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Location: United States; Europe Workplace: Remote ABOUT MATTER LABS Matter Labs invented ZK rollups and built the first one on Ethereum: six years in production, over a billion transactions processed, over four billion dollars in value locked. We want programmable money to become a foundation for the next financial system, with institutions able to shape the services they provide and keep authority as their infrastructure evolves. Prividium is our platform for institutions to build and operate digital asset businesses, with privacy and under their own rules. Prividium Commander is the control plane for digital asset services: an institution decides who can do what and tracks the resulting activity, on Prividium Ledger or on the chains it already runs. Prividium Ledger is a private blockchain with publicly verifiable execution. Prividium Connect gives institutions private, bridgeless transactions across blockchains. Prividium Ledger runs in production for a number of institutional customers. Keeping those ledgers reliable, and making the next ten cheaper to operate than the first four, is the work this role is hired for. Remote and global, few approvals, a CEO you can reach, unrestricted access to the best AI tools and the expectation that you use them, and a hiring bar of hell yes or no. THE ROLE You join the Production Unit, the three-person team that owns ZKsync OS in production for our customers: detection, incidents, rollouts and the service objectives each customer is measured against. Today the work is mostly reactive: on-call, incidents, rollouts, RCAs. The job is to change that. Every page and every manual step is a candidate for a fix in the server, a better alert or an automation. About 30 percent of your time goes to code now, and that share grows as the reactive load shrinks. You own the environments you are assigned end to end: whether a change is safe to roll out, how an incident gets restored and explained, and whether the customer's service objectives are being met. Component teams own their code; you read it, find the cause, and land the fix. WHAT YOU WILL DO: - Run production for institutional customers. Hold the First Responder rotation, coordinate incidents to restoration, and write the RCA the customer's engineers read. - Decide what ships. Go/no-go on changes to your environments, verification before rollout and validation after, including executing sequencer rollouts. - Remove the cause. Turn pages, runbooks and manual steps into fixes in the sequencer, provers or tooling, so the same incident does not come back. - Measure the service. Own the SLA card for your customers, measured monthly against their contracts. - Finish across teams. Drive diagnosis and fixes through the component teams that own the code, without waiting to be asked. - Later, support customers who run the chain themselves, where the fix has to work in someone else's hands. Within a year, on-call load in your environments is measurably lower because of what you shipped, and the unit can take on the next customer without adding people. WHAT WE LOOK FOR - You have been on-call for a system you wrote code for, and you have owned an incident from page to RCA to the fix that stopped it recurring. - You find causes in code you did not write. Strong in a systems language such as Rust, Go, C++ or Java; Rust is learnable here. - You verify before you roll out and you can say which changes are reversible and which are not. - You have run production for a service with external customers, and your incident notices and RCAs were read by their engineers. - You make other teams finish the work without escalating. - You are willing to hold a 24/7 rotation. Nice to have: rollup or node operations experience (sequencer, prover, L1 settlement); Ethereum execution client internals; tooling you built that other teams adopted. If you meet most of this and the rest is learnable, apply anyway. NOT THIS ROLE This is not a Forward Deployed Engineer role, which builds and deploys for a customer from discovery to production readiness; this role operates what is in production. It is not DevOps (clusters, network, L1 nodes, backups and disaster recovery stay with DevOps), not partner management, and not a people-management role. COMPENSATION AND WORK MODEL - Base salary range: USD 192,000 to 230,000 per year. Where an offer lands in the range depends on demonstrated scope and results against the bar described above. For candidates in the EU the same range applies - Performance-based variable compensation and a long-term token incentive are additional. - Benefits (employees): medical, dental and vision from day one, global health cover for team members outside the US; 401(k) with a Safe Harbor match up to 4 percent for eligible US employees, flexible paid time off plus public holidays and two company closure weeks a year; six weeks paid parental bonding leave plus up to ten weeks paid birth recovery leave; confidential mental health support; a USD 2,000 home office stipend, a company laptop refreshed every three years, up to USD 400 a month toward coworking, and a USD 500 annual learning budget; company and team offsites. - Fully remote. You must be based in the US or the EU, with the US preferred; some of our customers whitelist the jurisdictions their operators work from, so this is a hard requirement. - Full-time, as an employee or a contractor. - 24/7 First Responder rotation shared with the Production Unit. Everyone in this role is on it. - We do not ask about your current or past pay at any stage of the process.

Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Principal, Product Learning & Development About the job Twilio is the world’s leading customer engagement platform empowering developers to build modern communication applications and experiences designed to be trusted, simple and smart. Twilio is looking for a Principal, Product Learning & Development to bring our AI first PDLC vision to life and build the capability our product organization needs to deliver it. Reporting to the Director of Product Strategy & Operations, this role owns how our PMs get better at their craft, and how they learn to do that craft with AI. You'll build the competency model and curriculum that define "how we do product here," then go beyond curriculum by designing and shipping the internal tooling (prompt libraries, agents, PRD generators) that makes a PM measurably faster and sharper. You'll bring our AI first PDLC vision to life, partnering with product and engineering leaders to find where AI genuinely changes the work, and coaching the org through the change. Responsibilities We are looking for a leader who brings product, learning, and hands on AI expertise to help: Design and deliver the PM Academy, covering onboarding and ongoing curriculum across PRD writing, discovery, prioritization, roadmapping, and stakeholder influence, each taught with AI in the workflow. Design and help build and facilitate adoption of "PM in a box": ship internal AI tooling such as prompt libraries, agents, and PRD and research generators, as products with users, feedback loops, and adoption targets. Bring the AI first PDLC vision to life and execute against it, partnering with Product leaders to map current workflows and identify the AI and automation opportunities worth pursuing. Run cohort programs for new PMs and newly promoted PM managers, and design tailored programming for different parts of the organization rather than one generic track. Curate the internal playbooks, templates, and documentation that carry "how we do product here," and keep them current as practice changes. Facilitate workshops, office hours, and 1:1 coaching for PMs and PM leaders, building the credibility to coach senior people. Drive AI adoption across the PM org through a champion network that surfaces use cases from inside each team. Measure impact against baselines captured before rollout. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: Bachelor’s degree in Business, Computer Science, a related field or equivalent practical experience. 8+ years of experience across product management, consulting, program management, L&D or enablement Experience leading programs or product operations for B2B SaaS, PaaS or equivalent Outstanding written and verbal communication that drives executional impact at scale, distilling complex detail into an executive narrative, and explaining technical concepts to audiences without technical backgrounds. Strong facilitation, and the ability to build trust and exchange ideas across organizational boundaries in service of a broader goal. Excellent problem solving and organizational skills. Ability to thrive in a fast paced, evolving, ambiguous environment, with a default to action in order to adapt quickly to changing priorities and requirements. Desired: Master’s in computer science or engineering or business administration Hands on experience building AI agents, automated workflows, and internal tooling. Experience leading change management in B2B SaaS Location This role will be remote and based in the USA. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 5-10% travel is anticipated to help you connect in-person in a meaningful way. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $171,120 - $ 213,900 Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $181,200 - $226,500 Based in the San Francisco Bay area, California: $201,280 - $251,600 This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Applications for this role are intended to be accepted until March 1, 2027, but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: Москва Workplace: Офис Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Мы ищем Product Manager, который будет отвечать за внедрение и развитие продуктовых решений для транспортной логистики. Основная задача — помогать операционным командам осваивать новый функционал, оценивать его эффективность на практике и находить возможности для улучшений. Обязанности Изучать процессы транспортной логистики, потребности пользователей и особенности их работы; Организовывать внедрение нового функционала: взаимодействовать с логистами, проводить презентации и помогать командам осваивать инструменты; Собирать и анализировать обратную связь, выявлять проблемы и передавать их продуктовой команде в виде предложений по улучшению; Оценивать, как внедрённые решения влияют на операционные процессы и бизнес-результаты. Требования Опыт работы в транспортной логистике или понимание операционных процессов, взаимодействия с перевозчиками и организации перевозок; Опыт работы с IT-продуктами: участие в их развитии, внедрении или продуктовом управлении; Умение выявлять потребности пользователей, анализировать обратную связь и формулировать требования к улучшениям; Навыки взаимодействия с разными командами и сопровождения изменений. 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.

