Вакансии

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 applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Sweden, the Base compensation range for this role is SEK 814,000 - SEK 1,017,000 .  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. 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 applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Germany, the base compensation range for this role is € 100,000 - €125,000 . 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 .

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 applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In Spain, the base compensation range for this role is €85 ,000 - €107,000 . 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 .

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 applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In 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 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 .

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 applications from the UK, Ireland, Sweden, Spain and Germany. The opportunity: Grafana Labs is building a native experimentation platform: a Grafana app that lets teams define A/B tests, connect them to feature flags and product telemetry, and get trustworthy, statistically sound answers about what their changes actually did. It started as a hackathon project and is now used by Grafana engineering and product teams in our internal environment to run real experiments. The next step is to make it a first-class product: one we rely on every day internally and, over time, one we offer to Grafana Cloud customers alongside Frontend Observability, Session Replay and our other user-experience capabilities. You'll join the Product Analytics team , a group of highly technical product analysts who help teams across Grafana understand how our products are used and run experiments on them. As the team's dedicated software engineer, you'll own the engineering of the experimentation app and have a lot of influence over where it goes. You'll partner closely with data scientists on the statistics, data engineers on event pipelines and the data warehouse, software engineers across Grafana on feature flags, Frontend Observability and the App Platform, and product stakeholders who rely on experiment results to make decisions. This is a hands-on engineering role that ships production code. It is not an analyst role. About the product: The experimentation app is built on the Grafana App Platform: Frontend: a TypeScript and React app plugin using @grafana/ui, plus a custom datasource plugin that powers experiment statistics panels. Backend: Go, built with the Grafana App SDK. Experiments are Kubernetes-style custom resources defined in CUE, with an operator, admission webhooks, and support for declarative, GitOps-style management. Feature flags: integration with OpenFeature and the OpenFeature Remote Evaluation Protocol (OFREP) , Grafana's multi-tenant feature toggle service, and an embedded GO Feature Flag evaluator. Statistics engine: a Bayesian analysis engine (TypeScript, with a Go port) that produces a direction-aware verdict per metric, probability to be best, credible intervals, expected loss and sample-size recommendations. Data: experiment exposure and outcome events flow from product instrumentation through RudderStack into BigQuery, or from Grafana Faro into Loki, and are queried live through Grafana datasources. AI: experiment authoring assisted by Grafana Assistant , which discovers relevant data and drafts the experiment configuration for a human to review. What You’ll be doing: Evolve the experimentation app from internal tool to product. Full ownership of features end to end across the React frontend and Go backend, from problem framing and design through rollout, measurement and iteration. Build the experimentation experience. Develop intuitive workflows for defining hypotheses, configuring experiments and metrics, managing their lifecycle, and exploring results. Make these experiences useful for product managers and analysts as well as engineers. Make instrumentation easier to adopt and trust . Evolve the experimentation SDK and its OpenFeature and Faro integrations. Help teams connect variant assignment, actual exposure, and outcome events with consistent identity and event contracts. Connect experiments to the rest of Grafana’s user-experience stack. Integrate with Grafana Faro and Frontend Observability so flag exposures and outcomes are captured automatically, and link experiment results to Session Replay and critical user journeys so teams can see why a variant won, not only that it won. Harden the statistics and analysis path. Work with our data analysts to extend the statistics engine, and make analysis scalable, cost-aware and correct. Examples include moving computation server-side, scheduled analysis, alerting on experiment health, and guardrails against misleading results. Use AI where it genuinely helps. Extend the Grafana Assistant integration for authoring, explaining and reporting on experiments. Raise the engineering bar. Mentor teammates, including analysts who contribute code, through code review, pairing and design docs. Write the architecture decision records (ADRs), docs and demos that help other teams adopt experimentation. Own what you ship. Take part in on-call for the services you build, and support the internal teams that run experiments on them. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups, always with strong code review and quality standards. You’ll also have access to the latest frontier models from OpenAI, Anthropic, and Google. What makes you a great fit: We highly value people who are intellectually curious, default to transparency, have a strong bias towards action, and are kind and enjoy working as a team. Strong full-stack engineering experience. You’ve built and operated production web applications with TypeScript and React, and backend services in Go (or a similar language, with willingness to work in Go). You value maintainability, automated testing and secure development practices. Experience building an in-house platform or integrating existing experimentation and A/B testing platform (for example Statsig, Eppo, GrowthBook, Optimizely, LaunchDarkly experiments, or an in-house platform). Product and data intuition. You care whether what you shipped actually moved the needle, and you’re comfortable working with event data, SQL and data warehouses such as BigQuery. Technical ownership. You’ve delivered complex projects with minimal supervision, broken them into short feedback loops (analyze, design, ship an MVP, learn, iterate), and helped teammates work more effectively. Operational responsibility. You’ve been on call, supported software in production, and know how to make systems observable and debuggable. Pragmatic AI usage. You use AI coding tools thoughtfully, validate their output, and share practices that improve the team’s speed and quality. Clear communication. You can explain technical and statistical tradeoffs to engineers, analysts and product managers in a fully remote, asynchronous environment. Bonus Points For: Hands-on experience with feature flags and OpenFeature. A working understanding of experiment statistics: Bayesian or frequentist testing, sample sizing, variance reduction, and common pitfalls such as peeking and sample ratio mismatch. Experience with Kubernetes concepts: custom resources, operators, admission webhooks, GitOps. Experience building Grafana plugins or apps, or with the Grafana App SDK or Scenes. Familiarity with frontend observability and product analytics tooling, such as Grafana Faro, RUM, session replay, RudderStack or Segment. Open source contribution or maintainership. Experience as a user of Grafana, Prometheus, Loki or Tempo, whether at work or on a homelab. Compensation & Rewards: In the UK, the base compensation range for this role is £94 ,000 - £118,000 . 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 .

