Вакансии

Обзор позиции и стек: Компания специализируется на мобильных платежах и транзакционных сервисах. Требуется разработчик для развития бэкенд-сервисов банковского приложения с активным использованием AI-инструментов. Стек: .NET 8, ASP.NET Core, Web API, Entity Framework Core, микросервисы, REST/gRPC, RabbitMQ / Kafka, SQL, Docker. Задачи: — Разрабатывать и развивать бэкенд-сервисы банковского приложения на .NET 8; — Проектировать и реализовывать API для мобильного приложения и веба; — Активно использовать AI-инструменты для генерации кода, тестов, документации и миграций; — Работать с финансовой логикой: транзакции, лимиты, комиссии, идемпотентность операций; — Интегрировать решения с платёжными и банковскими системами; — Участвовать в проектировании архитектуры и проводить код-ревью. Требования: — Коммерческий опыт разработки на C# / .NET от 4 лет (уверенный опыт с .NET Core / .NET 6–8+); — Уверенное владение основным стеком (EF Core, микросервисы, брокеры сообщений, SQL, Docker); — AI-компетенции: ежедневная практика с Claude Code / Copilot, умение декомпозировать задачи для AI и критически ревьюить сгенерированный код (особенно в финансовой логике); — Понимание безопасности: OAuth2/OIDC, JWT, шифрование данных, OWASP Top 10; — Опыт работы с транзакционной логикой и требованиями к надёжности; — Английский язык — от B2+. Будет плюсом: — Коммерческий опыт в финтехе / банкинге / платежах; — Знание PCI DSS, ISO 8583 / ISO 20022, опыт интеграции с процессингом и эквайрингом; — MCP, автоматизация CI/CD и генерация тестов с помощью AI. Условия: — Полностью удаленная работа с гибким графиком; — Оплата в USD/USDT; — Минимум бюрократии и гибкие процессы в сильной команде; — Возможность профессионального роста и развития.

Location: United Kingdom (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In the United Kingdom, the Base compensation range for this role is GBP 103,958 - GBP 124,750 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Germany (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Germany, the Base compensation range for this role is EUR 100,000 - EUR 125,000 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Republic of Ireland (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In the Republic of Ireland, the Base compensation range for this role is EUR 107,000 - EUR 134,000 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Sweden (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Sweden, the Base compensation range for this role is SEK 878,578 - SEK 1,054,294 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Spain (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Spain, the Base compensation range for this role is EUR 94,025 - EUR 112,830 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Задачи: — Работа с Docker и системами оркестрации контейнеров Kubernetes — Управление конфигурациями с помощью Ansible, ArgoCD и инструментов IaC Terraform — Построение CI/CD пайплайнов с использованием GitLab CI и Jenkins — Работа с системами мониторинга и логирования: Prometheus, VictoriaMetrics, Grafana, Loki, ELK — Администрирование Linux и сетевые взаимодействия в микросервисной архитектуре — Изучение новых технологий (мультиагентные фреймворки, RAG, MCP) и предложение улучшений — Понимание жизненного цикла AI-агентов и ML-моделей — Разработка и развертывание автономных AI-агентов с использованием MCP, RAG — Работа с платформами для оркестрации агентов и serverless-средами — Интеграция корпоративных систем (OneWork, SberSpace) — Интерес к искусственному интеллекту и агентным системам Условия: — Работа в стабильной компании с официальным трудоустройством по ТК РФ с первого дня — "Белая" заработная плата — Расширенный социальный пакет: ДМС (включая стоматологию), корпоративные скидки на фитнес, спортивные секции — Профессиональное обучение и развитие — Современная техника, мощный ноутбук предоставляется в день оформления — Формат работы: строго офис, Москва

Задачи: — Получать задачи от внутренних заказчиков и погружаться в их бизнес-процессы. — Выявлять, какие процессы можно и целесообразно автоматизировать с помощью AI. — Формировать ТЗ, декомпозировать задачи и предлагать варианты реализации. — Проектировать структуру AI-автоматизации и самостоятельно реализовывать решения. — Работать с Claude, ChatGPT и другими LLM. — Создавать AI-ассистентов, AI-агентов и базы знаний. — Настраивать интеграции с CRM, 1С, сайтами, мессенджерами, телефонией и другими системами. — Работать с API, RAG, embeddings и автоматизированными workflow. — Тестировать, дорабатывать и повышать качество AI-решений. — Описывать готовые решения, создавать инструкции и базу знаний. — В перспективе выстраивать процессы разработки и управлять командой AI-разработчиков. Требования: — Опыт работы в AI / AI Automation / Backend / Integration от 3 лет. — Практический опыт работы с Claude, ChatGPT и LLM. — Опыт создания AI-решений и автоматизации бизнес-процессов. — Понимание API, интеграций, RAG, embeddings, AI-агентов. — Системное мышление и способность самостоятельно разобраться в новой задаче. — Умение общаться с бизнес-заказчиками и переводить их запросы в техническое ТЗ. — Навык самостоятельно вести задачу от постановки до готового результата. — Ответственность за качество и результат внедрения. Будет плюсом: — Python, SQL/PostgreSQL, n8n, Make, Docker, MCP, опыт создания AI-агентов, CRM/1С и опыт управления разработчиками. Условия: — Офис в Москве, рядом с м. ЦСКА. — График 5/2: 09:00–18:00 или 10:00–19:00. — Заработная плата обсуждается по итогам собеседования. — Реальные задачи по внедрению AI в бизнес, возможность видеть результат своей работы. — Возможность влиять на технологии и формировать AI-направление внутри компании. — Перспектива роста в Team Lead / руководителя направления. — Профессиональная команда и возможности для развития. — Современный офис класса А. — Скидки на услуги компании.