Задачи: — развивать технологические продукты для страхового рынка, разбираться в сложных бизнес-процессах и создавать решения, которыми пользуются сразу несколько компаний. — развивать направление страхования жизни внутри существующей платформы; — анализировать и унифицировать бизнес-процессы; — формировать единую продуктовую модель для работы банков с продуктами разных страховщиков; — прорабатывать партнёрские интеграции и возможности масштабирования решения; — формировать требования, управлять бэклогом и сопровождать реализацию продукта вместе с аналитиками и разработчиками. Требования: — опыт Product Manager / Product Owner в страховании/ InsurTech; — понимание страхования жизни и бизнес-процессов страховых компаний; — опыт развития B2B-продуктов, страховых платформ или интеграционных решений; — умение самостоятельно прорабатывать продуктовую логику и переводить бизнес-задачи в требования для разработки; — системное мышление, самостоятельность и готовность глубоко погружаться в продукт. — опыт в страховых B2B-платформах и агрегаторах; — опыт в продуктовых фабриках и конструкторах страховых продуктов; — опыт в развитии партнёрских кабинетов, API и B2B2C-решений. Условия: — Москва, удалённо или гибрид с возможностью очных встреч с командой и партнёрами. — ТК РФ — есть перспектива роста до руководителя продуктового модуля.

Responsibilities: — Define and lead the strategy and roadmap for fraud prevention, covering account integrity, money movement, decisions, controls, and customer protection experiences. — Develop and implement a strategic vision to reduce fraud and enhance risk management, including managing holds, limit structures, step-up verification, and friction points. — Design user journeys that balance risk-based friction with minimal disruption to legitimate users. — Build operational and platform tools to support risk and support teams in managing case volumes and exceptions. — Collaborate with data science teams to develop, deploy, and improve machine learning models continuously. — Establish and monitor metrics to evaluate risk effectiveness, operational efficiency, and customer experience impact. — Support scaling of Mercury's risk capabilities across expanding product offerings. Requirements: — Over 7 years of product management experience, specifically in fraud or risk within banking or fintech sectors. — Strong customer empathy and understanding of how risk friction affects user experience, growth, and retention. — Experience with complex automated decision systems, rules, machine learning models, and real-time data pipelines. — Proficiency in analytics and the ability to interpret performance metrics and trade-offs in ML models. — Proven cross-functional leadership skills, especially in balancing risk, compliance, and customer experience. — Excellent communication skills to translate complex risk concepts into actionable product strategies. — Ability to make balanced decisions amid ambiguity and imperfect information. Benefits: — Competitive total rewards package including base salary, equity (stock options/RSUs), and benefits. — Salary ranges are competitive within SaaS and fintech industries and adjusted based on experience, expertise, location, and internal equity. Additional Information: — Work location options include on-site in San Francisco, New York, Portland (US), or remote within Canada or the United States. — Mercury is a fintech company providing banking platforms and financial services for startups and small businesses. — Mercury is not an FDIC-insured bank; banking services are provided through partner institutions. — Mercury is an Equal Employment Opportunity employer committed to diversity and inclusion, providing accommodations for applicants with disabilities or special needs.

