Вакансии

Location: United States, Madison, WI Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. At PlayStation, we're passionate about both partnership and technology. We care about building performant products and powerful tools, solving practical problems in delightful ways. We love building the systems that millions of people use, and we're always our own first customers and critics. We strive to be at the forefront of development technologies and celebrate our diversity with engineering teams located on four continents from all walks of life. We build our teams to be places where every voice is heard, all input is valued, and our members have the creative freedom to make their ideas real. Sr Software Development Engineer in Test , ML Locations: Madison, WI and Waterloo, Ontario Canada P layStation is seeking a Sr Software Development Engineer in Test, ML to join our Madison team and lead quality efforts for machine learning-powered products and services. You will partner closely with ML engineers, software engineers, product managers, and data partners to build scalable test automation and validation approaches for systems serving PlayStation at global scale. This role is focused on building confidence in model reliability, production readiness, and behavioral consistency. Unlike traditional software backend testing, success here requires validating probabilistic systems through score distributions, cohort-level behavior, thresholds, and statistical signals, not just deterministic pass/fail assertions. Responsibilities: Drive architecture-level automation solutions and scalable quality engineering practices across multiple teams and product areas. Design, develop, and maintain automated test frameworks, test scripts for ML inference services and related ML platform components using python/Java Build and automate realistic, representative test account creations and datasets to evaluate model behavior across different scenarios Validate score distributions, ranking behavior, output quality, and other model signals for incoming ML models prior to release Perform different types of testing, including functional, integration, regression and API testing working with RESTful APIs, microservices and databases, and non-functional performance and load testing to verify inference service scalability, latency requirements and reliability under production like conditions Work closely with ML engineers and ops teams to ensure that all features and bug fixes come with automated test coverage, ensuring continuous integration and deployment Debug and analyze test failures, model anomalies and report defects Drive high standards of quality for both engineering decisions and customer-facing features with optimal test and automation strategy Develop and implement best practices for test automation that is highly scalable and maintainable Monitor test execution and optimize performance in test environments Come up with innovative solutions to organizational problems Required Qualifications: A Bachelor's degree in Computer Science or related field Minimum 5 years of experience as an SDET, with strong experience testing backend systems. Proficiency in Python/Java/Scala/go for test automation. Hands-on experience with API testing tools (e.g., Postman or similar) for distributed systems Familiarity with CI/CD pipelines and test execution in Jenkins or similar environments such as jenkins, GitHub Actions, ArgoCD, etc Hands-on experience building and maintaining automated test frameworks (e.g., pytest, JUnit, TestNG, etc.)Experience in working with databases  for backend validation. Experience with cloud and container technologies (AWS, GCP, Kubernetes, Docker, etc.) Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Datadog, etc.) for validating service health Strong understanding of software development lifecycle (SDLC) and agile methodologies. Excellent problem-solving skills and excellent communication skills. Preferred Qualifications: Experience testing machine learning systems, such as recommendation systems, search ranking systems, or other probabilistic ML application systems. Experience creating synthetic or seeded test data to simulate realistic customer/account behaviors. Experience evaluating model outputs using statistical techniques, distribution analysis, or scenario-based validation, rather than deterministic assertions. Knowledge of data pipelines, feature stores, inference systems or model-serving infrastructure (Seldon, KServe, Ray Serve, etc.) is a plus. Experience with performance and load testing tools Experience with Databricks or similar ML platform tooling Experience architecting and optimizing CI/CD pipelines, quality gates, and release validation systems using Jenkins or similar platforms. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $152,000 — $190,000 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

🔹Опыт работы в области тестирования программного обеспечения минимум 2 года.

