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Location: Remote Spain At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The International Accelerator Engineering team is growing, and we're looking for a Senior Software Engineer to join us! We're a full-stack team located entirely in Europe within the same time zone, but culturally rooted in Silicon Valley. We directly improve the financial lives of over 20 million people shaping how Affirm builds Direct-to-Consumer products for Canada, the UK, and future international markets. We build and own various products used by our consumers, like the Affirm App and other Direct to Consumer products across international markets. We are here to make sure we reach and provide useful tools to our users so they can experience honest financial products at their fullest. Our work is agile and fast-paced, shipping new code to production for millions to use across geographies and rigorously measuring the impact it has on them. This role rewards curiosity, ownership, ability to zoom in and out, switch contexts often, also in an open contribution model, and a builder's mindset. You'll know exactly what your objectives are, you'll have what you need to hit them, and you'll choose your own path to get there, while constantly looking for ways to get AI to increase productivity on a daily basis. You'll learn quickly from experienced teammates and grow your craft on problems that matter at scale. If you want to build something new and operate it at scale – come join us! What You'll Do: You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. On-Call Rotation - There would be an on-call rotation for this role as a requirement. What We Look For: · You have a total of 4+ years of experience as a software engineer. · You are experienced in designing, developing and launching backend systems at scale technologies like Python, Kotlin, AWS, MySQL, and Kubernetes. · You have experience shipping web apps using declarative UI frameworks like React or Vue. - You efficiently use AI to assist you to deliver high quality products on a daily basis · You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others. · You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely. · Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders. · You have strong verbal and written communication skills that support effective collaboration with our global engineering team. Compensation & Benefits Pay Grade - N Equity Grade - 4 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). ESP base pay range per year: €86,000 - €122,000 Additional benefits include: • Flexible Spending Wallets for tech, food and lifestyle • Away Days - wellness days to take off work and recharge • Learning & Development programs • Parental benefits • Employee Resource & Community Groups Location - Remote Spain We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Almaty, Kazakhstan Workplace: hybrid Grocery Storefront is a new team at inDrive. The team builds a native grocery and food shopping experience inside the inDrive super app: the iOS and Android storefront and the mobile backend-for-frontend (BFF). As an Android Engineer, you will build the Android storefront from its first version. You will work in a small team of iOS, Android, backend and QA engineers. Key Responsibilities Develop storefront screens and features in the Android app, from the catalog to the checkout Work with backend engineers on API contracts for the mobile BFF. Run A/B experiments, manage feature flags, and implement analytics events Do code reviews, write tests, and co-design solutions with backend and iOS engineers Build with AI tools (Claude Code, Copilot) as part of an AI-First approach Skills, Knowledge and Expertise 3+ years of commercial Android development with Kotlin Good knowledge of Coroutines, Flow, MVVM/MVI and DI (Dagger/Hilt) Experience with Jetpack Compose Experience with multi-module projects and Gradle Understanding of networking, caching and unstable connections Experience with unit testing English level: B1+ Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

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 .