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: New York City Metropolitan Area; New Jersey Workplace: hybrid About the Role: The problem you'd be solving We build AI systems that enterprises run their business on. Production systems inside banks, insurers, and health systems, where our engineers embed with the client, learn the work, and own the outcome. We call them Forward Deployed Engineers and Forward Deployed Executives. These people hold design conversations with a Chief Data Officer on Tuesday and ship to production next Monday. We are hiring a People & Talent Partner to help us scale our FDE/FDX, Product, and GTM teams. Five open reqs at a time, none of them generic. We would rather you run five properly than twenty badly. Beyond filling roles, you will own the talent community strategy around Provectus, and you will build the people-operations presence for our US team locally — be the person our US colleagues come to first. Location: Hybrid, New York: 2-3 days onsite. Type: Full-time (W2). What You'll Do: Recruiting: Full-cycle hiring across the US for Forward Deployed Engineers (software, AI/ML, architects, leads), Forward Deployed Executives, Product Owners, and Business Development Managers. Intake to offer: Partnership with the hiring managers. You'll run calibration with them and bring market data when a scorecard doesn't match what exists. Architect and execute Provectus's talent community strategy in the US. Meetups, workshops, hackathons, university programs, and the AI/ML communities. You don't need to have run events before. You need to want to help with that, and there's a budget and support from marketing when you do. US hiring strategy. Talent market intelligence, compensation benchmarking, and how we position Provectus against the companies competing for the same engineers. People operations for the US team. You'll be the on-the-ground people partner for our US-based colleagues, working with the Head of People Operations: Onboarding of US hires. First point of contact for US employees on benefits, time off, policies, and day-to-day people questions. Support for the performance review cycle for US-based staff: scheduling, collecting feedback, tracking outcomes. Team engagement and onsite days — the rhythm that makes a hybrid New York team feel like a team. What's the split between Recruiting and HR? 70/30 What You'll Bring: 4+ years of full-cycle recruiting experience in a fast-paced technical environment, ideally at an AI, cloud, or consulting firm Proven track record of sourcing and hiring senior technical profiles — AI/ML engineers, software engineers, architects, or consulting leaders Demonstrates personal AI adoption — uses AI tools as part of their recruiting workflow, not just aware of them Exposure to HR generalist or people-operations work — onboarding, benefits, employee relations — or a clear appetite to build it. You don't need to have been an HRBP. Excellent communication and stakeholder management skills; comfortable partnering with C-level and senior technical leadership Highly organized, self-directed, and comfortable with ambiguity in a distributed, global team Commitment to Provectus's core values: Obsession, Ownership, Transparency, and Partnership Based in the New York / New Jersey area and able to be onsite [2-3] days a week Nice to have: Experience building talent community: events, meetups, professional networks, or university programs Familiarity with US benefits administration, onboarding, and experience with an HRIS. Where this goes: This is a growing US function. The person who does this well takes on more of the community mandate, more senior searches, a deeper people-partner role as the US team grows, and a path toward owning the US talent function. We'll talk about that trajectory. What We Offer: Direct impact on Provectus's growth in the US market with direct visibility to leadership. Access to the Provectus Learning Hub, Claude Code certification support Collaborative culture that rewards ownership, curiosity, and continuous learning Full-time W2 model. Base $150k- 170k. Final offer reflects experience, skills, and market data. Health, vision, dental, disability, and life insurance; 401(k) plan; unlimited vacation. About Provectus: Provectus is an AWS Premier Partner and an Anthropic Strategic Partner working at the front edge of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable outcomes through bespoke applications, managed services, and advisory work. We focus on Financial Services & Insurance and Healthcare & Life Sciences, with offices across North America, LATAM, and EMEA. Hiring Process: 30-45-minute call with the Head of Talent Acquisition 30-minute call with the Head of People Operations On-site meeting with the CEO