Workplace: Москва и Краснодар (гибрид/офис), другие города - удаленно Привет! Мы ищем QA Mobile Fullstack в команду развития сервисов НКЗ и качества продовольственных товаров. Продукт, который мы развиваем: мобильное приложение приемки товаров на распределительных центрах. Соотношение ручного тестирования к автотестам: ~50/50. Стек технологий: PostgreSQL, REST API, Postman, Docker, Kafka, RabbitMQ, TestIt, Jira, Confluence, Android Studio, Charles/Proxyman, Pytest + Appium (UiAutomator2). Локация: Москва, Краснодар - гибрид, регионы - удаленная работа по РФ. Задачи Работать с DevTools (Elements, Console, Network, Application). Использовать Charles Proxy / Proxyman для сниффинга трафика Тестировать REST API с помощью Postman и Swagger и интеграции через Kafka UI / RabbitMQ Management / Offset Explorer Просматривать и анализировать серверные логи в Kibana / OpenSearch и т.д. Писать SQL-запросов средней сложности (СУБД - PostgreSQL, отправка запросов через DBeaver) Тестировать мобильное приложение на эмуляторах (Android Studio) и реальных устройствах Покрывать автотестами новый функционал (Pytest + Appium (UiAutomator2) Требования Коммерческий опыт тестирования ПО от 4 лет и опыт автоматизации тестирования от 2 лет (Appium (UiAutomator2)) Понимание жизненного цикла разработки ПО (SDLC) и процессов тестирования Работа в Agile/Scrum/Kanban-командах Навыки чтения и анализа технической документации, логов, DTO Способность создавать и поддерживать тестовую документацию (тест-кейсы, чек-листы, баг-репорты) Опыт тестирования веб- и мобильных приложений (Android) Будет плюсом Практика тестирования high-load систем Навыки нагрузочного тестирования Работа с Docker Знание CI/CD Условия Трудоустройство в аккредитованную IT‑компанию ДМС со стоматологией и льготными условиями для членов семьи Работу в уютном офисе в центре Москвы (ст. м. Савеловская) Корпоративные скидки PRIMEZONE, бесплатная подписка Магнит Премиум с повышенным кешбэком по программе лояльности М+ Поддержку в развитии через обучение, конференции и митапы, а также программу для руководителей - Leadership club IT‑комьюнити - среда, где быстрее находишь решения, делишься практиками, пробуешь новые роли и растешь от эксперта в стекe до лидера инициатив Мы являемся партнером Минцифры России по проекту Национальная система подтверждения IT‑компетенций Работа над масштабными продуктами и проектами (Умный магазин, роботизация, беспилотность, GenAI и другое) Социально– психологическая поддержка от >370 специалистов по направлениям: юристы, психологи, врачи, финансовые и ЗОЖ советники Формат работы Москва и Краснодар (гибрид/офис), другие города - удаленно

Location: London, UK We are looking for a Senior Python Engineer who writes production code every day. You will build new components and refactor business-built tools into well-engineered applications. You will work directly with portfolio managers to understand how the tools are used and what must not break. This is a 100% hands-on role, not an advisory or architectural role. This is a hybrid position requiring onsite presence at the client’s London office three days per week. Duration: 12+ months Design, develop, and maintain production-grade Python applications and APIs. Refactor and modernize Python/Excel tools built by business teams by adding tests, structure, security, and observability. Work directly with portfolio managers and front-office users to clarify requirements and validate results. Build data-intensive and analytics features using SQL and cloud data platforms. Contribute to CI/CD, automated testing, and code reviews. Apply AI-assisted development practices where they improve speed and quality. 5+ years of hands-on experience in production Python development. Python is the main language in your current role. ETF or investment front-office experience (asset management, investment banking, or capital markets). At a minimum, you have worked directly with portfolio managers or traders. Experience modernizing legacy or business-built applications. Strong SQL skills and experience with cloud platforms (AWS preferred). Experience with API design and integration, automated testing, CI/CD, and Git. Ability to gather requirements directly from business users and communicate clearly with non-technical stakeholders. Ability and willingness to work on-site at the client’s London office three days per week. Experience with fixed-income ETFs, portfolio management, or investment analytics. Experience with Aladdin, BNY, or comparable investment platforms. Experience with Snowflake, Redshift, Databricks, or BigQuery. Experience with AI-enabled development, agentic workflows, or AI-assisted SDLC.