Location: England; Portugal; Spain; Italy; Ireland; Germany Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE We're looking for a Staff Sales Engineer who's energized by solving hard, emerging problems at the intersection of AI, security, and software delivery. You will act as a trusted technical advisor and champion owner, partnering closely with Account Executives, Post Sales, and Product teams to drive measurable business and technical value through: - Technical Selling and Deal Shaping - AI Governance and Security Thought leadership - Technical Champion Ownership and Thought Leadership - Customer and Internal Advocacy - Competitive and Strategic Selling This role suits people who like translating deep technical complexity into business clarity, who are comfortable being one of the first to help define a category, and who bring varied backgrounds and ways of thinking to how we solve customer problems. As a Staff Sales Engineer, you will be reporting to the Solutions Engineering leadership team and operate at the intersection of technical depth, business acumen, and competitive selling discipline. _______________________________________________________________________ RESPONSIBILITIES Technical Selling and Deal Shaping - Lead deep technical discovery across Platform Engineering, DevOps, Security, and AI/ML teams to understand: - AI governance requirements for agentic development (shadow AI, ungoverned MCP tools, agents holding real developer credentials) - Software supply chain risk posture - Regulatory and compliance drivers (e.g., EU AI Act, NIST AI Risk Management Framework) - Secure development lifecycle requirements - Shape technical requirements early in the sales cycle to align customer outcomes with Docker's differentiated value in AI governance, container security, and software supply chain integrity. - Design, position, and execute structured PoCs/PoVs focused on: - Sandbox, network, and MCP tool policy enforcement - Image and artifact integrity (Docker Hardened Images, SLSA Build Level 3 provenance, verifiable SBOMs) - Software supply chain visibility - Agent and MCP tool governance controls - Secure build pipelines - Define clear success criteria, evaluation frameworks, and executive-ready value summaries. - Influence decision-making through demos, workshops, architecture reviews, and technical executive briefings. - Translate complex AI security and governance capabilities into clear business value narratives for CISOs, Heads of Platform Engineering, and AI leaders. AI Governance and Security Thought Leadership - Establish credibility as a trusted advisor on: - Responsible AI development practices - Secure AI model lifecycle management - Software supply chain integrity (SLSA provenance, SBOMs, verified base images) - Container and artifact security - DevSecOps best practices - Guide customers in implementing governance controls across AI-enabled SDLC workflows. Provide architectural guidance for: - Agentic AI development environments and runtime isolation (sandboxing) - Policy-as-code enforcement across agents, tools, and machines - MCP tool governance and allow-listing - Identity and access governance for AI workloads (IdP-based role and policy assignment) - Audit, logging, and SIEM visibility for agent activity - Act as a subject matter expert on secure software supply chain and AI security trends in customer-facing engagements. Technical Champion Ownership and Thought Leadership - Build, own, and expand relationships with technical champions across Security, DevOps, Platform, and AI teams. - Establish credibility as a trusted advisor through technical thought leadership, architectural guidance, and industry best practices. - Leverage champion relationships to influence broader buying groups, shape requirements, and uncover cross-sell and expansion opportunities. - Maintain engagement beyond the initial sale, ensuring outcomes are realized and leveraging insights to support future sales motions. Customer and Internal Advocacy - Advocate for customer needs with Product and Engineering, providing clear, actionable feedback informed by field experience. - Coordinate with Post Sales and Support resources to ensure continuity across the customer lifecycle. - Develop reusable technical assets (workshops, demos, reference architectures, enablement content) to scale impact across accounts. Competitive and Strategic Selling - Actively support competitive sales motions by identifying differentiation and influencing evaluation criteria throughout the sales cycle. - Partner with Sales to develop technical win strategies for strategic and competitive accounts. _______________________________________________________________________ QUALIFICATIONS We know strong candidates come from a range of paths, and that confidence gaps keep some excellent candidates from applying to roles like this. If you meet most of what's below and are excited about the rest, please apply. - Experience as a Sales Engineer, Solutions Engineer, or Solutions Architect in complex enterprise sales. - Strong experience running competitive PoCs/PoVs with clearly defined success and exit criteria. - Ability to engage credibly with senior technical and business stakeholders, including security and platform leadership. - Solid understanding of cloud platforms (AWS, Azure, GCP), containers, DevOps, and modern application architectures. - Experience with Docker, container ecosystems, or adjacent technologies strongly preferred. - Development, agentic AI development, software development lifecycle, and/or software supply chain experience strongly preferred. - Familiarity with AI governance, secure software supply chain (SLSA, SBOMs), MCP or agentic tooling, and DevSecOps practices strongly preferred. - Must be fluent in English. - Excellent communication, influence, and stakeholder management skills. - Willingness to travel to customer sites up to 25%. _______________________________________________________________________ WHAT TO EXPECT FIRST 30 DAYS - You will be welcomed with a first-in-class onboarding experience that includes equipment setup, a sweet swag package, and a collaborative training program working with an onboarding peer. - You will learn how to navigate award-winning sales tools such as