Location: Porto, Portugal
Workplace: hybrid
TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization.
We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact?
Responsibilities
We are looking for a Backend Software Engineer to join the teams building and running the backend services that power TeamViewer products. You will design, build and operate services that must be secure, reliable and scalable, working in an agile team alongside product, frontend and platform engineers.
Design, develop and maintain backend services and APIs using Java/Kotlin with Spring Boot or Node.js/TypeScript.
Build scalable, resilient services following clean architecture, domain-driven and event-driven principles.
Design data models and work with both SQL and NoSQL databases.
Implement asynchronous communication between services using messaging systems such as Kafka, NATS or RabbitMQ.
Containerize and deploy services with Docker and Kubernetes and contribute to CI/CD pipelines.
Write automated tests (unit, integration, contract) and take part in code reviews.
Use AI coding assistants effectively in your daily work, while keeping ownership of quality, security and maintainability.
Monitor and improve services in production, with a focus on performance, security and observability.
Collaborate with your team and other teams on technical decisions, shared standards and knowledge sharing.
Requirements
A degree in Computer Science, Software Engineering or a related field, or equivalent experience.
3+ years of professional experience in backend software development.
Solid experience with Java and/or Kotlin and Spring Boot, or with Node.js and TypeScript.
Good understanding of RESTful API design and distributed systems concepts.
Experience with relational (e.g. PostgreSQL) and NoSQL databases.
Familiarity with messaging systems such as Kafka, NATS or RabbitMQ.
Hands-on experience with Docker; Kubernetes experience is a plus.
Strong testing mindset and familiarity with CI/CD practices.
Hands-on experience with AI coding tools (e.g. Claude Code, GitHub Copilot, Cursor), including critically reviewing and testing AI-generated code.
Experience working in agile teams.
Fluent in English (spoken and written).
What we offer
Onsite Onboarding
in our HQ office for an optimal start
Great compensation and benefits packages
including company achievement bonus or sales bonus and regular salary reviews
Public transport friendly
offices
Special terms
for local gyms
Access to
Corporate Benefits platform
with many
discounts
Regular
Team events
and company-wide celebrations
Open door policy
, no dress code rules, frequent all Hands and Leadership Lunches
Hybrid
and
Flexible
work time
Work From Abroad Program
allowing up to 40 days of work outside your contracting country
We celebrate
diversity
as one of core values, join and drive one of the c-a-r-e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
If you require any accommodations or adjustments during the application or hiring process, including interview or onboarding support, please reach out to your Talent Acquisition Partner, who will be happy to support you.
Наша компания занимается продуктовой разработкой проектов наших Заказчиков под ключ. Проект — крупный коммерческий банк в РФ.
Ожидания:
— Опыт работы в QA: от 4 лет.
— Опыт автоматизации тестирования на Java: от 2 лет.
Требуемые знания и навыки:
— Опыт тестирования mobile/web приложений (от 2 лет).
— Опыт работы с Rest API.
— Опыт работы с SQL/NoSQL БД на уровне сложных запросов и выгрузок (join, View и т.д.).
— Опыт покрытия новых функциональностей при помощи инструментов автотестирования (Java).
— Опыт работы с интеграционным тестированием.
— Опыт работы с CI/CD (Jenkins, GitLab CI).
— Опыт работы с брокерами сообщений (Kafka, RabbitMQ, аналоги).
— Опыт работы с мок-сервисами (Wiremock или аналоги).
— Опыт написания библиотек и инструментов для автоматизации тестирования.
— Опыт применения процессов и методологий разработки программного обеспечения.
— Опыт применения инструментов и технологий разработки ПО.
— Опыт работы с системами на микросервисной архитектуре (Spring Cloud, Kubernetes, Openshift или аналоги).
— Опыт развертывания инфраструктуры.
— Опыт работы с системами Cache (Redis, Hazelcast).
— Инструменты Docker, Jenkins, K8s, SOAP UI, Postman, Jira, Confluence, Git, IntelliJ IDEA, Bitbucket, Docker Compose.
Дополнительная информация:
— Web и mobile тестирование: мобилка + веб.
— Backend и frontend тестирование: 80% / 20%.
— Ручное и автоматическое тестирование: 70% ручное, 30% авто.
Location: Porto, Portugal
Workplace: hybrid
TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization.
We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact?