Location: San Juan, Puerto Rico; New York, NY; District of Columbia; Europe | Spain Workplace: Hybrid About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the role Rain builds payments and stablecoin infrastructure. Finance, Risk, Compliance, and our partners rely on data from card transactions, settlements, ledger entries, and onchain transfers. We’re looking for a Data Engineer with batch and streaming experience to bring this data into our warehouse and keep it correct. You’ll build scalable, idempotent pipelines that handle late and duplicate data and alert us when something breaks. At Rain, everyone models data, writes production-quality code, and automates their own workflows. We use AI to speed up repetitive work, but we own and check the results. In this role, you’ll automate ingestion and quality checks so new sources come online quickly and stay trustworthy. What you’ll do - Build scalable batch and streaming pipelines, choosing the right approach for latency, cost, and correctness. - Process events near real time, handling deduplication, windowing, and late or out-of-order events. - Own batch ingestion from databases (CDC), files (SFTP and GCS), APIs, and onchain sources. - Build incremental dbt models that handle late data, duplicates, CDC deletes, and backfills; reconcile streaming and batch outputs. - Orchestrate pipelines in Dagster with sensors, schedules, and alerts. - Add freshness, volume, and reconciliation checks to every source, and fix root causes. - Work with backend pods on event and table contracts to prevent downstream breakage. - Partner with Analytics Engineers, Data Scientists, and Risk on their data needs, including ML features. What you’ll need - At least 3 years building production data solutions, including owning both batch and streaming pipelines end to end, from source to warehouse. - Experience designing data solutions at scale. - Strong SQL and Python / Rust, plus experience with a cloud data warehouse such as BigQuery, ClickHouse, or Snowflake and an understanding of their trade-offs. - Streaming experience with tools such as Pub/Sub, Kafka, Dataflow/Beam, or Flink. - Batch experience with dbt and an orchestrator such as Dagster or Airflow. - Experience with production data quality testing, monitoring, and reconciliation. - Ability to debug across the source database, pipeline, warehouse, and report. - Ability to use AI tools to learn and work faster while checking their output. Nice to have - Building offline and real-time ML feature pipelines, such as fraud or risk features. - Working with payments, banking, or blockchain data, including EVM or Solana events and indexers. - Using CDC and ingestion tools such as Datastream, Debezium, Meltano, Fivetran, or Airbyte. - Experience with GCP. Things that enable a fulfilling, healthy and happy experience at Rain: Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: San Juan, Puerto Rico; New York, NY; District of Columbia; Europe | Spain Workplace: OnSite About the Company Rain is the global stablecoin payments platform for enterprises, neobanks, platforms, developers, and AI agents. Our technology allows partners to move, store, and use stablecoins instantly and compliantly through global payment cards, rewards, on/offramps, wallets, and cross-border rails. As both a Visa and Mastercard Principal Member, Rain issues cards that work at more than 175 million merchant locations in over 220 countries and territories. Built natively for stablecoins and trusted by more than 100 organizations worldwide, Rain delivers secure, scalable infrastructure that makes money move freely and instantly around the world. You will have the opportunity to deliver massive impact at a hypergrowth company backed by some of the top investors in fintech, crypto, and SaaS. In January 2026, we closed a $250M Series C led by ICONIQ, valuing Rain at $1.95B, with Sapphire Ventures, Norwest, Galaxy Ventures, Dragonfly, Bessemer Venture Partners, FirstMark, Lightspeed, and Endeavor Catalyst also participating. If you're curious, bold, and excited to help shape a borderless financial future, we'd love to talk. Our Ethos We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company. About the role Rain is building payments and stablecoin infrastructure, and our data platform holds some of the most sensitive data a company can have: cardholder, ledger, and partner data across many countries. We’re looking for a Data Platform Engineer who has built and run data platforms for both batch and streaming to own the platform our data team and engineering pods depend on: the warehouse, streaming infrastructure, orchestration, BI, ML platform, access controls, and the tooling that makes all of it safe, reliable, and cost-efficient. Your product is the platform, and your customers are the engineers, analysts, and scientists who build on it. You’ll own the platform layer: the data and ML platform, the infrastructure for ingestion and processing in batch and streaming, data governance and security compliance, the warehouse, and the analytics and BI tooling. Data Engineers, Analytics Engineers, Data Scientists, and engineering pods build on it to run experiments, operate reliably, and turn data into decisions. At Rain, we’re builders who use AI to automate repetitive work. That changes what data roles look like: where a data scientist used to only analyze and an analyst used to only build dashboards, here everyone models data, writes production-quality code, and automates their own workflows. You own the result, including checking what the AI produces. For this role, that means automating access, deploys, and governance so the platform runs itself and stays compliant. What you’ll do - Design and build data platforms at scale for both batch and streaming, choosing storage, compute, and processing based on latency, cost, and reliability needs. - Own the infrastructure for BigQuery, streaming (such as Pub/Sub or Kafka, and Dataflow or Flink), Dagster+, and Lightdash as code, including environments, CI/CD, and deploys. - Own access and governance: IAM, policy tags, PII contracts, masked and no-PII access paths, and audit logs, across tables and streams. - Provide ML platform capabilities: feature pipelines, training data, and serving real-time features to fraud and risk models. - Build platform tooling: templates, CI checks, schema registry and data contracts, catalog, and lineage. - Monitor platform reliability, latency, and cost, and fix what is slow or expensive. - Design how backend events and CDC land in the warehouse, and advise backend pods on event design. - Respond to platform incidents and access requests, and automate the repetitive ones away. What you’ll need - At least 4 years building and running data platforms in production on a cloud provider such as GCP, AWS, or Azure, in both batch and streaming: you have operated infrastructure for each, not only one. - Experience designing data platforms at scale: storage and compute choices, multi-team access, reliability, and cost. - Experience operating cloud data warehouses and real-time stores such as BigQuery and ClickHouse. - Experience operating streaming infrastructure such as Pub/Sub, Kafka, Dataflow, or Flink, including retention, schema evolution, replay, and lag monitoring. - Experience operating batch infrastructure: orchestration (Dagster or Airflow), CI/CD, and environments. - Infrastructure as code with Terraform. - Experience with access control and data governance, such as IAM, column- or row-level security, and PII handling. - Strong Python and SQL. - Proficiency using AI tools to learn new skills and accelerate your work, while taking responsibility for checking the output. Nice to have - ML infrastructure experience, such as feature stores, Vertex AI, or model serving. - Experience in regulated environments such as payments, banking, PCI, or SOC 2. - Experience with data catalogs and lineage tools. - Experience with cost optimization in BigQuery, ClickHouse, or Snowflake. - Experience with CDC tools such as Datastream or Debezium. Things that enable a fulfilling, healthy and happy experience at Rain: Flexible time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take 10 days minimum for themselves. Flexible working ☕ We support a flexible workplace – work from home, come into an office, or both. We want everyone to work in an environment where they're their most confident and productive selves. New Rainmakers receive a stipend to set up a comfortable home workspace. Easy to access benefits 🧠 For US Rainmakers, we cover 95% of your health, dental, and vision plan costs and 90% for your dependents, plus a 100% company-subsidized life insurance plan. Retirement goals💡 Plan for the future with confidence. We offer a 401(k) with a 4% company match. Equity plan 📦 Every Rainmaker gets an equity option plan so we all benefit from our success. Health and Wellness 📚 High performance begins from within. Rainmakers receive a monthly stipend to be used for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you! In-office meals 🍜 Rainmakers working from the office enjoy lunch and dinner on us, covered with a DoorDash credit. Team summits ✨ Summits play an important role at Rain. Time together helps us build relationships and a common destiny. Expect team and company offsites, both domestic and international.

