Вакансии

Location: London Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. We are looking for an experienced Trading Systems Software Engineer to help build the applications, platforms and engineering capabilities that support QRT’s global trading environment. This is a broad software engineering role spanning application development, distributed systems, cloud technology, deployment automation and production engineering. You will design and build software used by traders, quantitative researchers, operations teams and other engineers across the firm. Your Future Role within QRT Design, develop and maintain production-grade applications, services and APIs supporting QRT’s trading platform. Build shared platforms and reusable capabilities that can be adopted across multiple trading desks and engineering teams. Develop modern web applications and operational tools that improve visibility, control and efficiency across trading workflows. Design scalable distributed and event-driven systems that integrate with trading platforms, market data services and internal infrastructure. Build deployment tooling, release automation and self-service capabilities that make software easier and safer to deploy and operate. Develop automated workflows for data processing, operational tasks and engineering processes using technologies such as Apache Airflow. Partner with traders, quantitative researchers and operations teams to understand their needs and solve practical business problems. Design software for latency-sensitive environments, balancing performance with reliability, scalability and operational simplicity. Build observable and resilient systems with appropriate monitoring, alerting, recovery and failure-handling capabilities. Work alongside infrastructure, cloud and DevOps engineers to deploy and support software across global production environments. Contribute to technical design and architectural decisions, evaluating new technologies where they can deliver meaningful value. Take ownership of software throughout its lifecycle, from initial design and implementation through to production support and continuous improvement. Your present skillset At least five years of experience developing and supporting production-grade software. Strong programming and software engineering skills in one or more languages such as Python, Java, Go, Node.js or C++. Experience designing maintainable, testable and scalable applications and services. A strong understanding of software design principles, data structures, algorithms and engineering fundamentals. Experience building RESTful APIs, distributed systems or event-driven architectures. Exposure to containerisation, orchestration and delivery technologies such as Docker, Kubernetes and CI/CD pipelines. Experience with public cloud technologies, preferably AWS. An understanding of messaging technologies such as Kafka or RabbitMQ. Experience considering reliability, observability, performance and failure recovery when designing production systems. Strong analytical and problem-solving skills, with the ability to make sound engineering decisions and explain the associated trade-offs. The ability to work effectively with both technical and non-technical stakeholders. QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees to achieve a healthy work-life balance.

- Evolve the Medusa-based commerce backend: custom modules, data models, module links, API routes, workflows. - Extend Medusa Admin with widgets and custom routes.

Location: Remote - EMEA Workplace: Remote ABOUT US Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we’ve built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We’re passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We’re a passionate team who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. ABOUT THE TEAM The Retail Media team is building a platform for connecting ecommerce retailers and brands. In a nutshell, retail media is the product that allows a brand to buy a placement within our customer’s search, browse, recommendations, collections, or quizzes results. A comprehensive retail media platform integrates seamlessly with online retailers, offering advanced targeting, bidding, and analytics capabilities. This platform aims to enhance ad visibility, optimize ad placement, and provide robust performance analytics. We're a passionate team of cross-functional engineers who love challenges and want to make people’s lives better. We value openness, curiosity, continuous improvement, and great code. We believe that empowering everyone in a company to do what they think is best can lead to great things. The Retail Media team is new and looking for Senior engineers who will help us build backend services, integrate with data warehouse and other services managing results order, and more. ABOUT THE JOB The primary focus of this job is to design, deliver & maintain web services in close collaboration with other engineers. - Build / deploy / support services using Python and FastAPI - Write AWS CloudFormation scripts, Jenkins jobs, Github actions following best industry standards - Set up service observability, monitoring metrics, and alerting (Prometheus, Grafana, PagerDuty, AWS CloudWatch) - Implement CI/CD pipelines and separate stability testing - Collaborate with technical and non-technical business partners to develop / update functionalities - Communicate with stakeholders within and outside the team REQUIREMENTS - Strong computer science background & familiarity with networking principles. - Experience in designing, developing & maintaining highload real-time services. - Proficiency in Infrastructure as Code (IaC) tools like CloudFormation or Terraform for managing cloud resources. - Hands-on experience with setting up and improving CI/CD pipelines. - Proficiency in Python. - Experience in server-side coding for web services, and a good understanding of API design principles. - Skilled in setting up and managing observability tools like Prometheus, Grafana, and integrating alert systems like PagerDuty. - Familiarity with Service-Oriented Architecture, knowledge of communication protocols like protobuf. - Experience with NoSQL and relational databases, distributed systems, and caching solutions (MySQL/PostgreSQL, ClickHouse/Athena). - Experience with any of the major public cloud service providers: AWS, Azure, GCP. - Experience collaborating in cross-functional teams. - Excellent English communication skills. - Ideal candidate has previous experience building ad tech solutions. - We're looking for someone who can overlap with 11:00–16:00 UTC — to keep collaboration smooth across time zones. BENEFITS - 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year - 🌎 Fully remote team - choose where you live - 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office - 💻 Apple laptops provided for new employees - 🧑‍🎓 Training and development budget for every employee, refreshed each year - 👪 Maternity & Paternity leave for qualified employees - 🧠 Work with smart people who will help you grow and make a meaningful impact - 💵 Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results - 📈 Stock options - offered in addition to the base salary - 🎉 Regular team offsites to connect and collaborate DIVERSITY, EQUITY, AND INCLUSION AT CONSTRUCTOR At Constructor.io http://Constructor.io we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group. Studies have shown that women and people of color may be less likely to apply for jobs unless they meet every one of the qualifications listed. Our primary interest is in finding the best candidate for the job. We encourage you to apply even if you don’t meet all of our listed qualifications. How we handle your data. By submitting this application, you acknowledge that Constructor will collect and process the personal data you provide for the purpose of evaluating your candidacy for this role. If you are not selected, we will retain your data for a limited period as described in our Recruitment Privacy Notice https://constructor.com/recruitment-privacy-notice. After that period your data will be deleted or anonymized.