Salesforce, Opine, Sigma, and Docker. - You will actively engage with senior stakeholders and manage relationships with clients. - You will work closely with your peers and partner with SEs to develop strategies to advocate for our customers. - At the end of your first month, you will have a proficient grasp of the tools and activities necessary to be successful in your role. FIRST 60 DAYS - You will be laser-focused on supporting the sales teams during your second month. - You will have connected with all of your team members. - You will gain in-depth knowledge of Docker's products and how they impact our customers. - You will have an advanced understanding of tools, activities, and best practices to be successful in your role. FIRST 90 DAYS - In month three, you will be confident in your craft and ready to immerse yourself fully in our customers' business needs. - You will continue efforts to improve messaging, processes, and activities. - You will educate our clients about our product roadmap and undertake product training for users. - You will be ready to operate independently at full speed. Visa sponsorship: Not available for this role. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. Europe: €141,400– €202,000 OTE ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: Canada Wide - Excluding Quebec; British Columbia Workplace: Hybrid ABOUT THE ROLE Safe Software is looking for a Staff AI Engineer to design, build, and deploy production-grade AI systems across the organization. This is a hands-on engineering role responsible for the full AI lifecycle, from data preparation and model development through evaluation, deployment, monitoring, and continuous improvement. You will work across generative AI, applied machine learning, retrieval, and agentic systems while establishing reusable architectures and engineering standards for complex production implementations. ABOUT THE TEAM AI Enablement helps Safe Software adopt AI effectively and responsibly. The team builds shared capabilities, platforms, and engineering standards while enabling departments to deliver AI solutions aligned with common security and governance practices. WHAT YOU'LL BE DOING - Design, build, evaluate, deploy, and operate end-to-end AI/ML systems in production, spanning data preparation, model development, training or fine-tuning, integration, application logic, monitoring, and continuous improvement. - Architect and build agentic and multi-agent systems, including orchestration, task routing, shared state, tool use, agent handoffs, human oversight, and failure recovery. - Design and build enterprise knowledge and retrieval systems across structured and unstructured data, using data pipelines, embeddings, hybrid search, reranking, metadata, and access-controlled retrieval. - Integrate AI solutions with enterprise applications, APIs, databases, data platforms, and governed tools. - Establish automated testing, evaluation, and observability practices covering task success, model and retrieval quality, hallucination risk, tool execution, safety, latency, cost, drift, and regression. - Design secure and responsible AI systems with least-privilege access, auditability, sensitive-data protection, and safeguards against prompt injection, data leakage, and unauthorized actions. - Create reusable architectures, libraries, and engineering standards, and provide cross-functional technical leadership through design reviews, mentoring, and stakeholder collaboration. - Evaluate emerging Large Language Models, frameworks, and platforms and make evidence-based adoption recommendations. QUALIFICATIONS, SKILLS, AND COMPETENCIES WHAT WE'RE LOOKING FOR - 8+ years across software engineering and AI/ML, including 3+ years building and operating AI/ML systems in production at scale. - Strong software engineering skills, particularly in Python or comparable backend technologies. - Experience developing, adapting, fine-tuning, evaluating, deploying, and monitoring AI or machine learning models. - Applied AI experience in enterprise use cases such as chatbots, workflow automation, RAG, intelligent document processing, recommendation systems, or decision support. - Strong understanding of generative AI, LLMs, retrieval systems, agent-based architectures, and applied machine learning. - Experience with production data pipelines, APIs, model-serving infrastructure, testing, security, reliability, and observability. - Ability to explain complex technical decisions and tradeoffs to engineering teams and business stakeholders. NICE TO HAVE - Experience with agent and workflow orchestration tools such LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent. - Experience with vector databases, semantic or hybrid search, embeddings, and reranking. - Experience with platforms such as Databricks, Snowflake, Amazon Bedrock, Microsoft Foundry/Azure AI, or equivalent. - Familiarity with MCP, A2A, self-hosted or open-weight models, and hybrid AI architectures. WHAT YOU CAN EXPECT When you choose a career with Safe Software, you’re also choosing… - Meaningful Work: Make a profound impact across our business, workplace and data integration product. - A Supportive Environment: Feel empowered to share your ideas and implement them with high autonomy and team support. - Social Responsibility: Become part of a team that finds meaningful ways to give back https://www.safe.com/about/community-initiatives/. Take paid time off to volunteer for one of our Safe-organized opportunities that align with our core community initiatives. - Learning & Career Development: We believe in your continuous learning and growth. Take advantage of an annual learning budget and training programs paid for by Safe. - Flexible Working Hours: Flexible and remote-friendly work arrangements to fit your lifestyle. Work when you want, and how you want to. - Work-Life Balance: There's no place for burnout at Safe. Maintain a healthy balance of your personal and work life without splitting yourself in two. Enjoy 3 weeks of vacation to recharge, plus an additional paid 6 seasonal days off per year. - Health & Wellness: Extended health, dental, health or lifestyle spending, and counseling benefits from day 1. That’s right, no waiting period. - Family is important: We are