Responsibilities: — Own product strategy, roadmap and prioritisation together with the CTO and company leadership. — Conduct discovery with PSPs, merchants, payment operations and internal teams to identify problems and automation opportunities. — Translate complex payment workflows into clear requirements and acceptance criteria for cashiers, hosted payment pages, widgets, and operational tools. — Define user journeys, permissions, and workflows; collaborate with the product designer on prototypes and specifications. — Lead delivery with engineering, QA, design, and business teams, balancing platform scalability with client-specific and white-label needs. — Establish product standards for localisation, accessibility, multi-tenancy, security, and auditability across global markets, devices, and payment behaviors. — Identify and promote AI use cases in core workflows, including contextual assistance, anomaly detection, recommendations, and natural-language analytics. — Utilize analytics, usability testing, and customer feedback to measure outcomes and enhance the product post-launch. Requirements: — Proven significant experience as a Product Manager, Product Owner, or Product Lead in payment processing platforms such as payment orchestration, PSP, acquiring, or payment gateways. — Direct ownership of cashiers, hosted payment pages, checkout flows, payment widgets, or similar transaction interfaces with accountability for results. — Strong understanding of payment journeys, transaction statuses, routing, declines, payment methods, and merchant requirements. — Solid UX knowledge including user research, journeys, and information architecture, with proficiency in Figma or equivalent tools. — Technical fluency in APIs, frontend architecture, and software delivery to make informed trade-offs with engineers. — Experience with global, multi-tenant products and practical understanding of AI in product workflows. — Fluent English. — Nice to have: experience with merchant portals, backoffices, B2B SaaS, data-heavy dashboards, payment orchestration platforms, improving checkout or payment-widget conversion, and frontend or software engineering background including prototype building and frontend inspection. Benefits: — Competitive compensation. — Cozy office in Limassol with snacks, drinks, PS5, and rooftop kitchen view during probation, with flexible format afterward. — Sports and lunch compensation. — Team events, health insurance, relocation, and work permit support.

Location: Москва Workplace: Комбинированный Мы создаём социальную сеть «Одноклассники» и развиваем все ключевые сервисы платформы — от контентных и коммуникационных до инфраструктурных, влияя на ключевые метрики продукта: DAU и Timespent. Наши решения работают под высокой нагрузкой и напрямую влияют на продуктовые метрики и пользовательский опыт. Ищем руководителя команды разработки, который возьмёт на себя техническое и управленческое лидерство команды. Задачи Руководство кросс-функциональной командой (backend, frontend, mobile, QA): повышение эффективности, развитие разработчиков Проработка продуктовых фич Участие в разработке при необходимости Улучшение качества, производительности и надёжности сервисов Проектирование и развитие архитектуры высоконагруженных сервисов Оптимизация процессов разработки и взаимодействия между командами Требования Имеете опыт в бэкенде (Java) от пяти лет, пишете на Java Знаете алгоритмы и структуры данных Уже управляли командой разработки от 5–7 человек Знаете, как выстраивать процессы разработки Умеете проектировать отказоустойчивые и высоконагруженные сервисы: планировали ресурсы и сроки

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

• Build and maintain functionality in our React Native SDK, including brownfield integration into partners’ host apps. • Debug the full request path: mobile client, network, BFF, and external services.