Responsibilities: — Work as a Senior QA Java Engineer using Java, AWS, JUnit 5, and Karate. — Handle backend services including APIs, databases, and distributed services. — Construct test environments using CI/CD and Spring Boot. — Participate in Agile/Scrum development processes using collaboration tools such as AZDO and Teams. Requirements: — Must reside outside Russia and Belarus. — Bachelor’s degree is mandatory. — At least 8 years of experience in both automation and manual testing methodologies. — Strong skills in backend services including APIs and databases. — Familiarity with Linux and database operations involving MySQL and PostgreSQL. — Programming experience in Java. — Proficiency in Russian and English languages. Conditions: — Remote work with a B2C contract. — Full-time, 8 hours per day with 4 hours daily overlap with the core team (8 a.m. to 12 p.m. UTC-5). — Minimum contract duration is 9 months. — Vacation is unpaid.

Задачи: — архитектурное проектирование решений с опытом от 3 лет. — понимание принципов разработки ПО, паттернов проектирования, микросервисных и серверлесс-архитектур. — документирование архитектурных решений и интеграционных схем с использованием UML и BPMN. — интеграция с внешними сервисами и проектирование API (REST, gRPC, GraphQL). — работа с облачными платформами AWS, Azure, GCP и CI/CD. Требования: — опыт архитектурного проектирования не менее 3 лет. — знание UML, BPMN. — навыки проектирования API и интеграции с внешними сервисами. — опыт работы с облачными платформами и CI/CD. Условия: — удалённая работа. — фулл тайм занятость. В отклике необходимо указать ID вакансии, ФИО, локацию, возраст, занятость, формат работы, стек, опыт, резюме и сверку с требованиями.