dedicated to supporting our employees through parenthood and offer a Parental Leave Top-Up Program for new parents through childbirth or adoption. - Shared Success: Share in Safe’s success with our bi-annual profit sharing and RRSP/TFSA matching program. - An Accessible Commute: Regardless of your commute method, we’re located close to public transit, and provide complimentary parking and bike storage for our team! ABOUT SAFE SOFTWARE Safe Software transforms organizations with FME, the only All-Data Any-AI Enterprise Integration Platform connecting all your data, anywhere, at any velocity. With over 30 years of expertise and 25,000+ enterprise customers across 125+ countries, we simplify your data journey, wherever it leads. Founded in 1993, Safe is headquartered in Surrey, BC with over 300 team members and counting. We’re always looking for talented individuals with diverse backgrounds who are determined to learn and grow. Are you ready to join the team? OUR COMMITMENT TO DIVERSITY AND INCLUSION Safe Software is an equal opportunity employer and we truly believe that innovation and strength begin with diversity and inclusion. We welcome all candidates regardless of race, gender identity or expression, sexual orientation, age, ability, disability, national or ethnic origin, political belief, religion, or family status. Should you require accommodations during the recruitment process, please contact hr_dept@safe.com. NOTICE REGARDING USE OF AUTOMATED TOOLS IN HIRING At Safe Software, we use automated tools to help us process applications and identify qualified candidates. These tools may assist in screening resumes and summarizing interview content based on the information you provide. This helps our team review applications efficiently while ensuring every candidate is considered based on the requirements of the role. Please be assured that the final hiring decision is always made by a member of our team. For more information on how we protect your privacy, please see our policy https://www.safe.com/legal/#applicant-privacy-policy. If you have questions about this process, please contact us at hr_dept@safe.com.

Location: Ukraine OUR HIRING PROCESS: We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment. We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team. At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team. From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live. INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy We're looking for Senior AI Engineers to design, build and run LLM-powered agents and AI features in production. You'll work across the full lifecycle: from scoping a use case with stakeholders, through architecture and development, to deployment, evaluation and ongoing improvement. This is a hands-on role for engineers who think like product owners: you understand the business problem, define what success looks like in numbers, ship to real users, and own the result after launch. Our stack: Python and TypeScript/Node.js, PostgreSQL, Kafka, Docker, GitHub Actions, AWS. We run multiple LLM providers (Anthropic, OpenAI, Google, AWS Bedrock and others) behind a shared LLM gateway, with MCP for tool access. We work AI-native: agentic coding tools are part of how engineering gets done here, and we provide official Anthropic Claude certification for our engineers. As part of our team, your responsibilities in this role will include: Design and build LLM agents and agentic workflows: tool use via MCP, structured outputs, retrieval (RAG), multi-step orchestration, human review steps where needed. Build and maintain MCP servers and tool layers that give agents governed access to company data and systems. Own quality and cost: evals and golden sets, per-agent telemetry (tokens, cost, latency, accuracy), prompt and model versioning, provider failover and model routing. Ship through CI/CD like any other production service: tests and evals in the pipeline, containerized deploys, monitoring, rollbacks. Contribute to shared platform pieces: the agent template, the LLM gateway, observability. Work directly with business stakeholders to scope, prioritize and validate use cases. Push back when something doesn't need an agent. Use AI coding tools daily. Claude Code is our default; deep experience with a comparable agentic tool also works. You drive the tool, verify its output and catch its mistakes. Our ideal candidate possesses the following skills: 5+ years of software engineering experience, with production systems you've designed, shipped and supported. Proven experience building LLM-based agents or agentic workflows that reached production with real users. Hands-on experience with agent frameworks and SDKs: Claude Agent SDK, Claude Managed Agents, Pydantic AI, LangGraph or similar. You can also explain what you'd build without one. Hands-on experience with MCP and RAG: you've built MCP servers or equivalent tool layers, and retrieval pipelines over real, messy data. Experience with multiple LLM providers and with AWS Bedrock: model selection, routing, fallbacks, cost and rate-limit management. Strong Python and SQL. Comfortable in TypeScript/Node.js. Solid production engineering on AWS: Docker, CI/CD, testing, observability. Product thinking and business focus: you start from the problem and its cost, define success in measurable terms, and own outcomes. Daily use of agentic coding tools (Claude Code, Codex, Cursor or similar), with the judgment to verify what they produce. Clear communication with technical and non-technical stakeholders, in English. Nice to have: LLM observability or gateway tooling (Langfuse, LiteLLM, OpenTelemetry for LLM traces or similar). B2B contact and company data: enrichment, deduplication, matching. Cloud operations or FinOps: monitoring, incident handling, cost management. Event-driven or workflow-engine experience (Kafka, Temporal or similar). Experience replacing no-code or workflow-tool automations with production code. What we offer: Fully remote work format; A collaborative and creative environment that values initiative and experimentation; Paid time off and sick leave; Reduced working hours on Fridays during the summer; Days-off on US national holidays + your birthday; Schedule: 14 PM - 23 PM EEST (Kyiv time).

