Responsibilities:
— Design, build and maintain backend services in Go with clean, idiomatic, and readable code
— Design gRPC and REST APIs, maintain stable contracts, and version them when changes occur
— Write efficient PostgreSQL queries, design schemas, and create safe, reversible migrations
— Properly use goroutines, channels, and context to avoid leaks and ensure correct timeouts and cancellations
— Handle errors explicitly, including retries and idempotency for repeatable calls
— Write unit and integration tests covering business logic and failure cases
— Implement structured logging, metrics, and health checks for problem diagnosis
— Ensure service security by validating input, authenticating callers, and keeping secrets out of code and logs
— Profile and optimize CPU, memory, and database load as needed
— Write concise technical documentation for owned APIs and services
— Review teammates' pull requests to maintain code consistency
Requirements:
— 1–3 years of commercial backend development experience in Go
— Experience building or maintaining at least one production service in Go (REST or gRPC)
— Proficiency with PostgreSQL including queries, indexes, and migrations
— Experience using Docker and writing Dockerfiles
— Basic Kubernetes knowledge is a plus
— Experience integrating third-party APIs, preferably payments or webhooks
— Familiarity with Git and pull requests in a team environment
— Required skills include Go concurrency primitives (goroutines, channels, context), error handling, REST API design, gRPC and Protobuf knowledge, PostgreSQL SQL queries and migrations, Docker, Git, unit testing in Go, HTTP basics including JWT authentication, and Linux basics
Nice to have:
— Kubernetes basics (pods, deployments, logs via kubectl)
— Experience with payment providers (Click, Payme, Uzum) or webhooks
— Experience with message queues such as RabbitMQ, Kafka, or NATS
— Redis
— CI/CD with GitHub Actions
— Monitoring tools like Prometheus or Grafana
— Experience with Helm, ArgoCD, or other GitOps tools
— Experience with HashiCorp Vault or other secrets managers
— Experience with IoT or hardware integrations (barriers, cameras, ANPR)
— Experience with payment providers and fiscal requirements
— Networking experience including tunnels, VPNs (IPsec), and load balancers
— Some knowledge of C#/.NET
Soft Skills:
— Takes responsibility for results beyond just completing tasks
— Proactively asks for help when stuck
— Communicates clearly about progress and blockers
— Accepts code review feedback calmly
— Learns new tools quickly
— Pays attention to detail, especially in payment logic
— Works well in a small team
Candidate Assessment Process:
1. CV review including GitHub within 3 working days
2. Short call (20–30 minutes) discussing experience and role
3. Technical interview (60–120 minutes) covering Go basics, concurrency, PostgreSQL, REST/gRPC, and a live coding task
4. Final interview (30 minutes) with team lead discussing work style and offer
Apply https://hh.uz/vacancy/139299572
Location: London; Belgrade; Ireland
Keeping a crawler running is not the same as keeping it productive. Queues can grow while servers look healthy, and a small change can become a fleet-wide bottleneck. On Perplexity's Crawler team, you'll improve throughput, plan capacity, and build operational reliability through safer deployments, better observability, and durable fixes.
Responsibilities
- Operate and optimize Kubernetes workloads and supporting infrastructure for crawler services, including fetching and rendering fleets.
- Build and maintain infrastructure as code and CI/CD pipelines, with safe rollouts, validation, and fast rollback.
- Define SLOs and build monitoring, alerting, and observability for availability, latency, throughput, and resource saturation.
- Own capacity planning and resource efficiency; diagnose queue backlogs, network failures, and resource bottlenecks with service owners.
- Participate in the team's on-call rotation, lead incident response, and turn blameless postmortems into durable reliability improvements.
- Write production software to automate diagnosis and routine remediation, with validation and approval gates for high-impact actions.
Qualifications
- 5+ years of experience in SRE, production engineering, or infrastructure-heavy backend roles, with strong programming skills in Python, C++, Rust, or Go.
- Hands-on experience with cloud infrastructure, production Kubernetes, infrastructure as code such as Terraform, and automated deployment workflows.
- Strong Linux and networking fundamentals, including TCP/IP, DNS, TLS, HTTP, and load balancing.