О компании FANzino — B2B-провайдер игр нового формата в мире онлайн-гемблинга. Задачи: — Проектирование, внедрение и поддержка CI/CD пайплайнов с использованием GitLab CI/CD. — Развертывание, администрирование и масштабирование приложений в Kubernetes (K8s). — Управление доступами и развертывание систем Jira, Confluence. — Управление и оптимизация инфраструктуры на базе AWS (EC2, S3, RDS, VPC, IAM, EKS и др.). — Управление DNS. — Администрирование и глубокое понимание операционных систем Linux. — Настройка, мониторинг и обеспечение отказоустойчивости кластеров Kafka и NATS. — Управление и поддержка кластеров баз данных (PostgreSQL, MySQL, Clickhouse) включая репликацию, бэкапирование и восстановление. — Внедрение и поддержка систем мониторинга, логирования и оповещения (Prometheus, Grafana, ELK Stack). — Внедрение и проектирование PKI и SSH инфраструктуры управления доступами. — Обеспечение безопасности инфраструктуры и приложений. — Менторство и передача знаний младшим членам команды. — Поиск и устранение неисправностей, оптимизация производительности систем. Требования: — Опыт работы на позиции DevOps Engineer от 5 лет. — Экспертные знания Kubernetes: опыт развертывания, управления, масштабирования и траблшутинга кластеров. — Понимание архитектуры K8s. — Глубокие знания Linux: администрирование, сетями, файловыми системами. — Опыт работы с GitLab CI/CD: создание и поддержка сложных пайплайнов, интеграция с различными инструментами. — Практический опыт с Apache Kafka: установка, настройка, мониторинг, оптимизация производительности и обеспечение отказоустойчивости кластеров. — Уверенный опыт работы с AWS: проектирование и управление инфраструктурой, знание основных сервисов (EC2, S3, RDS, VPC, IAM, Route 53, CloudWatch, EKS). — Опыт администрирования кластеров баз данных: знание принципов репликации, резервного копирования, восстановления, мониторинга производительности. — Опыт работы с системами управления конфигурациями Ansible и инструментами Infrastructure as Code - Terraform. — Работа с предоставлением доступов через SSH, PKI. — Опыт работы с системами мониторинга и логирования (Prometheus, Grafana, ELK Stack, Zabbix). — Понимание принципов сетевой безопасности и опыт применения лучших практик. Будет плюсом: — Наличие сертификаций AWS (например, AWS Certified DevOps Engineer - Professional). — Сертификации Kubernetes (CKA, CKAD). — Опыт работы с другими облачными провайдерами (Azure, GCP). — Знание других брокеров сообщений (RabbitMQ, Redis Streams). — Опыт работы с сервис-мешами (Istio, Linkerd). Личные качества: — Сильные аналитические и навыки решения проблем. — Отличные коммуникативные навыки. — Умение работать в команде и самостоятельно. — Проактивность и желание развиваться в новых технологиях. — Ответственность и внимание к деталям. Условия: — Работа из офиса: офис на Кипре (Лимассол). — Гибкое начало рабочего дня. — Компенсация питания в офисе. — Официальное оформление по ТК Кипра. — 4 дополнительных day off. — Отсутствие легаси.

Задачи: — Отвечать за техническое направление, сроки поставки и развитие команды из 3 разработчиков и 3 QA-инженеров. — Работать в паре с Product Owner продукта IB360. — Отчитываться EVP of Product Management. — Проводить 1:1, перформанс-ревью и карьерные разговоры с командой. — Формировать технический роадмап домена вместе с продуктом. — Участвовать в код-ревью, тестировании, CI/CD, управлении инцидентами и поддержании архитектурных стандартов. — Планировать спринты, проводить груминг бэклога, триаж багов, анализировать метрики и velocity. — Мониторить здоровье системы, участвовать в on-call и SLA вместе с сервис-партнерами. Требования: — Опыт разработки не менее 6 лет, из них минимум 2 года в управлении инженерной командой. — Практический опыт работы с одним или несколькими языками: Python, Java, C#, .NET. — Знание платформ Android, Windows и Linux, а также MySQL и gRPC. — Навыки построения и поддержки CI/CD, написания unit- и интеграционных тестов. — Опыт работы с облачными платформами AWS или Azure, микросервисной и event-driven архитектурой. — Опыт найма, развития и удержания сильных инженеров. — Владение Agile и опыт работы в сложных проектах с быстрым темпом. — Опыт международной разработки и работы между часовыми поясами. — Уверенное владение английским языком для объяснения технических вопросов нетехническим стейкхолдерам. Будет плюсом: — Высшее образование в области Computer Science или Software Engineering. — Опыт работы с распределёнными системами под высокую нагрузку и большие объёмы данных. — Знания в области data engineering и platform engineering. — Опыт внедрения новых технологий, процессов или структуры команды. — Участие в open source проектах или технических сообществах. Условия: — Гибридный формат работы с офисом в центре Белграда. — Контракт и полная занятость. — 25 дней отпуска в году, включая праздники и больничные. — Ежемесячная медицинская выплата. — Подписка на AI-ассистента для кода. — Вся коммуникация ведётся на английском языке. Оплата: $4 500–5 500 в месяц. География работы: Белград, гибридный формат.