Responsibilities
We are looking for a Full Stack Software Engineer to join the teams building the backend services that power TeamViewer products and the web applications on top of them. You will work across the stack, from APIs and data to user interfaces, in an agile team alongside product, UX and platform engineers.
Develop and maintain backend services and APIs using Java/Kotlin with Spring Boot or Node.js/TypeScript.
Build web applications and features using React and TypeScript, using our design system and shared components.
Design data models and work with both SQL and NoSQL databases.
Integrate services through REST APIs and messaging systems such as Kafka, NATS or RabbitMQ.
Containerise and deploy applications with Docker and Kubernetes, and contribute to CI/CD pipelines.
Write automated tests across the stack and take part in code reviews.
Use AI coding assistants effectively in your daily work, while keeping ownership of quality, security and maintainability.
Monitor and improve features in production, with a focus on quality, performance and security.
Collaborate with your team and other teams on technical decisions and knowledge sharing.
Requirements
A degree in Computer Science, Software Engineering or a related field, or equivalent experience.
3+ years of professional experience in fullstack development.
Solid backend experience with Java and/or Kotlin and Spring Boot, or with Node.js and TypeScript.
Solid experience with React and TypeScript.
Good understanding of RESTful API design and web application architecture.
Experience with relational (e.g. PostgreSQL) and NoSQL databases.
Familiarity with messaging systems such as Kafka, NATS or RabbitMQ is a plus.
Hands-on experience with Docker; Kubernetes experience is a plus.
Strong testing mindset and familiarity with CI/CD practices.
Hands-on experience with AI coding tools (e.g. Claude Code, GitHub Copilot, Cursor), including critically reviewing and testing AI-generated code.
Experience working in agile teams.
Fluent in English (spoken and written).
What we offer
Onsite Onboarding
in our HQ office for an optimal start
Great compensation and benefits packages
including company achievement bonus or sales bonus and regular salary reviews
Public transport friendly
offices
Special terms
for local gyms
Access to
Corporate Benefits platform
with many
discounts
Regular
Team events
and company-wide celebrations
Open door policy
, no dress code rules, frequent all Hands and Leadership Lunches
Hybrid
and
Flexible
work time
Work From Abroad Program
allowing up to 40 days of work outside your contracting country
We celebrate
diversity
as one of core values, join and drive one of the c-a-r-e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
If you require any accommodations or adjustments during the application or hiring process, including interview or onboarding support, please reach out to your Talent Acquisition Partner, who will be happy to support you.
Location: Porto, Portugal
Workplace: hybrid
TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization.
We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact?
Responsibilities
We are looking for a Senior Frontend Software Engineer to build the web experiences on top of the backend services that power TeamViewer products. You will shape our frontend architecture, drive quality and consistency across web applications, and act as a technical reference for other engineers in an agile, modern environment.
Design, build and maintain complex, large-scale web applications using React and TypeScript.
Own and evolve the frontend architecture, including micro-frontend patterns (e.g. Module Federation, Piral), monorepo setup and shared component libraries.
Define state management and data-fetching strategies, separating server state, client state and UI state in a clear, scalable way.
Contribute to and help govern our design system together with UX/UI designers, ensuring consistency, accessibility and reusability.
Integrate frontends with backend services and APIs, working with backend engineers on API contracts, authentication flows and data models.
Drive web performance: rendering optimization, code splitting, bundle size and Core Web Vitals.
Ensure high standards for security, accessibility, internationalization and browser compatibility.
Define and drive frontend testing practices (unit, integration, visual regression, end-to-end).
Contribute to build tooling, CI/CD pipelines and containerized deployments with Docker and Kubernetes.
Drive adoption of AI-assisted development in the frontend: set good practices, share workflows and keep quality high.
Mentor other engineers, lead code reviews and drive technical decisions within and across teams.
Requirements
A degree in Computer Science, Software Engineering or a related field, or equivalent experience.
6+ years of professional experience in frontend development, with a track record of leading technical topics.
Expert knowledge of React (hooks, context, concurrent rendering, Suspense), TypeScript and modern JavaScript.
Deep experience with well-known state management and data-fetching libraries, such as Redux Toolkit (incl. RTK Query), Zustand, MobX, TanStack Query or XState, and the judgement to choose the right tool for each case.
Proven experience building and maintaining design systems or component libraries (e.g. Storybook, design tokens, theming).