- Experience building observability with tools such as Datadog, Prometheus, or Grafana, and using SLOs to guide reliability improvements.
- Proven experience diagnosing distributed-system failures, leading production incidents, and improving system performance or resource efficiency.
Nice to have
- Experience operating web crawlers, search infrastructure, or browser fleets at scale.
- Experience with distributed queues, backpressure, workload isolation, or multi-region recovery.
Location: London; Belgrade; Ireland
Keeping a crawler running is not the same as keeping it productive. Queues can grow while servers look healthy, and a small change can become a fleet-wide bottleneck. On Perplexity's Crawler team, you'll improve throughput, plan capacity, and build operational reliability through safer deployments, better observability, and durable fixes.
Responsibilities
- Operate and optimize Kubernetes workloads and supporting infrastructure for crawler services, including fetching and rendering fleets.
- Build and maintain infrastructure as code and CI/CD pipelines, with safe rollouts, validation, and fast rollback.
- Define SLOs and build monitoring, alerting, and observability for availability, latency, throughput, and resource saturation.
- Own capacity planning and resource efficiency; diagnose queue backlogs, network failures, and resource bottlenecks with service owners.
- Participate in the team's on-call rotation, lead incident response, and turn blameless postmortems into durable reliability improvements.
- Write production software to automate diagnosis and routine remediation, with validation and approval gates for high-impact actions.
Qualifications
- 5+ years of experience in SRE, production engineering, or infrastructure-heavy backend roles, with strong programming skills in Python, C++, Rust, or Go.
- Hands-on experience with cloud infrastructure, production Kubernetes, infrastructure as code such as Terraform, and automated deployment workflows.
- Strong Linux and networking fundamentals, including TCP/IP, DNS, TLS, HTTP, and load balancing.
- Experience building observability with tools such as Datadog, Prometheus, or Grafana, and using SLOs to guide reliability improvements.
- Proven experience diagnosing distributed-system failures, leading production incidents, and improving system performance or resource efficiency.
Nice to have
- Experience operating web crawlers, search infrastructure, or browser fleets at scale.
- Experience with distributed queues, backpressure, workload isolation, or multi-region recovery.
London; Belgrade; Ireland
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
Location: Remote - Colombia ; Remote - Costa Rica ; Remote - Mexico
About Backblaze
Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands.
Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $136M ARR and is the leading specialized storage cloud, managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals.
But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We’re seeking a Site Reliability Engineer III (DBA) in LATAM to join our team!
About the Role
We are seeking a Site Reliability Engineer III with a Database Administration focus to help ensure the stability, scalability, and reliability of our production database systems, primarily Vitess (distributed MySQL) and Cassandra, alongside the rest of our production services and infrastructure.
This database specialization is layered on top of the full SRE III scope on the team. You will carry the same on-call, incident response, and service ownership expectations as other SRE IIIs, with database systems serving as your area of deepest technical ownership.
Because our SRE Database Engineering function is new, this role will also help establish its operational foundation by designing database architecture and developing the runbooks, escalation guidance, procedures, and training materials that our Level 1 and Level 2 SRE Database Engineers will use as they onboard.
The ideal candidate will have strong experience with production database systems, Linux, automation, distributed systems, Kubernetes, observability, and incident response, with a proactive approach to reliability and operational excellence.
What You'll Do:
Database Architecture & Administration:
Design, deploy, and own highly available database architecture for Vitess (distributed MySQL) and Cassandra.
Establish and document operational procedures, runbooks, and escalation guidance for Level 1 and Level 2 SRE Database Engineers.
Optimize database performance through query tuning, indexing strategies, schema design, and capacity planning.
Own database backup, recovery, replication, and disaster recovery strategies.
Perform and validate disaster recovery testing and database recovery procedures.
Drive database security, access control, patching, hardening, and compliance practices.
Serve as an escalation point for complex database production incidents.
Partner with the DBA and Data Infrastructure teams on resharding, capacity planning, replication, and architecture decisions for sharded MySQL environments.
Service Reliability & Operations:
Support the availability and durability of critical services across production environments.
Monitor service health using SLIs, SLOs, error budgets, monitoring, logging, and alerting platforms.