Location: Intellias Meet your recruiter Diana Meneses diana.meneses@intellias.com https://www.linkedin.com... Vacancy details Test Engineering Automation Test Engineer (Python) Senior United States Office APPLY NOW REFER A FRIEND We are looking for a QA Engineer to support validation and quality assurance activities for an IVI software platform. The engineer will work closely with development, systems, requirements, and integration teams to ensure software quality throughout the software development lifecycle. The role includes test planning and execution, requirements traceability, defect management, and verification of infotainment features across software and hardware environments. This includes hands-on testing on test benches, HIL/Labcar systems, integration rigs, and target hardware, ensuring that IVI functionality meets quality, performance, and reliability requirements while aligning with automotive development processes and standards. What project we have for you Join a team developing and validating a next-generation In-Vehicle Infotainment (IVI) platform for a leading automotive OEM. The project focuses on connected vehicle services, multimedia, navigation, and user experience features. You will support software validation across cloud, bench, Labcar, and target hardware environments, ensuring high quality, reliability, and compliance with automotive development standards. What you will do Review and analyze software requirements, user stories, and acceptance criteria. Develop and maintain test plans, test cases, and test execution reports. Execute functional, integration, regression, and end-to-end testing activities. Verify traceability between requirements, test cases, and defects. Identify, document, and track software defects through resolution. Collaborate with developers, product owners, and systems engineers to ensure product quality. Support release validation and software verification activities. Participate in Agile ceremonies and quality planning sessions. Contribute to continuous improvement of QA processes, tools, and methodologies. Support compliance with automotive software development standards and processes. What you need for this 8+ years of experience in Software Quality Assurance or Software Testing. Experience in automotive software, infotainment, HMI, connected vehicle, Android Automotive, or embedded systems projects. Strong understanding of Software Development Life Cycle (SDLC) and Agile methodologies. Hands-on experience in creating and executing test cases, test plans, and test reports. Experience with API, integration, and system-level testing. Knowledge of requirements management and traceability practices. Experience with requirements management tools such as Codebeamer or similar. Experience with cloud platforms, preferably AWS, and validation of cloud-based applications and services. Experience with test automation frameworks and scripting, such as Python, Selenium, Robot Framework, Appium, Playwright, or similar tools. Familiarity with CI/CD pipelines and tools such as GitHub Actions, or GitLab CI. Strong analytical, troubleshooting, and communication skills. Bachelor’s degree in Computer Science, Engineering, or a related field. Preferred Qualifications Experience supporting software releases in large-scale automotive programs. Knowledge of ISO 26262 and functional safety concepts. Experience working in distributed, cross-functional global teams. ISTQB certification or equivalent. Working knowledge of ASPICE and automotive software development processes. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Android Automotive Python Selenium

Location: Intellias Meet your recruiter Sara Abdelaziz Sherif sara.abdelaziz@intellias.com https://www.linkedin.com... Vacancy details Test Engineering Manual Test Engineer Strong Middle Cairo, Egypt Remote APPLY NOW REFER A FRIEND Drivers of change, it’s your time to pave new ways. Intellias, a leading software provider in the automotive industry, invites you to develop the future of driving. Join the team and create products used by 2 billion people in the world. What project we have for you We are looking for a skilled Manual Test Engineer with a clear understanding of SDLC and testing theory. Seasoned in testing practice with good investigation skills to join our team in its work on automotive project on-site. What you will do Performing software updates to the test cars or test benches. Taking part of daily/evening testing iterations on test benches. Performing weekend static or dynamic test drives by additional customer requests. Executing test plans/test suites based on priorities provided by Test Manager/Test Lead. Recording traces and providing proper time markers for defect analysis. Converting and cutting logs based on markers and adding them to the defect reports. Creating defect reports directly after a test drives/runs in internal or customer defect management system. Producing Test Reports/Test Summary Reports after test drives/runs. Creating or extending Test cases/suites/plans for testing needs. Supporting the engineering team by testing dev-drops. Providing immediate feedback or rectifications to the Tickets Coordinator, FO, Program Lead, Project Lead, etc requests. Collaborating with a car manufacturer or IVI system development team. What you need for this At least 4 years of experience as a Test Engineer Automotive experience of at least 3 years Proven proficiency in the creation of test reports and defects Solid experience in Test case creation Understanding of SDLC and testing theory Very good communication skills in English Nice to have: Flexibility in working schedule. Shifted working hours are expected. Begin after 14:00 What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Automotive Driving Testing

