work is internal - the users are Cast AI's own engineers. The team is a multiplier for the engineering organization: whatever it builds is built once and serves every team, and the time product teams would otherwise spend on infrastructure goes back into developing their products. What the team owns is whether the tools engineers use to build, deploy, and observe their services are good enough that reliability is actually achievable, and with hundreds of engineers and dozens of services leaning on that at once, the platform has to be fast, correct, and boring in the best sense. Requirements: Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices - not just make something work. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. Experience in platform engineering - you've built and operated (not just consumed) most, but not necessarily all of: CI/CD and GitOps systems (GitLab CI, Argo CD, Kargo), infrastructure as code (Terraform), container orchestration (Kubernetes, Helm), observability and monitoring tooling (VictoriaMetrics, Grafana, Loki, Tempo), and cloud platforms (AWS, GCP, or Azure). Experience with AI coding agents and agentic development workflows. You've personally driven a complex project end-to-end. Strong debugging, optimization, and performance-tuning skills. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. Participate in on-call rotation for teams that require it. Nice to have: Kubernetes operators, Helm chart authoring, admission webhooks. Internal developer platform (IDP) design - golden paths, self-service tooling, service catalogs. Local development environment tooling (devcontainers, Tilt, Skaffold, or similar). Kubernetes or cloud-native OSS contributions. Responsibilities: Design, build, and operate the CI/CD pipelines every engineering team ships through. Build and maintain the observability and monitoring tooling other teams use to debug their own systems in production. Build local development environment tooling that lets engineers reproduce production-like conditions on their laptop. Reduce friction for every other team: identify where engineers lose time to infrastructure and fix it at the root, not with a workaround. Debug complex issues that span CI/CD, observability tooling, Kubernetes, and cloud infrastructure. Contribute to the platform roadmap and backlog - shape what gets built next for the engineers who depend on you. Tools we use daily: Programming Language: Go Cloud & Orchestration: Kubernetes, GCP, AWS, Azure Infrastructure as Code: Terraform Databases & Storage: ClickHouse, Cloud Object Storage Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs Observability: Grafana, VictoriaMetrics, VictoriaLogs, VictoriaTraces, Loki, Tempo CI/CD & GitOps: GitLab CI, ArgoCD, Kargo What’s in it for you? Competitive salary (€6,500 – €9,000 gross, depending on the level of experience) plus separate compensation for on-call participation (passive coverage and active interventions) 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. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. 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 that elevate your skills. 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. You'll be expected to travel to Vilnius for onboarding - travel costs are covered by the company. 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, we would like to inform you that 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: Croatia; Cyprus; Estonia; Greece; Ireland; Malta; Romania Why Cast AI? Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production. The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation. Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS. Global team, diverse perspectives We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead. Unicorn momentum In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started. Join us as we build the future of autonomous infrastructure. 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, Slovenia, and Ukraine. What you'll be solving Every dollar Cast AI saves a customer has to be provable, every action taken on their infrastructure has to be attributable to someone authorized to take it, and every price used to make that case has to be current across every cloud, region, and availability zone. This is the trust and accounting layer underneath the whole platform: get it wrong, and customers can't log in, can't trust the savings number, or get billed incorrectly - any one of which ends the relationship. This posting covers multiple teams working on different pieces of the same trust-and-accounting problem: authentication, authorization, and SSO for every user and workload. Billing, audit trails, notifications, and feature flags that keep the platform transparent for every customer. Real-time cloud pricing tracking across every region and availability zone, including Spot availability and discounts. And reporting that turns high-volume time-series data into fast, accurate answers about what the automation actually saved. Requirements Strong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices - not just make something work. Production experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language. You've built or operated trust-critical systems at scale - authentication/authorization, billing, or financial/accounting-adjacent data, where being wrong has real consequences. Good understanding of API design best practices - versioning, backward compatibility, auth, idempotency, async patterns, and similar. Strong debugging, optimization, and performance-tuning skills – including query profiling, index design, and database performance tuning beyond ORM usage. Experience operating and optimizing systems under high load - you know how to find and fix the bottleneck, not just add more resources. Hands-on experience with Kubernetes - you understand the core concepts (pods, services, deployments) and have deployed or debugged something on a cluster. Experience with AI coding agents and agentic development workflows. You've personally driven a complex project end-to-end. Strong English skills, both verbal and written. Startup mindset: adaptable, proactive, and comfortable with ambiguity. Participate in on-call rotation for teams that require it. Nice to haves Multi-tenant identity system design - authentication, authorization, SSO. Enterprise identity protocols - SAML, OIDC, and SCIM for enterprise account provisioning and sync. Billing, audit-trail, notification, or feature-flag systems in production. Experience with cloud provider pricing/billing APIs across AWS, GCP, or Azure, or tracking Spot instance availability. High-cardinality time-series ingestion and querying at scale. Understanding of Kubernetes internals. CI/CD and DevOps practices experience. Observability tooling (Prometheus, Grafana, OpenTelemetry) in production. Responsibilities Design, build, and operate backend services in Go that other teams and customers depend on being correct. Own features end-to-end: from design through implementation, testing, and production rollout. Debug complex production issues involving security-, money-, or trust-critical flows. Collaborate with product and other engineering teams to solve problems that don't have textbook solutions. Contribute to product direction and backlog - shape what gets built next, not just how it's built. Tools we use daily Programming Language: Go Cloud & Orchestration: Kubernetes, AWS, GCP, Azure Infrastructure as Code: Terraform Databases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse Messaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs Observability: Prometheus, Grafana, Loki, Tempo CI/CD & GitOps: GitLab CI with ArgoCD What’s in it for you? Competitive salary (€6,500 – €9,000 gross, depending on the level of experience) plus separate compensation for on-call participation (passive coverage and active interventions) 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. Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. 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 that elevate your skills. 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. You'll be expected to travel to Vilnius for onboarding - travel costs are covered by the company. 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, we would like to inform you that 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