Experience with micro-frontend architectures and scalable frontend codebases, including monorepo tooling (e.g. Nx, Turborepo).
Strong knowledge of modern build tooling (e.g. Vite, Webpack) and bundling optimisation.
Solid understanding of web performance profiling and optimization (memoisation, virtualization, lazy loading, Core Web Vitals).
Experience with API integration via REST and/or GraphQL, real-time communication (WebSockets) and authentication standards such as OAuth 2.0 / OpenID Connect.
Strong knowledge of web accessibility (WCAG) and web security best practices (XSS, CSRF, CSP).
Experience with frontend testing tools such as Jest or Vitest, React Testing Library, and Playwright or Cypress.
Experience with frontend observability and error tracking (e.g. Sentry, OpenTelemetry) is a plus.
Experience with SSR frameworks (e.g. Next.js) or Node.js is a plus.
Hands-on experience with AI coding tools (e.g. Claude Code, GitHub Copilot, Cursor) and a clear view on how to use them responsibly in a team.
Experience mentoring engineers and working in agile teams.
Fluent in English (spoken and written).
What we offer
Onsite Onboarding
in our HQ office for an optimal start
Great compensation and benefits packages
including company achievement bonus or sales bonus and regular salary reviews
Public transport friendly
offices
Special terms
for local gyms
Access to
Corporate Benefits platform
with many
discounts
Regular
Team events
and company-wide celebrations
Open door policy
, no dress code rules, frequent all Hands and Leadership Lunches
Hybrid
and
Flexible
work time
Work From Abroad Program
allowing up to 40 days of work outside your contracting country
We celebrate
diversity
as one of core values, join and drive one of the c-a-r-e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
If you require any accommodations or adjustments during the application or hiring process, including interview or onboarding support, please reach out to your Talent Acquisition Partner, who will be happy to support you.
Location: Bulgaria; Croatia; Cyprus; Estonia; Finland; Greece; Hungary; Ireland; Latvia; Lithuania; Malta; Moldova; Montenegro; North Macedonia; Poland; Romania; Slovakia; Slovenia; Sweden; Ukraine
Why Kimchi?
Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters and now we're providing a managed variant of those same capabilities.
Our Infrastructure today
Multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API and deployment ranging from our GPUs to your own VPC. The inference layer is the foundation and the API is what sits in front of it as the primary channel for broadly and reliably distributing our AI services and powers our own Kimchi harness.
As a Senior Software Engineer, you will have the opportunity to work on different key features of our product. All of these are high-agency roles across multiple parts of the tech stack that minimize process friction that would otherwise prevent you from shipping.
In every team you will own features end-to-end: design, implementation, testing, production rollout. Most projects ship in 1-4 weeks. You'll work directly with product and other engineering teams on problems that don't have textbook solutions.
We are currently hiring
Senior Software Engineers
for the following teams
Agent Platform Team:
The Agent Platform squad builds the infrastructure that lets teams run fleets of AI agents securely, whether in the cloud or self-hosted, so work can move confidently from a developer's laptop to production environments. The platform enforces least-privilege access to resources, requires human approval before agents can touch anything critical, and logs every action agents take for full auditability. The goal is to give engineering and operations teams the confidence to scale up agent usage without sacrificing security, control, or visibility into what their agents are actually doing.
Responsibilities:
Design and build distributed systems that run agent fleets at scale across cloud and self-hosted environments, with security at its core
Make every agent action observable, auditable, and governable
Develop a remote-first experience of working with agents
Requirements
Production experience with Go or Typescript is strongly preferred; candidates without either should demonstrate strong systems programming skills in a comparable language.
Strong debugging, optimization, and performance-tuning skills – including query profiling, index design, and database performance tuning beyond ORM usage.
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and Kubernetes is a strong plus
Observability tooling (Prometheus, Grafana, OpenTelemetry), CI/CD and DevOps practices experience.
Startup mindset: adaptable, proactive, and comfortable with ambiguity.
Strong English skills, both verbal and written.
You've personally driven a complex project end-to-end.
(Agent Platform) Experience in virtualization, networking, security, and Kubernetes internals is a strong plus
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: Bulgaria; Croatia; Cyprus; Estonia; Finland; Greece; Hungary; Ireland; Latvia; Lithuania; Malta; Moldova; Montenegro; North Macedonia; Poland; Romania; Slovakia; Slovenia; Sweden; Ukraine
Why Kimchi?
Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters and now we're providing a managed variant of those same capabilities.
Our Infrastructure today
Multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API and deployment ranging from our GPUs to your own VPC. The inference layer is the foundation and the API is what sits in front of it as the primary channel for broadly and reliably distributing our AI services and powers our own Kimchi harness.
As a Senior Software Engineer, you will have the opportunity to work on different key features of our product. All of these are high-agency roles across multiple parts of the tech stack that minimize process friction that would otherwise prevent you from shipping.
In every team you will own features end-to-end: design, implementation, testing, production rollout. Most projects ship in 1-4 weeks. You'll work directly with product and other engineering teams on problems that don't have textbook solutions.
We are currently hiring
Senior Software Engineers
for the
Harness team
:
OpenAI and Anthropic ship models. They also ship one harness each – the scaffolding that turns a raw model into something that can plan, execute, recover, and complete work. We ship a different kind of harness: one built for cost-conscious, long-horizon autonomy, running on inference infrastructure we control end-to-end.
A decent model with a great harness beats a great model with a bad harness. We've watched this play out. The gap between what today's models can do and what you see them doing is largely a harness gap – and that gap is where we operate.
Responsibilities:
Architect planner/executor/evaluator pipelines – planning with a reasoning model, execution with a fast one, evaluation with a third. No self-verification.
Manage agent memory and context – state persistence across sessions, context compaction, tool-call offloading
Own the harness surface - TUI, MCP integrations, telemetry.
Work directly with users - including our own colleagues - to identify, understand and fix pain points
Requirements
Production experience with Go or Typescript is strongly preferred; candidates without either should demonstrate strong systems programming skills in a comparable language.
Strong debugging, optimization, and performance-tuning skills – including query profiling, index design, and database performance tuning beyond ORM usage.
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and Kubernetes is a strong plus
Observability tooling (Prometheus, Grafana, OpenTelemetry), CI/CD and DevOps practices experience.
Startup mindset: adaptable, proactive, and comfortable with ambiguity.
Strong English skills, both verbal and written.
You've personally driven a complex project end-to-end.
(Harness) Experience on working with harnesses and creating your own AI workflows is a strong plus
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: Bulgaria; Croatia; Cyprus; Estonia; Finland; Greece; Hungary; Ireland; Latvia; Lithuania; Malta; Moldova; Montenegro; North Macedonia; Poland; Romania; Slovakia; Slovenia; Sweden; Ukraine
Why Kimchi?
Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters and now we're providing a managed variant of those same capabilities.
Our Infrastructure today
Multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API and deployment ranging from our GPUs to your own VPC. The inference layer is the foundation and the API is what sits in front of it as the primary channel for broadly and reliably distributing our AI services and powers our own Kimchi harness.
As a
Senior Software Engineer
, you will have the opportunity to work on different key features of our product. All of these are high-agency roles across multiple parts of the tech stack that minimize process friction that would otherwise prevent you from shipping.
In every team you will own features end-to-end: design, implementation, testing, production rollout. Most projects ship in 1-4 weeks. You'll work directly with product and other engineering teams on problems that don't have textbook solutions.
We are currently hiring
Senior Software Engineers
for the
API Platform Team
:
Owns the inference API responsible for delivering our AI services across the world while making sure it's reliable and capable to scale in tandem with our company's growing ambitions, as well as our analytical platform, billing and role-based controls that enable our users to monitor and control their usage with ease - be it as a solo developer or a large enterprise. You'll own our infrastructure, datastores, analytics, observability and CI/CD pipeline.
Responsibilities:
Develop with observability in mind, identify bottlenecks and optimize for performance. When p99 latency climbs, you find the cause through query profiles and flame graphs instead of raising the alert threshold.
Design the datastores and distributed systems behind the inference API, and keep them reliable as usage scales from a solo developer to a large enterprise.
Build the billing, usage metering, and role-based controls that let users monitor and govern their own consumption. Catch correctness problems where a wrong number costs you trust.
Requirements
Production experience with Go or Typescript is strongly preferred; candidates without either should demonstrate strong systems programming skills in a comparable language.
Strong debugging, optimization, and performance-tuning skills – including query profiling, index design, and database performance tuning beyond ORM usage.
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and Kubernetes is a strong plus
Observability tooling (Prometheus, Grafana, OpenTelemetry), CI/CD and DevOps practices experience.