Задачи: — Внедрение и развитие практик agent-engineering в разработке программного обеспечения. — Участие в реальных задачах разработки, построение и развитие агентского слоя, подготовка agent harness. — Внедрение SDD и других подходов AI-assisted SDLC. — Помощь командам эффективно и безопасно использовать код-агентов. — Формирование внутренних стандартов и лучших практик. — Превращение AI-кодинга в управляемый производственный процесс с использованием спецификаций, контекста, тестов, ревью, observability, permissions и качественного результата. — Формирование целевой архитектуры на основе бизнес-требований и существующих систем. — Выбор технологий, границ компонентов и интеграционных подходов. — Оценка нефункциональных требований: масштабируемость, надёжность, безопасность, стоимость. — Подготовка артефактов: схемы, ADR, интеграционные контракты. — Согласование решений с командными и предметными архитекторами и стейкхолдерами. — Сопровождение команд при реализации. — Участие во всех этапах AI SDLC: от требований и декомпозиции до реализации, тестирования, ревью и релиза. — Разработка и сопровождение задач с использованием AI-код-агентов. — Подготовка agent-ready спецификаций, task breakdown, acceptance criteria и context packs. — Построение и развитие agent harness: инструкции, шаблоны, инструменты, MCP-интеграции, тестовые контуры, evals, observability. — Внедрение SDD, TDD/BDD и других подходов к AI-assisted разработке. — Настройка безопасного контура работы агентов: sandbox, permissions, approval gates, audit trail. — Развитие code-RAG / context engineering по внутренним репозиториям и документации. — Помощь командам во внедрении AI-assisted workflows в реальные процессы. — Проведение воркшопов, менторинг разработчиков, подготовка внутренних инструкций. — Оценка новых AI coding tools, моделей и агентских фреймворков. — Измерение эффекта внедрения и улучшение практик на основе данных. Требования: — Опыт разработки не менее 5 лет, из них 2–3 года в архитектуре распределённых систем. — Глубокие знания микросервисов, интеграций (REST, Kafka, ESB), баз данных и облачных платформ. — Владение методами моделирования архитектуры: C4, UML, ArchiMate. — Понимание вопросов безопасности, отказоустойчивости, планирования ёмкости и оценки стоимости. — Знание корпоративных стандартов, EAM-ландшафта и предметной области. — Навыки коммуникации и ведения переговоров, умение обосновывать решения для бизнеса и разработки. Условия: — Удалённая работа в формате fulltime. — Зарплата до 376 000 рублей netto (ИП, самозанятый).

Location: Remote Workplace: Remote Blockstream https://blockstream.com/ was founded in 2014 by Dr. Adam Back https://en.wikipedia.org/wiki/Adam_Back and a group of fellow cryptographers and engineers who are passionate about Bitcoin and its potential to change the world. Today, Blockstream is the leading Bitcoin company, providing cutting-edge infrastructure solutions for enterprises, institutions, and individual Bitcoin users. We develop industry-leading Bitcoin self-custody solutions, Bitcoin-based financial products, second-layer scaling technologies, and enterprise-grade blockchain infrastructure. We’re looking for an experienced Security Architect to design, implement, and oversee secure systems and applications across Blockstream’s enterprise products and infrastructure. The ideal candidate is a full-stack engineer with a strong backend focus, deep understanding of secure application design, and prior experience building or securing platforms in fintech, banking, or blockchain. You’ll partner closely with product, DevOps, and engineering teams to ensure Blockstream’s systems and data are protected from evolving threats — without compromising innovation or performance. What You’ll Be Doing (Responsibilities): - Define and drive security architecture across applications, services, and infrastructure. - Partner with engineering teams to design and implement secure software systems, focusing on backend and data security. - Conduct threat modeling, risk assessments, and security reviews for new and existing products. - Develop and enforce secure coding practices, frameworks, and review processes. - Collaborate with DevOps on cloud and container security, CI/CD hardening, and access controls. - Evaluate and integrate security tools for code scanning, vulnerability management, and incident response. - Guide and mentor engineers on best practices for secure application development. - Stay ahead of emerging security trends, compliance standards, and attack vectors — particularly in fintech and blockchain domains. What We Look For in You (Required Qualifications): - 10+ years of experience in software engineering or security architecture roles. - Strong full-stack background with