Location: United States Workplace: Remote Coder is hiring a Senior Product Manager to own Workflows and Integrations, two of the newest surfaces in Coder Agents. You'll take charters that are close to a blank page and give them a strategy. Workflows is the automation layer for the AI software development lifecycle. It owns how the development work a team repeats every day becomes something agents run for them, and how our users author, reuse, and share those automations. Integrations is the connective tissue that lets our agents reach outward and outside tools reach in. First-party product integrations such as Slack and Linear, connectors to the external tools our customers already run, and the API and auth work that makes each of those feel like a first-class part of the product. You'll define vision and strategy where it's still nascent, then bring enough structure to scale without slowing momentum. You'll partner closely with engineering, design, and go-to-market teams to ship and measure impact. We're running lean on process by design, so expect to build judgment, not bureaucracy. What you'll do here - Own the full product lifecycle for Workflows and Integrations, from incubating ideas through GA and into ongoing scale, including the sequencing between the two. - Define and evolve product vision and strategy for both charters, synthesizing customer, market, and business signals into a clear roadmap. - Define what development work is worth automating first, and what it takes for a team to trust an agent to run it unattended. - Own the integration surface as a product: which third-party tools our agents can reach, and what partners need to build against us. - Research customer problems through direct engagement with enterprise accounts, community feedback, and ecosystem analysis. - Bring just enough structure to move fast without losing rigor: strong problem statements, crisp requirements, clear execution. - Lead high-stakes customer conversations, including executive roadmap reviews, product demos, and enterprise stakeholder discussions. - Collaborate with PMM to shape licensing, packaging, and pricing decisions that support these surfaces' path to sustainable growth. What we're looking for - 5+ years of experience building software products end-to-end, with clear customer and business outcomes, at least three of them on developer-facing or infrastructure products. - You've built products where developers or platform and DevOps operators were the adopting users. Developer platforms, CI/CD, workflow and orchestration systems, API and integration platforms, infrastructure-as-code, or cloud infrastructure. - You've taken an agentic or LLM product to production, and can talk concretely about tool design, evaluations, and the ways your agents failed. - You've owned a platform, API, or extensibility surface that other people built on top of, and you understand the versioning, auth, and governance trade-offs that come with it. - Proven experience taking a product from zero to GA, setting direction where little exists yet. - Experience shipping into enterprise engineering organisations, where the adopter is a developer and the buyer is a platform or engineering leader. - A strong technical foundation that lets you collaborate credibly with engineers and make informed trade-offs. - Proven ability to operate independently and set the agenda with minimal oversight. - Willingness to travel occasionally for customer and industry engagements. Bonus tacos if you have - (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) - Experience with automation or orchestration products such as CI systems, data pipelines, RPA, or agent frameworks. - Experience with pricing strategy, licensing models, onboarding funnels, or open-core business models. - Experience across both startup and larger-scale organizations. - Comfort representing Coder externally through talks, writing, or other public channels. ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Location: United Kingdom Workplace: Remote You'll make Coder easy to buy, deploy, integrate, and operate at the world's largest organizations. Partnering with another Product Manager in the Enterprise Experience theme, you'll help enterprises confidently adopt safe, secure, and governed development environments for humans and AI agents alike. You'll co-own the strategy for making Coder a first-class citizen in complex enterprise ecosystems. You'll work with engineering, security, sales, and customer-facing teams to turn enterprise challenges into product capabilities, removing barriers to adoption and ensuring Coder scales reliably in demanding environments. What you'll do - Co-own the Enterprise Experience charter with another Product Manager, sharing responsibility for strategy, prioritization, execution, and outcomes - Define and evolve the product strategy for enterprise readiness, turning customer needs and market expectations into a clear roadmap - Identify and eliminate technical, security, compliance, and operational barriers preventing enterprises from adopting Coder - Shape how Coder is deployed and operated at scale, including reference architectures, high availability, upgrades, and lifecycle management - Drive integrations with enterprise systems for identity, access management, application lifecycle management, reporting, and collaboration - Translate enterprise security, compliance, and governance requirements into product capabilities that enable safe development for humans and AI agents - Engage directly with enterprise customers and field teams, distinguishing recurring product needs from one-off requests - Lead strategic customer conversations, including executive roadmap reviews, technical evaluations, and enterprise deployment discussions What we're looking for - 5+ years building software products end-to-end with clear customer and business outcomes, including at least 3 years on developer-facing, infrastructure, or enterprise platform products - Experience building products for enterprise IT, platform engineering, DevOps, or security teams - Understanding of how large organizations evaluate, procure, deploy, and operate software - Familiarity with enterprise infrastructure concepts such as Kubernetes, cloud and hybrid deployments, high availability, authentication, authorization, and lifecycle management - Experience translating enterprise security, compliance, or regulatory requirements into practical product capabilities - Understanding of enterprise integrations, interoperability, and the trade-offs between security, compatibility, and maintainability - Experience working with enterprise engineering organizations where developers are the users but platform engineering, IT, security, and leadership influence purchasing decisions - Strong technical foundation enabling credible collaboration with engineers and architects - Ability to operate independently, collaborate effectively with other PMs, and drive complex initiatives with minimal oversight - Willingness to travel occasionally for customer and industry engagements Bonus tacos if you have (Tacos? Ask us how we say thanks by giving tacos!) - Experience with security and compliance frameworks such as SOC 2, ISO 27001, FedRAMP, HIPAA, or GDPR - Hands-on familiarity with Kubernetes, infrastructure-as-code, or enterprise deployment architectures - Experience building products for regulated industries such as financial services, healthcare, or government - Familiarity with air-gapped environments, sovereign AI, data residency, or self-hosted AI infrastructure - Experience with enterprise procurement, technical sales enablement, or complex customer evaluations ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Ищу продакта, которому интересно развивать технологические продукты для страхового рынка, разбираться в сложных бизнес-процессах и создавать решения, которыми пользуются сразу несколько компаний.

Ищу Senior Product менеджера. Нужно будет менедженить продуктовую команду мобильного приложения в 27 человек.

– 5+ лет в Product / Program Management в технологических компаниях. Чем предстоит заниматься:

Чем предстоит заниматься: Управлять развитием продукта в рамках уже определённой продуктовой стратегии. Основной фокус — операционное управление продуктом, проработка и реализация продуктовых инициатив, без формирования стратегии и определения долгосрочного вектора развития продукта ;

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.