Location: Mapbox Helsinki Workplace: Remote Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.  As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. WHAT YOU'LL DO This role is scoped by skill rather than by product. The problems below span multiple departments and show up across our Search and Places data work, our Location and Navigation Intelligence work, and the Platform work that makes Mapbox usable by agents. You'll be hired into one specific team or product area, but you'll work across teams where your expertise meets the highest-priority AI problems. You should expect to move between teams and tech stacks as the work demands. At this level you own the technical design and delivery of a multi-component AI system, and you are accountable for the quality of what ships in your area.   IN THIS ROLE, YOU WILL: - Define how the products you own should work, build a measurement framework for it, and build evaluation systems for non-deterministic behavior. Formulate hypotheses around the products we build and seek the signal needed to validate them. Define what a correct result is for a given input and state, determine whether to assemble datasets from real usage or hand-written cases, and gate changes on regression results. - Run continuous evaluation of the products we build, whether APIs, SDKs, data representations, or reference applications, from the position of the end user, whether developer, agent, or consumer. Assess the gaps such as misuse of parameters or integration anti-patterns, recommend the fixes, and make sure they land. - Own the MVP against an agreed north star technical design, and balance technical perfection against shipping useful increments. - Build data pipelines and the tooling around them: ingestion, conflation, entity resolution, quality checks, and the batch and streaming jobs that keep a large dataset current. - Track and pull external datasets, models, and benchmarks from published research and open-source releases. Evaluate what fits the problem and constraints , and decide when to adopt what exists versus build your own. - Design feedback loops so that using a product generates data that improves it. Instrument systems so failures arrive with enough context to reproduce, then turn the recurring ones into evaluation cases. - Design the boundary between a model and the tools it calls. Build or improve the model harness, decide what the model handles, what it delegates, and how to keep it working from the state it actually fetched. - Work to a latency and cost target per request: streaming, partial results, caching, model routing, prompt structure. - Build the internal harnesses and tools (CLI, MCP, and others) your team needs to iterate quickly, and share the parts that generalize with other teams. - Raise the bar on your team through code and design review, and bring other engineers up on eval practice. - Some of the technical questions in this area are still open. You will help answer them. - Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends. WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE - Bachelors degree in STEM discipline and 5+ years of software engineering experience, with production ownership of services, pipelines, or SDKs. - 2+ years shipping LLM-backed features to real users, in systems that carried error budgets, on-call rotations, and customers who noticed regressions. - Direct experience or deep understanding of designing evaluations for non-deterministic systems. You can describe a dataset you built and the failure it caught. - Data engineering depth: SQL, at least one distributed processing framework, and experience with pipelines where a wrong record mattered more than a slow one. - Fluency with tool calling and agent orchestration, including the failure modes: stale context, hallucinated arguments, silent partial success, unbounded loops. - Working knowledge of more than one agent harness, and opinions about where each of them is weak. - Strong Python or TypeScript, and comfort reading code in whatever language the caller happens to be written in. - Experience diagnosing latency in a distributed request path. - Comfort with ambiguity, and the judgment to ship something narrow that works while the general solution is still unclear. - Clear written communication. Mapbox is distributed across time zones and we make most decisions in documents and Slack.   NICE TO HAVE TRAITS FOR THIS ROLE - Geospatial data experience: routing, geocoding, POI or address data, OpenStreetMap, or conflation of overlapping sources. - Public API or SDK design experience, particularly for developers you never talk to. - Experience building against MCP or similar tool transports. - Experience running evals in CI, with a commercial harness or one you built. - Automotive, in-vehicle infotainment, CarPlay, or Android Auto experience. - Voice pipeline experience: streaming ASR, TTS, barge-in, endpointing, wake word. - Work under constrained compute, offline, or intermittent connectivity. - Experience operating a product through its first external integrations, where the customer finds the gaps before you do.   WHAT WE VALUE In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders: - We value high-performing creative individuals who dig into problems and opportunities. - We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people. - We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company. - We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.   HOW WE SUPPORT YOU - Hybrid/Remote Options: Enjoy flexibility to work comfortably from home or periodically from an office where applicable. - Country-Specific Care & Coverage: Private health, dental, and income protection plans tailored to elevate your regional statutory benefits. - Family-First Support: Family care, maternity and paternity leave policies to support your growing family. - Lifestyle Spending Account: Contributions to support your health, wellness, and personal growth - Balance & Brainpower: Mental health support for you and your dependents. - Rest & Recharge: Paid time away, company holidays, and generous absence policies. - Time Off to Give Back: Dedicated paid volunteering time in addition to your standard PTO.   By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here. Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application. We are committed to a fair and equitable hiring process. We do not discriminate against any protected class. #LI-Remote