- Develop and maintain modern web applications. - Design and implement AI-powered features and agentic workflows.

Develop and maintain scalable backend services and REST APIs. 5+ years in backend development (Python 3+, in Django or similar).

Задачи: — проектирование и разработка нового функционала платформы — анализ и усовершенствование существующего функционала платформы — проектирование и реализация интеграций со сторонними сервисами — работа в команде: развитие практик, код ревью, усовершенствование процессов — тесное взаимодействие с бизнесом: выяснение требований и контекста, анализ оптимального способа реализации идей — коммуникация с коллегами смежных областей: QA, Frontend, DevOps, BA Требования: — опыт разработки Java Backend от 2 лет — сильные навыки программирования на Java — навыки работы с AI-ассистентами — уверенные знания Spring инфраструктуры — опыт работы с популярными SQL базами (PostgreSQL, MSSQL, MySql, Oracle и др.) — понимание принципов работы Redis, Kafka, NoSql DB (Mongo) — знание базовых принципов микросервисной архитектуры — опыт работы с Kubernetes Плюсы: — практический опыт разработки приложений электронной коммерции, знание e-commerce платформ — опыт работы с Elasticsearch как поисковым механизмом Условия: — стабильный и прозрачный доход, размер заработной платы обсуждается по итогам собеседования — оформление согласно ТК Республики Беларусь — гибридный формат работы 5/2, офис в Минске по адресу ул. Кальварийская, д.42 (ст.м. Молодежная)

Responsibilities: — Developing and maintaining modern web applications — Building responsive, high-performance UIs and reusable components — Developing backend services and APIs using Node.js — Integrating internal services and third-party platforms — Improving application performance, architecture, and scalability — Troubleshooting, testing, and maintaining clean, reliable code Requirements: — 3+ years of frontend development experience — Strong TypeScript and React and/or Next.js skills — Hands-on backend experience with Node.js — Experience with REST APIs and third-party integrations — Familiarity with Git, CI/CD, testing, and performance optimization — Ability to write clean, maintainable, and scalable code Nice to have: — Experience with platform modernization — Automated testing and API mocking — DevOps and infrastructure automation

Responsibilities: — Own outcomes by collaborating with Product and Design to clarify customer needs, select approaches, and manage initiatives through delivery and follow-up. — Build across the stack by developing data exploration interfaces, backend services and APIs, and the data models and computations connecting them. — Ensure complex logic is reliable by investigating assumptions, reasoning through edge cases, and establishing testing and validation methods for algorithms and statistical business logic. — Drive coordinated delivery by breaking down ambiguous goals into manageable steps, agreeing on priorities, coordinating dependencies, surfacing risks early, and keeping colleagues informed. — Build shared understanding by listening to different perspectives, explaining trade-offs clearly, and helping engineering and business stakeholders reach decisions. — Strengthen engineering practice through architecture discussions, thoughtful reviews, documentation, mentoring, and process improvements. Requirements: — Senior engineering experience with designing, shipping, and operating substantial production software and the ability to explain decisions behind it. — Full stack capability with depth, comfortable across frontend, backend, data, and models, with particular strengths and willingness to deepen expertise as needed. — Strong fundamentals including understanding of APIs, data modeling, algorithms, application state, and testing affecting correctness, performance, and maintainability. — Analytical reasoning skills to break down unfamiliar problems, make assumptions explicit, identify counterexamples, and verify solution soundness. — Collaborative leadership skills including asking useful questions, building agreement, giving and receiving constructive feedback, and helping colleagues progress. — Practical AI judgment to provide useful context, critically assess generated output, verify changes through tests and investigation, considering security, maintainability, and complexity. — Experience with analytical products, statistics, or algorithmic systems is valuable. — Curiosity and willingness to learn the domain are essential. Benefits: — Opportunity to combine product engineering with quantitative challenges, influence product and architecture, and grow through hands-on technical leadership and collaboration. — Healthcare and mental health support, paid holidays and family leave, equity opportunities, and career development opportunities provided by Smartly. Recruitment Process: — Recruiter conversation about experience and role. — Team lead discussion about expectations and ways of working. — Technical interviews covering coding, system design, and architecture.