Workplace: remote Location : San Francisco Bay Area, CA, USA Work Model: Hybrid (2–3 days per week onsite) What we expect : Pharma/Biotech R&D application experience Strong Python development experience in scientific computing or data-intensive applications Hands-on Scientific Computing and HPC experience, including Slurm, shared filesystems, and batch processing Strong Linux, shell scripting, scientific package and environment management skills Experience developing and troubleshooting scientific data processing and analysis pipelines AWS Cloud experience and Docker REST APIs, microservices, and Python backend frameworks (Django/FastAPI or similar) SQL and relational databases Experience with AI-assisted software development tools Strong communication skills and ability to work directly with scientists to understand scientific workflows and resolve technical issues Nice to have : Bioinformatics or computational biology experience GPU workloads and scientific workload optimization Spark and distributed data processing OpenEye/FastROCS or other scientific computing toolkits We offer : Competitive compensation Remote or office work Flexible working hours Continuous education, mentoring, and professional development programs A team with excellent tech expertise

Workplace: remote Location : San Francisco Bay Area, CA, USA Work Model: Hybrid (2–3 days per week onsite) What we expect : Strong TypeScript/JavaScript and Angular or React experience Java/Spring Boot backend development experience REST APIs, microservices, and third-party integrations SQL and relational databases AWS Cloud experience Experience maintaining and enhancing data-intensive web applications, including scientific or analytical visualizations Strong production troubleshooting and debugging skills Experience with AI-assisted software development tools Strong communication skills and ability to work directly with scientists to understand workflows and resolve issues Availability to work in the Pacific Time Zone Nice to have : Vue.js, D3.js Spotfire or other scientific visualization platforms Pharma/Biotech R&D or scientific application experience We offer : Competitive compensation Remote or office work Flexible working hours Continuous education, mentoring, and professional development programs A team with excellent tech expertise

Responsibilities: — Work on Document AI tasks including parsing complex documents and scans — Develop Computer Vision solutions for recognizing floor plans and technical drawings Requirements: — Hands-on experience with Document AI — Hands-on experience with Computer Vision Benefits: — Remote work with 6-hour overlap required with Canada — Full-time position on a long-term project — Immediate start Tech stack includes Python, PyMuPDF, OCR technologies (AWS Textract / Tesseract), Structured LLM Output, OpenCV, Shapely (geometry/polygons), and SVG generation.

Location: Poland; Romania; Bulgaria; Serbia Workplace: Remote We are B2Spin, and we are dedicated to delivering the best Free-to-Play Social Casino and gaming experiences by creating captivating, engaging, and unique products that are accessible to everyone. We have built a team of talented professionals from all over the globe, who are working to continually improve the experiences of our players. We are not looking to just be part of the industry, but to revolutionize it. The role B2Spin is looking for a Data Science Manager to lead and grow our data science team across product, marketing, performance, and beyond. Reporting to the Head of Data, you'll set the quality bar for modelling and experimentation, translate business needs into clear team priorities, and act as the connective tissue between data scientists and the stakeholders who depend on their work. This is a role for someone who is genuinely hands-on, cares deeply about craft, and knows how to bring out the best in the people around them. What you'll do - Own the team's output across verticals — partner with the Head of Data to shape and prioritise the roadmap so data science work stays tightly aligned with business goals. - Bridge data science and the business — translate stakeholder needs into team priorities, manage expectations proactively, and communicate trade-offs and results in terms that land with non-technical audiences. - Raise and hold the quality bar — review modelling approaches, experimental design, and causal inference work, and step in directly to pair, deliver, or course-correct when coverage or quality demands it. - Hire, coach, and grow data scientists — run the hiring loop, lead 1:1s, and partner with the Head of Data on performance, compensation, and career development. - Drive rigorous experimentation — champion sound A/B testing, quasi-experimental methods, and causal thinking across both product and performance tracks. What we're looking for - A hands-on data science background with a track record of delivering models, experiments, or analyses that other teams actually used — not just built. - Demonstrated depth in at least one domain: Recommendation Systems, - - Experimental Design and Causal Inference, Customer Segmentation, Churn Prediction, Fraud/Anomaly Detection, or CRM analytics — product-focused experience particularly valued. - Strong command of statistical methods, supervised and unsupervised machine learning, and causal inference, sufficient to review and credibly challenge work across both tracks. - Evidence of leading others — as a tech lead, mentor, or hiring interviewer; prior formal people-management experience is a plus. - Proficiency in Python and SQL. - The communication range to give precise technical feedback to data scientists and represent the team clearly to senior non-technical stakeholders. - Familiarity with cloud-based data and ML platforms (AWS, GCP, or Azure) is a nice-to-have. Our values At B2Spin, passion drives everything — we love building cool stuff and want teammates who feel the same way. We operate on performance: accountability, transparency, and a bias for progress over perfection. If that sounds like your kind of environment, we'd love to hear from you. Equal opportunities We hire based on skills, drive, and ideas — nothing else. Your background, gender, age, race, ethnicity, disability, sexual orientation, religion, neurodiversity, or educational path will never be a barrier to joining us. We also welcome candidates from non-traditional career journeys and value diverse perspectives that challenge conventional thinking. Diversity fuels our innovation, collaboration, and growth, and we're committed to creating an environment where everyone can contribute their best work and thrive.