Appbooster — одна из ведущих AdTech-компаний в сфере мобильного маркетинга, работает с 2013 года, привлекла пользователей в 10 000+ приложений. Ищем опытного Product Manager, который возьмёт оунерство над SaaS-платформой Appbooster Platform — технологической платформой для продвижения мобильных приложений с инструментами ASO, аналитикой, запуском и управлением рекламными кампаниями, собственным источником мотивированного трафика и интеграциями с внешними системами. Платформа работает в 115 странах, имеет сложную бизнес- и бэкенд-логику, включая атрибуцию трафика, множество API-интеграций, MCP-сервер и взаимосвязанные процессы. Задачи: — владеть продуктом: отвечать за метрики, проверку гипотез, приоритизацию, фокусы команды и достижение результата; — искать точки роста выручки: анализировать воронку пользователей, юнит-экономику, поведение клиентов, выявлять узкие места и формулировать пути роста платформы; — запускать эксперименты для проверки гипотез, доводить до выводов через проблему, метрику, ожидаемый эффект и способ проверки; — самостоятельно ставить задачи дизайну, разработке, тестированию; — развивать экосистему вокруг платформы (ASO-сервис, связка с ORM) для работы продуктов как единого целого; — участвовать в адаптации продукта под зарубежные рынки; — оценивать потенциал направлений и аргументированно предлагать масштабирование или заморозку. Требования: — опыт в B2B-продуктах от 3 лет с полным циклом: анализ → гипотеза → запуск → результат → выводы; — опыт работы с выручкой и монетизацией: Revenue, ARPU, LTV, retention, конверсия в оплату; — аналитические навыки: самостоятельный анализ данных, построение воронок, выводы; — опыт постановки задач разработке: написание спецификаций, перевод бизнес-задач в ТЗ без потери деталей; — использование AI-инструментов в рабочем процессе для исследований, анализа конкурентов, прототипирования, документации. Будет плюсом: — понимание мобильного маркетинга и экосистемы сторов: UA, ASO, трекинг (AppsFlyer/Adjust), атрибуция, специфика App Store и Google Play; — английский от уровня B2; — опыт в adtech, mobile UA или ASO-инструментах; — опыт работы с платформенными/маркетплейс-продуктами; — опыт вывода продукта на международные рынки. Условия: — полноценный ownership продукта, минимум бюрократии, фокус на результат; — свобода в выборе гипотез, инструментов и подходов; — удалённый формат работы без ограничений по локации и гибкий график; — ДМС после 3 месяцев работы; — корпоративный Mac и необходимые инструменты; — системный процесс performance review раз в год и быстрый обмен открытым фидбеком; — компенсация 30% затрат на занятия английским в партнёрских школах или с личным преподавателем, English speaking club; — компенсация внешних курсов и программ обучения с индивидуальными условиями; — открытая и нетоксичная корпоративная культура, прозрачные процессы планирования и принятия решений; — полноценный онбординг и возможность проявлять себя; — корпоративные подарки на день рождения.

Задачи: — Проектировать UX и UI новых игровых экранов и фич. — Работать внутри существующего визуального стиля игры, сохраняя его консистентность. — Поддерживать и развивать UI Kit: добавлять новые компоненты и состояния по мере развития проекта. — Продумывать структуру интерфейсов для сложных игровых систем: прогрессия, персонажи, экипировка, события, магазины, Battle Pass, рейтинги, турниры и т.д. — Выстроить AI first pipeline создания UI: от постановки задачи и генерации структуры экрана до получения максимально готового результата в Figma. — Использовать AI не только для референсов или генерации картинок, а как полноценный рабочий инструмент: агенты, генерация layouts, работа с design system, автоматизация повторяющихся операций, генерация вариантов и т.д. — Улучшать саму дизайн систему так, чтобы AI мог как можно надежнее собирать из нее новые интерфейсы. — Подготавливать макеты и компоненты для передачи в разработку и взаимодействовать с командой Unity. Требования: — Опыт работы над RPG, Strategy, 4X, social casino или другими UI heavy играми. — Хорошее понимание UX мобильных игр: информационная иерархия, навигация, состояния элементов, onboarding, progression UX. — Сильное владение Figma, компонентами, variants, variables и design systems. — Умение работать с уже существующим стилем. — Понимание того, как строить масштабируемый UI Kit для игры с большим количеством экранов. — Опыт построения AI процессов вокруг Figma. — Опыт работы с Figma API / MCP / AI-агентами. — Понимание UI DSL, structured UI descriptions, YAML/JSON схем интерфейсов или похожих подходов. — Опыт автоматической генерации экранов из дизайн системы. — Понимание Unity UI и того, как дизайнерские компоненты превращаются в реальные игровые интерфейсы. Условия: — Part time. — Удаленная работа. — Долгосрочное сотрудничество. — Гибкий график, важнее результат и скорость коммуникации с командой. При отклике прислать: — примеры RPG / Strategy / других системных игр, над которыми вы работали. — короткое описание того, как именно вы сейчас используете AI в UI/UX работе. — резюме в PDF, ссылку на общий портфель и ставку в час.