Location: Hong Kong SAR; Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Project Overview： Maintain the mobile app for iOS and Android in Flutter Follow Figma designs to build beautiful interfaces through Flutter Work with our design and backend teams to implement new features Stay up to date with best practices in mobile performance, security, and UX Write documentation and support internal knowledge sharing Must Haves Major in Computer Science or related fields. Solid foundation in computer science and a good understanding of microcomputer principles. Strong sense of responsibility for software products, with good communication skills and excellent teamwork capabilities. Proficient in at least one programming language, such as (but not limited to): Java, Kotlin, Objective-C, Swift, C, C++, or Python. Passion for building the high-performance apps Nice to Haves Strong experience with Flutter and Native mobile development Solid understanding of TypeScript and modern React patterns Side projects or open-source contributions Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

• Разработка ML-моделей для автоматической модерации видеоконтента: классификация контента, выявление запрещённых материалов, определение нарушений правил платформы. • Разработка моделей на основе Computer Vision и Deep Learning для анализа видео и изображений.

Задачи: — Реализовывать и развивать мобильный SDK, проводя рефакторинг существующей архитектуры на Kotlin Multiplatform; — Развивать сетевой и data layer, включая управление запросами, retry-стратегии, throttling, обработку ошибок, кэширование, локальное хранение и синхронизацию данных; — Разрабатывать асинхронные пайплайны с контролем конкурентности и latency, реализовывать фоновые операции и управление состоянием данных; — Реализовывать realtime-взаимодействие и persistent connections, включая механизмы восстановления соединения, интеграцию нативной и веб-части через WebView и взаимодействие с backend; — Обеспечивать корректную интеграцию и работу SDK в сторонних приложениях, заниматься тестированием, диагностикой, мониторингом и оптимизацией производительности и потребления ресурсов. Требования: — Практический опыт разработки на Kotlin Multiplatform на системном уровне, не UI; — Опыт разработки SDK, библиотек, framework или сложных переиспользуемых мобильных компонентов; — Знание интеграции мобильных библиотек или SDK в сторонние приложения; — Регулярная практика проектирования и реализации архитектуры мобильных приложений или платформенных решений; — Опыт работы с асинхронностью и конкурентностью (Kotlin Coroutines / Flow); — Опыт проектирования сетевого взаимодействия на уровне production, применение модели OSI при разработке сервисов; — Понимание построения data-heavy систем на клиентской стороне: кэширование, синхронизация, консистентность данных; — Навыки самостоятельной реализации технических решений, тестирования и отладки; — Опыт системного debugging и поиска первопричин проблем. Будет плюсом: — Опыт разработки и поддержки приложений с DAU > 1000; — Знание Swift и Swift Concurrency; — Опыт интеграции WebView и взаимодействия нативной и веб-части; — Опыт работы с realtime-коммуникациями, streaming и persistent connections; — Знакомство с SQLDelight, OkHttp и аналогичными инструментами; — Понимание работы поисковых систем, ранжирования или e-commerce систем. Условия: — Удалённая работа или гибридный формат; — Предпочтительная локация: Москва, Екатеринбург, Нижний Новгород (для периодических личных встреч); — Оформление сотрудничества через ИП; — Оплата 2000–2500 рублей в час; — Максимальный месячный бюджет 420 000 рублей. Дополнительно: — Вы будете единственным мобильным инженером компании, отвечать за мобильный SDK; — Архитектура SDK 2.0 уже спроектирована, предстоит реализовать её, довести SDK до production и обеспечивать дальнейшее развитие и качество; — Тесное взаимодействие с backend-инженером, включая совместные code review; — Работа над SDK от анализа и проработки решений до реализации, тестирования, выпуска и поддержки. Технологический стек компании включает Kotlin, Swift, Kotlin Multiplatform, SQLDelight, OkHttp, Flutter, Python. Компания YoloPrice — embeddable e-commerce платформа, интегрируемая в сторонние мобильные приложения, обеспечивающая ключевую логику: поиск, данные, синхронизацию и работу приложения в online.