Задачи: — проектирование и развитие безопасности multi-cloud инфраструктуры на базе AWS и Azure — управление IAM/PAM и Hybrid Identity — обеспечение безопасности сетевого периметра — работа с SIEM, EDR и реагирование на инциденты — автоматизация security-контролей, включая Terraform, CI/CD Security, Kubernetes Security, Policy-as-Code Требования: — опыт работы 6+ лет в Infrastructure / Cloud / Security Engineering, из них 3+ года с фокусом на Security — сильный production-опыт с AWS и Azure, проектирование multi-cloud инфраструктуры — глубокие знания Active Directory, IAM/PAM, Hybrid Identity — практический опыт с SIEM, EDR и Incident Response — опыт работы с Terraform, CI/CD Security, Kubernetes Security, Policy-as-Code — опыт работы в регулируемой финансовой индустрии — опыт обеспечения безопасности crypto-инфраструктуры: wallets, HSM/MPC, crypto exchanges или crypto payments — дополнительные знания: ISO 27001, SOC 2, DORA, API Security, Threat Modeling Условия: — география: Кипр или Дубай (ОАЭ), рассматриваются кандидаты, готовые к релокации — формат работы: гибридный, 3 дня в неделю в офисе — язык общения: русский — компенсация обсуждается индивидуально, ориентир на ожидания кандидата — отсутствует time tracking