О проекте: Мы строим технологическую платформу для производства, хранения и дистрибуции медиаконтента. Это медиа-хранилище нового поколения, где AI‑агенты берут на себя рутинные и творческие задачи: от автоматической разметки и адаптации контента до его подготовки к публикации в 30+ каналах (сайты и приложения Банка, мессенджеры, соцсети). Наш технологический стек: Ядро фронтенда: React, Next.js, TypeScript Состояние и данные: Redux Toolkit, RTK Query Взаимодействие с AI: Server-Sent Events (SSE), стриминг ответов агентов, MCP Стилизация: CSS3, SASS/SCSS, CSS Modules Тестирование: Jest, React Testing Library Серверная часть: Node.js, REST API, SSR Инструменты и CI/CD: npm/yarn, Git, Webpack, ESLint, Jenkins, Docker Управление: Jira, Confluence Требования: Опыт коммерческой фронтенд-разработки от 5 лет, из них от 2 лет в роли Senior. Глубокий практический опыт с React, Next.js и TypeScript, понимание внутреннего устройства. Опыт проектирования архитектуры сложных фронтенд-приложений и принятия ключевых технических решений. Понимание и применение принципов SOLID, DRY, KISS, а также паттернов проектирования. Опыт работы с менеджерами состояний (Redux Toolkit, RTK Query) в крупных проектах. Уверенные знания HTML5, CSS3 и препроцессоров (SASS). Опыт работы с REST API, SSR и серверным Node.js на продвинутом уровне. Опыт работы с Server-Sent Events (SSE): проектирование стриминговых интерфейсов, обработка событий на клиенте, реконнекты, graceful degradation. Умение писать unit‑тесты (Jest/React Testing Library), опыт внедрения культуры тестирования в команде. Опыт наставничества и менторства разработчиков. Условия: Возможность карьерного роста и получения экспертизы в ведущих финансовых организациях страны; Скидки на абонемент в фитнес-центр, курсы английского языка; Офисный, гибридный, удаленный формат работы Оформление по ТК РФ на бессрочный трудовой договор.

Задачи: — Разработка и развитие мобильного приложения на Capacitor (web-технологии внутри нативной обёртки, публикация в App Store и Google Play) — Разработка веб-кабинета пользователя и админ-интерфейсов — Совместная работа с бэкенд-командой по проектированию и интеграции REST API — Обеспечение производительности, отзывчивости и кросс-браузерной совместимости интерфейсов — Участие в code review, написание тестов, поддержание качества кода — Работа с существующим кодом и его постепенный рефакторинг — Ведение повторяемых частей работы с помощью ИИ-агентов (сборка экранов под новый партнёрский бренд, подключение к API, проверка на устройствах) с целью сокращения времени выпуска с дней до часов Требования: — 3+ года коммерческого опыта в JavaScript — 2+ года опыта работы с Vue.js (Composition API, Vue Router, Pinia/Vuex) — Уверенное знание HTML5, CSS3, адаптивная вёрстка — Опыт интеграции REST API (HTTP, JSON, авторизация, обработка ошибок) — Опыт работы с Git в команде — Базовое знание Docker (запуск проекта в контейнерах) — Умение читать чужой код и работать с legacy — Английский: Beginner и выше — Практический опыт или четкое понимание ценности работы через ИИ-агентов — Осознанная проверка кода за агентом: умение аргументированно объяснить логику и корректность сгенерированного результата Будет плюсом: — Опыт работы с Capacitor, Cordova или Ionic — Опыт публикации приложений в App Store и Google Play — TypeScript — Опыт работы с современными сборщиками (Vite, Webpack) — Опыт написания unit/e2e тестов (Vitest, Jest, Cypress, Playwright) — Понимание принципов PWA — Опыт работы с PHP backend (для эффективной коммуникации с командой) — Опыт работы в telecom — Навык декомпозиции задач для эффективного делегирования ИИ-агентам — Умение выявлять характерные изъяны AI-кода — Опыт создания системных инструкций и переиспользуемых ролей для агентов вместо написания разовых запросов — Способность выстраивать многоэтапные цепочки агентов (анализ → планирование → кодинг → тест) — Навык интеграции агентов с внешним окружением: MCP-серверами, технической документацией и таск-трекерами — Четкое понимание границ применимости ИИ: где автоматизация полезна, а где целесообразнее ручное исполнение Условия: — Формат: Full-time (170 часов в месяц), удалённая работа, долгосрочное сотрудничество — На финальном этапе возможен запрос рекомендаций от бывших коллег/руководителей — Перед финальным оффером проводится стандартный Background check — Обязательное использование программы учёта времени Scrin.io на рабочем устройстве