Startup mindset: adaptable, proactive, and comfortable with ambiguity.
Strong English skills, both verbal and written.
You've personally driven a complex project end-to-end.
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
Ищем Senior QA Engineer в крупную технологическую компанию, которая разрабатывает высоконагруженные платформенные продукты для международных рынков в entertainment-индустрии.
Продукты построены на микросервисной архитектуре, поэтому важно уметь смотреть на систему целиком: разбираться во взаимодействии сервисов, тестировать frontend и backend и понимать, что происходит на разных уровнях приложения.
Задачи:
— участвовать в обеспечении качества продукта на всех этапах разработки и релизного процесса;
— тестировать frontend и backend;
— заниматься как ручным тестированием, так и автоматизацией;
— разрабатывать и поддерживать E2E-автотесты на Playwright;
— развивать API-автоматизацию;
— тестировать REST API и WebSocket;
— работать с микросервисами и проверять интеграции между сервисами;
— работать с SQL и данными;
— поддерживать и развивать автотесты в CI/CD;
— участвовать в выборе подходов к тестированию новой функциональности;
— улучшать QA-процессы и подходы внутри команды;
— проводить code review автотестов и делиться экспертизой с другими QA.
Требования:
— опыт в QA от 5 лет;
— сильный опыт ручного тестирования frontend и backend;
— коммерческий опыт автоматизации и самостоятельного написания автотестов;
— JavaScript / TypeScript;
— уверенный практический опыт с Playwright;
— опыт UI- и API-автоматизации;
— хороший уровень работы с REST API;
— опыт работы с WebSocket;
— понимание микросервисной архитектуры и взаимодействия сервисов;
— уверенная работа с SQL;
— понимание CI/CD и того, как автоматизированные тесты встраиваются в pipeline;
— умение самостоятельно определять подход к тестированию, оценивать риски и отвечать за качество своей части продукта.
Для Senior-уровня также важен опыт развития QA-практик: mentoring, code review, помощь коллегам и участие в улучшении процессов.
Будет плюсом:
— опыт с message brokers;
— Docker / Kubernetes;
— нагрузочное тестирование;
— GraphQL;
— Redis;
— опыт мобильного тестирования.
Условия:
— full-time;
— удаленный формат работы;
— гибкое начало рабочего дня;
— корпоративная техника;
— испытательный срок 3 месяца;
— расширенный пакет бенефитов после испытательного срока: медицинская страховка, бюджет на спорт / языки / дополнительное медицинское покрытие, дополнительные оплачиваемые дни отдыха;
— внутренние технические встречи, тренинги и возможность участия в профессиональных конференциях и обучении.
Рабочий язык команды — русский, поэтому для позиции нужен свободный разговорный русский.
Процесс: Знакомство с рекрутером → короткий технический скрининг → основное техническое интервью → встреча с командой.
УдалённоseniorГеография найма не уточнена, офис: Белград
Задачи:
— разработка на Python с использованием asyncio, FastAPI
— работа с брокерами и таск-менеджерами: Kafka, RabbitMQ, Celery
— оптимизация запросов и проектирование схем в PostgreSQL
— реализация межсервисных коммуникаций через gRPC, REST, Webhooks
— написание фронтенд-компонентов на TypeScript и React
— применение DevOps-практик: Docker, CI/CD, развертывание в Kubernetes
— использование инструментов мониторинга Prometheus и Grafana
— обеспечение покрытия кода тестами
Требования:
— 3+ года коммерческого опыта на Python с глубоким пониманием asyncio, FastAPI
— опыт работы с Kafka, RabbitMQ, Celery
— уверенные знания PostgreSQL (query tuning, schema design)
— практический опыт межсервисных коммуникаций: gRPC, REST, Webhooks
— опыт написания фронтенд-компонентов на TypeScript / React
— понимание DevOps-практик: Docker, CI/CD, Kubernetes
— опыт работы с инструментами мониторинга Prometheus / Grafana
— культура покрытия кода тестами
— будет плюсом опыт работы с телеком-инфраструктурой, IP-телефонией, CTI или системами контакт-центров
Условия:
— full-time
— b2b-контракт
— почасовая оплата
— удалённая работа, строго по России
Задачи:
— Разрабатывать и поддерживать backend-сервисы на Go.
— Развивать микросервисную архитектуру и REST/gRPC API.