проектировать и валидировать архитектурные решения; улучшать производительность как Backend, так и клиентских приложений;

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE We’re looking for a Software Engineer to join our AI Tooling team and help shape how developers and agents build with Supabase. You'll build and own our AI tooling, including agents, the MCP server, agent skills and the dashboard assistant, and as the space moves you'll build the tooling for new technologies too. You'll build it all eval-first: every tool ships with evals and metrics, so we know, with evidence, that it makes agents better rather than worse. You'll work closely with the Docs, CLI, Frontend and SDK teams, and with the AI Tooling Infrastructure engineers who run these services in production. Other teams contribute to AI Tooling to improve Supabase's agentic capabilities, and you'll help them do that while keeping the quality bar high. This role is ideal for someone who thrives in async, fast-paced environments and is excited about building developer tools that scale to millions. WHAT YOU’LL BE RESPONSIBLE FOR - Build and improve the AI tooling we run today, including the MCP server, agent skills, agents and the Assistant. - Make new Supabase products usable by agents from day one: tools, skills and evals for new product surfaces. Also build tooling for new AI technologies as they emerge: prototype quickly, evaluate honestly, and decide with the team what is worth taking to production. - Drive an eval-first approach: build and improve evals, instrumentation and feedback loops, measure tools against a no-tool baseline, and help define the quality KPIs and gates that stop regressions shipping. - Understand how customers and agents actually use what we ship, and turn that into improvements to our tooling, interfaces and documentation. - Design how documentation and product knowledge are exposed to agents, and measure whether it works. - Build patterns and tools that help customers add AI to their own apps, such as MCP on Edge Functions, vector embeddings and agents running on Edge Functions. - Enable teams to improve Supabase's agentic capabilities through contributions to AI Tooling: clear contribution paths, templates, documentation and review practice. - Centralise shared AI logic so teams reuse it rather than duplicate it. - Ship tools that are battle-tested, with strong tests, benchmarking and stress testing where it counts. - Work with the AI Tooling Infrastructure engineers on reliability, auth and hosting. - Work across Docs, CLI, Frontend, SDK and other teams to deliver one coherent developer experience, and stay close to the fast-moving AI ecosystem. YOU MIGHT BE A GOOD FIT IF YOU MUST HAVE: - Have 5+ years of experience in professional software engineering experience. - Write strong TypeScript and know the JavaScript ecosystem well: npm, ES modules, bundlers, compatibility. - Are deeply familiar with the AI ecosystem: current tools, agent patterns and practical trade-offs. You can tell a durable pattern from hype. - Have built developer tools, product interfaces or platform primitives used by other engineers. - Have designed or used evaluation frameworks to measure AI quality, reliability and task success, and understand baselines, variance and cost. - Have strong judgement about where AI improves workflows and how to avoid fragile or gimmicky experiences. - Write tests and validate reliability in real-world conditions. - Know Postgres and relational database practice. - Communicate clearly in writing, work across product, engineering and docs, and thrive in async, globally distributed teams. - Are comfortable navigating ambiguity and moving quickly. NICE TO HAVE: - Experience with vector databases and embeddings, ideally pgvector. - Examples of customer-facing AI features or agents you've shipped. - Examples of documentation or structured knowledge designed for developers or agents. - Experience with Braintrust or a similar eval and tracing platform, or setting up CI quality gates. - Open-source contributions or developer tooling you've maintained. - Experience across several product surfaces or teams. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

- Разработка и поддержка E2E-автотестов на Playwright + TypeScript. - Тестирование Frontend и пользовательских сценариев (включая работу с оборудованием: кассы, весы, сканеры, ККТ).

Ищем senior full stack разработчика, который разбирается в задачах пользователей, принимает технические решения и самостоятельно доводит функции до выпуска и использования. - Разрабатывать функции целиком: уточнять требования и критерии приёмки, реализовывать backend на Go, интерфейсы на React / TypeScript, API и работу с PostgreSQL.