Задачи: — Разработка и развитие мобильного приложения на Capacitor (web-технологии внутри нативной обёртки, публикация в App Store и Google Play) — Разработка веб-кабинета пользователя и админ-интерфейсов — Совместная работа с бэкенд-командой по проектированию и интеграции REST API — Обеспечение производительности, отзывчивости и кросс-браузерной совместимости интерфейсов — Участие в code review, написание тестов, поддержание качества кода — Работа с существующим кодом и его постепенный рефакторинг — Ведение повторяемых частей работы с помощью ИИ-агентов (сборка экранов под новый партнёрский бренд, подключение к API, проверка на устройствах) с целью сокращения времени выпуска с дней до часов Требования: — 3+ года коммерческого опыта в JavaScript — 2+ года опыта работы с Vue.js (Composition API, Vue Router, Pinia/Vuex) — Уверенное знание HTML5, CSS3, адаптивная вёрстка — Опыт интеграции REST API (HTTP, JSON, авторизация, обработка ошибок) — Опыт работы с Git в команде — Базовое знание Docker (запуск проекта в контейнерах) — Умение читать чужой код и работать с legacy — Английский: Beginner и выше — Практический опыт или четкое понимание ценности работы через ИИ-агентов — Осознанная проверка кода за агентом: умение аргументированно объяснить логику и корректность сгенерированного результата Будет плюсом: — Опыт работы с Capacitor, Cordova или Ionic — Опыт публикации приложений в App Store и Google Play — TypeScript — Опыт работы с современными сборщиками (Vite, Webpack) — Опыт написания unit/e2e тестов (Vitest, Jest, Cypress, Playwright) — Понимание принципов PWA — Опыт работы с PHP backend (для эффективной коммуникации с командой) — Опыт работы в telecom — Навык декомпозиции задач для эффективного делегирования ИИ-агентам — Умение выявлять характерные изъяны AI-кода — Опыт создания системных инструкций и переиспользуемых ролей для агентов вместо написания разовых запросов — Способность выстраивать многоэтапные цепочки агентов (анализ → планирование → кодинг → тест) — Навык интеграции агентов с внешним окружением: MCP-серверами, технической документацией и таск-трекерами — Четкое понимание границ применимости ИИ: где автоматизация полезна, а где целесообразнее ручное исполнение Условия: — Формат: Full-time (170 часов в месяц), удалённая работа, долгосрочное сотрудничество — На финальном этапе возможен запрос рекомендаций от бывших коллег/руководителей — Перед финальным оффером проводится стандартный Background check — Обязательное использование программы учёта времени Scrin.io на рабочем устройстве

Задачи: — Переводить бизнес-задачи в архитектурные и технические решения — Развивать AI-продукты, интеграции, новые каналы и источники данных — Определять затрагиваемые компоненты, API, контракты, модели данных и бизнес-семантику — Декомпозировать разработку на проверяемые задачи для AI coding agents — Проверять сгенерированный код, проводить code review, тестирование и выпуск изменений — Отвечать за стабильность, безопасность и конечный результат Требования: — Опыт промышленной разработки от 3 лет — Бэкграунд в аналитике данных, BI или системном анализе — Умение работать с бизнес-требованиями, метриками, моделями данных и интеграционными контрактами — Практический опыт промпт-инжиниринга: проектирование, тестирование и оптимизация промптов для LLM, построение многошаговых AI-флоу и достижение стабильного качества ответов — Практический опыт с LLM, AI-агентами, RAG, tool calling, structured outputs и MCP — Уверенное знание TypeScript или Python, API, SQL, Git, CI/CD и автоматизированного тестирования — Понимание принципов работы современных языковых моделей, ограничений LLM и способов повышения качества генерации — Системное мышление, самостоятельность и ответственность за продукт целиком Будет преимуществом: — Опыт создания и оптимизации сложных промптов для различных AI-сценариев (reasoning, extraction, generation, classification) — Опыт создания evals, guardrails и контроля качества AI-ответов — Опыт работы с React, Telegram-ботами, BI-платформами и семантическими слоями Условия: — Конкурентную заработную плату (обсуждается индивидуально) — Профессиональный рост и участие в масштабных проектах — Работу в крупном холдинге с активной цифровой трансформацией — Сильную ИТ-команду и поддержку руководства — Необходимость краткосрочного приезда в солнечный Ташкент для оформления