deep backend security expertise (Python, Go, C/C++, Rust, or similar languages). - Demonstrated experience designing and securing systems for enterprise fintech, banking, or blockchain environments. - Knowledge of cryptography, authentication, and key management. - Hands-on experience with cloud security (AWS, GCP, or similar). - Familiarity with threat modeling, secure SDLC, and modern application security frameworks (OWASP, NIST, ISO 27001). - Excellent communication skills — able to clearly articulate risks and solutions to both technical and non-technical stakeholders. Nice To Haves (Preferred Qualifications): - Experience with Bitcoin, Lightning, or blockchain protocols. - Contributions to open-source security tools or projects. - Security certifications (CISSP, OSCP, CEH, or equivalent) are a plus but not required. 🔒 Stay Safe from Job Scams All official Blockstream communication will come from an @blockstream.com email address. We will never ask you to share sensitive information or purchase equipment during the hiring process. If in doubt, contact us at hr@blockstream.com. Learn more about avoiding job scams here https://consumer.ftc.gov/consumer-alerts/2022/05/want-work-home-spot-scams-first.

Нужен специалист по безопасности кода: развивать S-SDLC и автоматизацию статического анализа веб-приложений, проводить ручной анализ и аудит кода, искать секреты. Ещё предстоит участвовать в проектировании безопасной архитектуры, формулировать требования, консультировать разработчиков и контролировать исправление уязвимостей.

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. As an Intermediate Backend Engineer on the GitLab Orbit team, you'll help build and operate a graph data service that supports GitLab Duo agents, analytics, and architecture-level features across GitLab.com, Dedicated, and Self-Managed deployments. You'll join a Rust-first team that values clear ownership, thoughtful system design, and rigorous thinking about data and reliability. The Knowledge Graph service is a Rust backend that builds a property graph from GitLab’s software development lifecycle (SDLC) and code data. It uses ClickHouse, NATS JetStream, and the Data Insights Platform. It exposes secure graph queries and MCP tools used by AI agents and product features. In this role, you’ll deliver features and improvements in well-scoped areas, learn the broader architecture, and contribute to reliability, observability, and operational readiness. In your first year, you’ll take clear ownership of specific components or features (for example, parts of the SDLC indexing pipeline or query paths). You’ll help reduce single points of failure with better tests and runbooks, and you’ll help the team ship analytical services that are easier to maintain and evolve over time. What you’ll do Implement and iterate on backend features in the Rust-based Knowledge Graph service, including changes to the query engine, SDLC and code indexing flows, and API endpoints (including MCP endpoints) under guidance from senior and staff engineers. Maintain integrations between Knowledge Graph and the rest of the GitLab platform, working in areas that touch GitLab Rails, the Data Insights Platform (Siphon, NATS, ClickHouse), and GitLab Duo Agent Platform. Contribute to system design discussions by proposing options, raising questions, and documenting decisions, with a focus on reliability, scalability, and maintainability for analytical graph workloads. Improve the operational maturity of the service by adding or enhancing metrics, logging, runbooks, alerts, and small readiness tasks, and by participating in on-call rotation as appropriate for your level and experience. Collaborate asynchronously with product, data, infrastructure, security, and AI counterparts to clarify requirements, align on scope, and ship features safely for customers and sustainably for the team. Use AI-assisted development workflows responsibly (for example, using Knowledge Graph-backed agents and internal Duo tooling), and share what works with the team while keeping a strong focus on code quality and correctness. Participate in code reviews, knowledge-sharing sessions, and pairing to both learn from others and help maintain consistent standards across the codebase. Contribute across the stack when needed, including occasional Ruby work for Rails integration and authorization paths, or small frontend changes related to Knowledge Graph features (for example, Software Architecture Map UI plumbing). Take part in on-call or operational support where your team’s ownership model requires it. What you’ll bring Professional experience building and maintaining backend systems in production, with an understanding of reliability, maintainability, and how to support services over time (for example, incident response and follow-ups). Proficiency in at least one modern backend language and strong interest in Rust, with either prior Rust experience or clear evidence you can ramp quickly and deliver in a Rust-first, performance-sensitive codebase. Some exposure to distributed data or analytics systems (for example, OLAP databases, Kafka- or NATS-style messaging, or change data capture (CDC) pipelines), or strong motivation to develop those skills in this role. Interest in graph data