— Работать с PostgreSQL, Redis и очередями сообщений.
— Разрабатывать асинхронные процессы и интеграции.
— Писать тесты, участвовать в code review.
— Поддерживать надежность сервисов и разбирать production-инциденты.
Требования:
— Опыт в blockchain, crypto.
— Работа с финансовыми транзакциями, балансами, ledger или billing.
— Опыт разработки wallet, deposit/withdrawal-сервисов.
— Знание OpenTelemetry, Prometheus, Grafana и других observability-инструментов.
— Понимание AML/KYC, PCI DSS или GDPR.
— От 3 лет коммерческой разработки на Go.
— Опыт разработки и поддержки production backend-сервисов.
— Понимание микросервисной архитектуры.
— Опыт работы с PostgreSQL, Redis и Kafka / RabbitMQ / NATS или аналогами.
— Понимание транзакционности, идемпотентности и конкурентного доступа.
— Опыт написания тестов и работы с Docker.
— Базовое понимание Kubernetes.
— Знание HTTP, TLS, JWT/OAuth2, authentication/authorization.
— Умение писать читаемый, поддерживаемый и безопасный код.
Условия:
— Гибридный формат работы в Минске.
Задачи:
— построение нового продукта с нуля
Требования:
— опыт работы CTO/Head of Engineering от 3-х лет в B2B, e-commerce или логистических проектах
— практический опыт построения микросервисной или модульной архитектуры (DDD, API-first, event-driven)
— глубокое понимание CI/CD, контейнеризации (Docker, Kubernetes) и облачной инфраструктуры
— опыт интеграции с 1С/ERP, WMS, CRM и платежными шлюзами
— разговорный английский на уровне B2
— стратегическое мышление и умение переводить бизнес-задачи на технический язык
— лидерские качества и опыт антикризисного управления
Условия:
— удалённая работа
Требуется Senior DevOps-инженер в команду, которая занимается проектом крупнейшего производителя ювелирной продукции.
Требования:
— коммерческий опыт в DevOps или SRE от 4 лет;
— реальный опыт проектирования и построения инфраструктуры с нуля;
— опыт эксплуатации Docker Swarm в production;
— уверенное знание и production-опыт Kubernetes;
— опыт настройки GitLab CI/CD, раннеров и пайплайнов для фронтенда и бэкенда;
— понимание сетевой модели и проксирования через Nginx;
— опыт эксплуатации Percona XtraDB Cluster / Galera в production: кворум и split-brain, SST/IST, bootstrap после падения, бэкапы через Percona XtraBackup;
— опыт работы с Docker, PostgreSQL, Redis и S3-совместимым хранилищем;
— опыт настройки Prometheus, Grafana, Loki и Zabbix;
— готовность участвовать в архитектурных решениях, работе с командами разработки и технических переговорах с подрядчиками.
Условия:
— гибридный формат работы в Москве;
— клубы по интересам, летний выезд на природу AGIMA Camp и корпоративные вечеринки, куда можно приглашать и свою семью;
— открытость к решению любых вопросов и поддержка в создании вашего личного бренда для профессионального роста;
— бесплатные билеты на культовый забег для IT-специалистов RUNIT;
— участие в профильных конференциях с оплатой дороги и участия, если выступаете как спикер;
— доступ к разработанным курсам по UX-дизайну, проджект-менеджменту, тимлидингу и другим направлениям.
Location: Canada
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Location: United States
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Задачи:
— Разработка AI-агентов, которые выполняют рабочие процессы, а не только чат-интерфейсы.
— Работа с агентами, которые подключаются к API и внутренним системам, используют инструменты, извлекают контекст, принимают решения на нескольких шагах и восстанавливаются при сбоях.
Требования:
— Опыт разработки на Python и бекенд инженерия.
— Опыт работы с LLM API и агентными системами в продакшене.
— Знание LangGraph, LangChain, LlamaIndex или аналогичных технологий.
— Опыт работы с вызовом функций/инструментов и структурированными выводами.
— Знание RAG, embeddings, векторного поиска и управления контекстом.
— Опыт работы с состоянием агента, памятью, маршрутизацией, повторными попытками и логикой резервного копирования.
— Интеграция API и событийно-ориентированные рабочие процессы.
— Оценка, трассировка и отладка LLM.
— Опыт работы с Docker, Kubernetes, CI/CD и AWS.