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

• 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.

Задачи: — Доработка существующего функционала и разработка нового — Сбор и анализ бизнес-требований, моделирование возможных решений — Решение интеграционных задач с использованием современных технологий — Документирование проекта, написание инструкций к собственным разработкам — Сопровождение пользователей на этапе внедрения Требования: — Высшее техническое образование или студенты старших курсов — Технический английский язык (желательно) — Опыт программирования (желательно) — Высокий уровень обучаемости, самоорганизации и клиентоориентированности — Готовность к обучению и самообучению, стремление повышать профессиональный уровень и расти по карьерной лестнице Условия: — Возможность совмещать работу с учебой: полная или частичная занятость на 30/35 часов с гибким началом и окончанием рабочего дня — Оплачиваемая стажировка с дальнейшим трудоустройством в штат компании, пересмотр оклада и грейда дважды в год — Удобный офис в историческом районе Москвы, в шаговой доступности от метро Добрынинская, Серпуховская, Павелецкая — Технологичное рабочее место с 2+ мониторами, многофункциональным порталом собственной разработки, собственной системой обслуживания баз данных, сильной ИТ-инфраструктурой, современным железом (intel 10+, nvme ssd, 32gb ram) — Обучение и развитие: внутренние и внешние тренинги, компенсация обучения, участие в конференциях, корпоративная база знаний, скидки на изучение английского языка — Социальный пакет: мобильная связь, корпоративное такси, дополнительные дни отпуска, доплата по больничным листам до 100% зарплаты, компенсация покупки абонемента в спортзал, софинансирование ДМС — Корпоративная жизнь: кейс-чемпионаты, английский клуб, волейбол, тематические вечера, выезды на природу Используемый стек: YouTrack, Bitrix24, многофункциональный портал собственной разработки (backend 1С + React/Android/iOS фронтенд), EDT, GIT, GITLAB, SonarQube, автоматизированное тестирование (vanessa automation), docker Компания предоставляет сильную IT инфраструктуру с собственным железом в лучших ЦОД, veeam, SSO, 100+ виртуальных машин. География работы: Москва, офис.

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

Location: Москва Workplace: не определен, Удаленно Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Команда Магазина занимается разработкой backend сервисов для основного приложения WB. Сейчас в планах очень крутые и амбициозные задачи в направлении core, финтеха и контента. Тут высокая нагрузка до 150К RPS и большая ответственность! Обязанности Участвовать в разработке новых микросервисов бэкенда мобильных приложений и доработке их фукционала; Разрабатывать архитектуру новых сервисов; Профилировать и оптимизировать высоконагруженные микросервисы; Покрывать разрабатываемый код unit-тестами, обеспечивая его надежность и упрощение рефакторинга. Требования Имеете опыт разработки на Golang не менее двух лет, применяете лучшие практики языка для создания эффективного и поддерживаемого кода; Имеете опыт разработки микросервисов и многопоточных приложений; Разрабатываете и понимаете принципы разработки высоконагруженных систем; Имеете опыт разработки Web-сервисов (REST, gRPC), знаете HTTP; Проектируете и оптимизируете реляционные базы данных (PostgreSQL), имеете опыт работы c NoSQL и брокерами сообщений. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.