modeling and query patterns (property graphs, multi-step (n-hop) traversals, aggregations), and willingness to learn the tools and concepts used in Knowledge Graph over time. Practical experience (or strong interest) using AI tools in day-to-day development, along with a thoughtful approach to validating outputs and integrating AI into your workflow. A language-agnostic mindset and evidence that you can pick up new languages and frameworks as needed (for example, Ruby, Go, or TypeScript/Vue where the work touches adjacent systems). Solid fundamentals in system design for your level, including the ability to reason about trade-offs, ask good questions, and align your implementation work with documented architectural decisions. Comfort working in a low-process, high-ownership environment where you take responsibility for your work, refine problem statements with teammates, and communicate progress clearly in writing across time zones in an all-remote team. About the team GitLab Orbit sits within the Data Engineering organization. We work closely with partners across AI (Duo Agent Platform), analytics, infrastructure and delivery, and security because our work spans many parts of the platform. We collaborate asynchronously rather than following a feature factory model. A key challenge for us right now is scaling sustainably as usage grows and team members take time off. That includes hardening multi-tenant behavior. At the same time, we're bringing Knowledge Graph to The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $115,200 — $162,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Ukraine; Spain; Slovakia; Serbia; Yerevan; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: Intellias Meet your recruiter Sushil Francis Borde sushil.borde@intellias.com https://www.linkedin.com... Vacancy details Information Security Security Engineer Senior Bulgaria, Croatia, Egypt, India, Poland, Portugal, Spain, Ukraine, United Kingdom Remote APPLY NOW REFER A FRIEND We are looking for a Security / Policy Engineer to design and implement authorization models for AI agents and cloud-native platforms. The role focuses on AWS AgentCore Policy (Cedar), policy-as-code, OAuth/JWT-based authorization, and zero-trust security architecture. The ideal candidate has hands-on experience with cloud security, identity engineering, ABAC design, and enterprise-grade access control systems. What project we have for you Our customer is a multinational corporation with more than a century of history and offices in over 180 countries. Their most ambitious goal at the time is to introduce a range of Reduced-Risk Products (RRPs). The target audience is more than 1 billion consumers around the globe. IT platform hosts 700+ applications. Intellia’s mission is to help the client with the engineering of a comprehensive software ecosystem for a game-changing IoT product on the margin of innovative consumer experience and cutting-edge technology. Our teams are involved in the engineering of core platform components for best-in-class eCommerce, Digital Marketing and IoT solutions. As an Engineer, you will become a part of Core Architecture Team and be responsible for the architecture, implementation of best practices in our Digital Engineering Enterprise Platform. The Platform is a set of services and internet applications that accelerate the development and delivery of software applications by taking care of common SDLC challenges. The Platform provides access and consumption for engineering teams to a set of services, technologies, practices for their development and for operating their application, ensuring a set of compliance and best practices. What you will do Design and implement authorization policies using Cedar and AWS AgentCore Policy. Develop and maintain policy-as-code frameworks for cloud-native and AI-agent platforms. Build and govern Attribute-Based Access Control (ABAC) models following least-privilege and default-deny principles. Integrate authorization systems with OAuth 2.0, JWT, and Microsoft Entra ID. Define and maintain principals, resources, actions, and conditional access policies. Design token validation, claims mapping, and authorization decision workflows. Implement audit logging and traceability for policy evaluation and access decisions. Partner with security, architecture, and platform teams to support enterprise security reviews and governance processes. Contribute to zero-trust security architecture and authorization strategy across distributed systems. Evaluate and adopt emerging AWS authorization technologies, including Cedar and AWS Verified Permissions. What you need for this • AWS AgentCore Policy (Cedar) • Cedar policy language (principals, actions, resources, conditions) • OAuth 2.0 / JWT / MS Entra integration • Policy-as-code patterns • Default-deny authorization models • Audit logging for policy decisions Experience: • 5+ years cloud security or identity engineering • Attribute-based access control (ABAC) design • OAuth 2.0 / JWT token inspection and claims mapping • Enterprise security review (InfoSec, ARB processes) Will be a plus: • AWS Cedar (open source) prior exposure • AWS Verified Permissions or AgentCore Policy early experience • Zero-trust architecture design What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: North Macedonia; Bosnia and Herzegovina; Czechia; Croatia; Moldova; Bulgaria; Montenegro Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: Ukraine; Serbia; Yerevan; Spain; Slovakia; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: North Macedonia; Montenegro; Moldova; Bulgaria; Czechia; Bosnia and Herzegovina; Croatia Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner , working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: New Jersey; New York; Connecticut Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems. Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive. Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented. Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket. Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack. Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name. We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name. What we look for: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits. Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses). Nice to have Containers and orchestration (Kubernetes/ECS) and CI/CD in production. IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it. Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously. You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare. Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice. What We Offer: Full-time. On-site visits to client’s facilities and our office in NYC 1/week Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. Base salary $200-250k + bonuses; OTE up to $300k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team. We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates. You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO. How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion.

• Разработка стратегии и целевой архитектуры мобильных и цифровых каналов банка. • Руководство, развитие и масштабирование команды мобильной разработки.

Location: European Union Workplace: Remote Playson is a leading online gaming supplier, founded in 2012, which has developed worldwide recognition in the industry. We offer complete gaming solutions based on the latest technologies and detailed market analysis for the leading iGaming operators. Due to the dynamic growth, we are excited to invite a Technical Support Engineer for night shifts with a relevant background to apply for the role in our Integration Department. Technical Support Engineers at Playson is responsible for a full customer support service of our current partner's integrations. To succeed in the advertised role, you have: - ready for only night shifts - Familiarity with monitoring tools (e.g., Elastic, Dynatrace, Grafana) - A proactive, client-focused attitude and strong work ethic - Strong problem-solving and troubleshooting skills - Effective communication skills, both written and verbal - At least Upper-Intermediate English (written and spoken) - Eagerness to learn quickly and grow technically - Working knowledge of XML and JSON - Basic experience with Git and version control workflows - Understanding of API protocols (e.g., REST) - Awareness of the software development lifecycle (SDLC) Would be beneficial to know: - Familiarity with the iGaming industry - Hands-on software development experience with Java, C#, Node.js, or TypeScript - Experience with cloud infrastructure (AWS, Azure, or GCP) and Kubernetes - Experience using Jira and the Atlassian stack - Basic understanding of QA processes and test environments - Previous experience in a technical support, DevOps, or site reliability role - Practical experience with monitoring systems - Exposure to Agile frameworks (Scrum or Kanban) and basic project management skills The importance of the role is in: - Understand and analyse issues, be able to find appropriate solutions - Integration protocol testing - Second-level customer support - Delivering excellent customer service with 5 shifts a week What you get in return: - Competitive Salary: We offer a competitive salary in EUR, subject to annual performance reviews - Quarterly Bonuses: Benefit from a transparent and systematic quarterly bonus system - Flexible Schedule: We offer a flexible work schedule to accommodate your needs - Remote Work Option: Choose to work remotely, providing greater flexibility and comfort - Medical Insurance: Receive comprehensive medical insurance for both you and a significant other - Financial Support for Life Events: We provide financial support during special life events - Unlimited Paid Vacation: Enjoy unlimited paid vacation leave - Unlimited Paid Sick Leave: Take unlimited paid sick leave whenever necessary - Professional Development: Get reimbursement for professional courses for your development The recruitment process looks like this: 1. HR interview (45 min) 2. Technical interview (60 min) 3. Final Interview (60 min) If the job description rings a bell - take action and apply! Looking forward to welcoming you to the iGaming world! Ambitious goals require a quick ability to manoeuvre through changes in the world. Playson is all about that. 🚀 Join us today! By submitting your application, you acknowledge that your personal data will be processed in accordance with our Privacy Policy https://playson.com/privacy.