— Приветствуется опыт мультиагентной оркестрации, MCP, workflows с участием человека и мониторингом агентов в продакшене.
Условия:
— Удалённая работа.
— Полная занятость или контракт.
Location: Remote / Germany
Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We're handling petabyte-scale data with sub-second queries. Our product is a Kubernetes‑based platform delivered as B2B SaaS or as a self‑hosted on‑prem solution, including air‑gapped deployments. We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence.
Role
The Learning and Development Expert - Programs & Content designs and runs our training programs and content, from onboarding to workshops. Uses data and feedback to continuously improve, and works closely with our team leads.
What you'll do
Design and run our training programs and content, ranging from onboarding to workshops
Create and maintain training content, including e-learning modules, onboarding curricula, toolkits, and workshops
Support learning needs assessments by working closely with team leads
Organize and run training sessions as well as feedback cycles
Analyze training feedback and outcomes to continuously improve programs and content
Collaborate closely with our LMS and Data specialist to align metrics, analytics, and reporting processes
About you
2+ years of experience in L&D, training, or instructional design
Creative in content creation, balanced with a structured, self-directed way of working in a remote-first environment
Practical experience working with an LMS (as a user)
Good numerical instincts for interpreting training data
Fluent in English and German (C1+).
Based and authorized to work in Germany
Nice-to-haves
Experience with instructional design methods (e.g., ADDIE)
Experience with facilitation/workshop moderation
Experience or certification in coaching
What we offer
Remote-first, Germany-wide:
Work from wherever you do your best work, with regular team gatherings in Berlin and other off-site locations.
Flexibility by default:
Flexible working hours help you make work fit your life.
Your setup, your way:
Get a personal home-office equipment budget to create a workspace that works for you.
30 days of vacation:
Take the time you need to recharge and come back with fresh energy.
Keep growing:
We invest in your personal and professional development.
Get rewarded for impact:
Performance bonuses are tied to agreed objectives and key results.
A warm welcome:
Every new team member gets a welcome goodie bag.
Good people, good times:
From summer and Christmas parties to regular team gatherings, we make time to celebrate together.
A mission that matters:
Work on challenges with tangible impact on public safety and national security.
Location: Remote / Germany
Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We're handling petabyte-scale data with sub-second queries. Our product is a Kubernetes‑based platform delivered as B2B SaaS or as a self‑hosted on‑prem solution, including air‑gapped deployments. We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence.
Role
The Learning and Development Expert - LMS & Data owns the technical and data backbone of our learning infrastructure. Makes sure the LMS runs smoothly, data is captured cleanly, and gives the L&D team the foundation for sound, data-driven decisions.
What you'll do
Build, configure, and maintain the LMS (course structure, user management, automations, reporting)
Collect and analyze learning KPIs (completion rates, engagement, skill-gap data) and translate them into clear dashboards
Support learning needs assessments through data analysis (skill matrices, team-level training gaps)
Produce regular reports on the effectiveness of learning initiatives for leadership
Act as the technical point of contact for LMS integrations with other HR systems
Support the organization and execution of training sessions and feedback cycles
About you
2+ years of experience in L&D, HR analytics, HR controlling, or another data-heavy role
Practical experience building or administering an LMS (e.g., Personio, Docebo, TalentLMS)
Very strong command of Google Sheets and data-driven decisions in an L&D context
Analytical, structured approach with a self-directed way of working in a remote-first environment
Conceptual approach to project work
Fluent in English and German (C1+)
Based and authorized to work in Germany
Nice-to-haves
Experience with BI tools (e.g., Looker, Tableau)
Experience with LMS integrations/APIs
What we offer
Remote-first, Germany-wide:
Work from wherever you do your best work, with regular team gatherings in Berlin and other off-site locations.
Flexibility by default:
Flexible working hours help you make work fit your life.
Your setup, your way:
Get a personal home-office equipment budget to create a workspace that works for you.
30 days of vacation:
Take the time you need to recharge and come back with fresh energy.
Keep growing:
We invest in your personal and professional development.
Get rewarded for impact:
Performance bonuses are tied to agreed objectives and key results.
A warm welcome:
Every new team member gets a welcome goodie bag.
Good people, good times:
From summer and Christmas parties to regular team gatherings, we make time to celebrate together.
A mission that matters:
Work on challenges with tangible impact on public safety and national security.
ГибридPorto, Portugal
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
Автоотклики