Location: Paris, Remote Workplace: remote Our Security and IT team keeps the 360Learning platform secure, compliant and auditable for the 1,500 organisations that learn on it every day. As a Senior DevSecOps Engineer, your mission is to make our infrastructure secure by design, detectable by default, and provable at audit time. 360Learning runs its learning platform on Azure and Kubernetes, certified ISO 27001:2022 and SOC 2 Type II. Over the past two years the technical security workload has grown on every front: a larger and more regulated customer base sending their own scans and security assessments, a wider detection and response scope, more infrastructure to keep hardened and auditable, and a growing backlog of security engineering projects that never reach the top of the queue. We are creating this position to add real technical capacity on the infrastructure side of security, and to move part of our security posture from manual effort to automated guardrails. You will be the bridge between security and platform engineering: deep enough in infrastructure to fix things yourself, and close enough to security operations to know what to look for. “Ours is a small, senior team with a broad scope: information security, compliance, infrastructure governance and internal tooling, with dual audit accountability on ISO 27001:2022 and SOC 2 Type II. That means direct impact and no layers between you and the decision. Roughly half of this role is greenfield build work you will own end to end.” Guillaume Seigneuret, CISO and Hiring Coach. Within 1 month, you will: Complete our onboarding and learn how we work through our own platform and our Convexity culture Map our Azure and AKS environment, our detection and logging coverage, and our ISO 27001 and SOC 2 control scope with the CISO and the Security Engineer Meet the DevOps, platform engineering and IT teams you will work with daily Shadow alert triage and one customer security assessment end to end Within 3 months, you will: Be autonomous on our AKS and Azure environment and handle infrastructure related alerts end to end Have shipped at least one concrete hardening or automation improvement in production Own the infrastructure scope of vulnerability management, from triage to remediation follow up Within 6 months, you will: Have the honeypot live and producing high fidelity alerts Have measurably widened SIEM connector coverage, with documented log sources and retention Run infrastructure vulnerability remediation on a predictable cycle with SLA reporting Within 12 months, you will: Manage detection content as code, with reviewed and tested rules and documented runbooks Have largely automated audit evidence on the infrastructure scope Have eliminated long lived credentials on the critical paths, so engineering teams ship on secure defaults they did not have to think about The Skill Set: 5+ years in infrastructure, cloud or platform engineering with a strong security focus, or in security engineering with hands on infrastructure practice Production experience with Kubernetes: RBAC, network policies, admission controllers, secrets handling, workload identity, runtime security Solid cloud experience, ideally Azure. Strong AWS or Google Cloud experience with a genuine interest in converting works too Infrastructure as code: Terraform, GitOps workflows, CI/CD pipelines Scripting and automation: Python or Go, plus shell. Comfortable reading and writing code, and opening pull requests on repositories owned by other teams Log analysis and investigation: cloud audit logs, query languages, correlation across identity, network and application sources Fluent English (US/UK) / B2 level or equivalent (FR). Enthusiasm for our working environment explained here: https://bit.ly/Convexity360L What we offer: Compensation: Package includes base salary, a variable component and equity 📈 Benefits/Perks : Work From Home stipend, RTT, lunch vouchers, medical insurance, gym subscription, 1 month parental leave for the second parent. Balance: Flexible hours, full remote work possible anywhere in France 🏠 Diversity, Equity, and Inclusion : We have 6 active ERGs including Mental Health, Environmental/Sustainability, Women, Parents, LGBTQIA2S+, and Ethnic Diversity. Each group has at least one executive team member serving as a member of the group, bringing greater awareness to each group’s activities and providing a quick path to impact 🤝 Corporate Social Responsibility : Review our CSR Charter: 360learning.com/blog/corporate-social-responsibility-charter 🌎🌏🌍 Culture: A framework that will help you make an impact - envision our way of working and our Convexity Culture: https://bit.ly/Convexity360L & find out more about the teams, product and processes https://bit.ly/42H1ggC 🚀👩🏻‍💻🏆 Interview Process: Phone Screen with our Talent Acquisition Manager Discovery Meeting with our Head of Security Live exercise with our Head of Security and our Head of Devops: investigation of an incident scenario, or review of an insecure infrastructure configuration Clarification Meeting with the Security Engineer and a DevOps engineer Culture Fit Meeting with our VP of Engineering Offer! Who We Are 360Learning enables companies to upskill from within by turning their experts into champions for employee, customer, and partner growth. With our LMS for collaborative learning, Learning & Development teams can accelerate upskilling with the help of internal experts instead of slow top-down training. 360Learning is the easiest way to onboard and upskill employees, train customer-facing teams, and enable customers and partners–all from one place. 360Learning powers the future of work at 1,700 organizations. Founded in 2013, 360Learning has raised $240 million with 400+ team members across North America and EMEA. Learning Includes Everyone. In concert with our culture, 360Learning believes learning includes everyone and that means embracing the strengths of diversity, connectedness, and inclusion. Through conscientious efforts, our global footprint celebrates cultures, perspectives, and experiences from all over the world to support our platform that is built for all regardless of race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. Thus, 360Learning is proud to be an equal opportunity workplace, and we commit to continue this throughout our processes for recruitment, compensation, benefits, performance, promotion, and all other conditions and terms of employment. We want to learn from and with you!

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

Responsibilities: — Design, deploy, and operate production AI infrastructure for customer workloads. Requirements: — Experience with machine learning, Kubernetes, Java, Spark, IAM, Infrastructure-as-Code, Go, Terraform, networking, distributed computing, GCP, Python, GitOps, Dask, DevOps, AWS, Helm, CI/CD, and Security. Benefits: — Salary range $250,000 - $275,000.

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

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

Responsibilities: — Work as a Senior PHP Web Developer. — Utilize PHP, MySQL, and Git in development tasks. — Knowledge of Go, React, and AWS is considered a plus. Requirements: — Experience suitable for Mid-Senior level. Benefits: — Attractive compensation package. — Fully remote work option available for candidates based in Cyprus or Greece. Note: Remote work is explicitly listed for candidates residing in Cyprus or Greece.