Partner with service owners to define and improve SLIs, SLOs, error budget policies, and alerting.
Participate in on-call rotations, incident response, root cause analysis, and post-incident reviews.
Serve as an escalation point for complex production database and infrastructure incidents.
Follow established ITIL/OSS processes including incident, change, problem, and capacity management.
Take ownership of operational issues and drive projects from problem discovery through resolution.
Automation & Tooling:
Develop automation for common operational and database administration tasks to reduce manual intervention and operational toil.
Contribute to monitoring, logging, and alerting frameworks including Prometheus, Grafana, Catchpoint, and ELK.
Help integrate operational runbooks and incident response workflows with FireHydrant.
Work with CI/CD pipelines, configuration management, and infrastructure as code tools including Terraform, Ansible, and Jenkins.
Develop scripts using Bash, Python, Go, or similar technologies to improve reliability and operational efficiency.
Operate and troubleshoot containerized production environments using Kubernetes and Docker.
Work within Kubernetes and Vitess environments using technologies such as kubectl, mysqlsh, and Vitess keyspaces.
Work with HashiCorp technologies including Terraform, Vault, and Nomad.
Project Management & Collaboration:
Lead Production Readiness Reviews (PRRs) for functionality being handed off from engineering partner teams.
Support the operational readiness of new database-backed services before they enter production.
Build training plans, onboarding materials, and technical documentation for new Level 1 and Level 2 SRE Database Engineers.
Partner with Engineering, Product, Operations, and DBA/Data Infrastructure teams on reliability initiatives.
Assist with capacity planning, disaster recovery exercises, database migrations, and infrastructure projects.
Work with vendors and service providers to troubleshoot service issues and track SLA performance.
Identify opportunities for automation and process efficiency.
Share technical knowledge and help grow a reliability-minded engineering culture.
Incident Response:
Respond to and resolve production database, infrastructure, and service incidents.
Troubleshoot and escalate database, Linux, networking, application, and infrastructure issues as needed.
Participate in the on-call rotation and serve as an escalation point for database-related incidents.
Lead or contribute to root cause analysis and post-incident reviews.
Identify recurring issues and develop long-term corrective actions to improve reliability.
Design action plans to address recurring operational and database problems.
What We Value:
A proactive mindset with a can-do attitude.
Someone who can work independently, take ownership, and drive complex technical problems through resolution.
Someone who steps up, supports teammates, mentors others, and shares knowledge freely.
Strong problem-solving skills and a willingness to learn new technologies.
Curiosity, reliability, and a desire to improve the reliability and scalability of production systems.
Required Qualifications:
6–8 years of experience in site reliability engineering, systems engineering, infrastructure operations, database engineering, or similar roles, with meaningful experience supporting production database systems.
Deep hands-on experience with MySQL and distributed or sharded database systems.
Experience with Vitess in a production environment strongly preferred.
Experience administering and supporting NoSQL databases such as Cassandra.
Experience designing high-availability database architecture, replication topology, backup strategies, and disaster recovery processes.
Strong SQL skills, including query performance analysis, indexing, schema design, and troubleshooting.
Solid Linux systems administration and troubleshooting skills.
Experience with security-focused operations including patching, system hardening, access controls, and vulnerability remediation.
Strong understanding of service reliability concepts including monitoring, alerting, incident response, root cause analysis, SLIs, SLOs, and error budgets.
Experience working with containers and orchestration platforms including Kubernetes and Docker.
Comfortable operating in Kubernetes and Vitess environments using tools such as kubectl, mysqlsh, and Vitess keyspaces.
Experience with infrastructure and configuration management technologies including Terraform, Ansible, Jenkins, and HashiCorp products such as Vault and Nomad.
Proficiency in at least one scripting language such as Python, Bash, or Go.
Experience establishing operational procedures, runbooks, documentation, and escalation processes.
Experience mentoring, training, or helping onboard engineers into complex technical environments.
Experience supporting large-scale, production-grade systems.
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
Preferred Qualifications:
Direct production experience with Vitess.
Experience with large-scale distributed or sharded MySQL environments.
Experience with Cassandra or similar distributed NoSQL databases at scale.
Experience in SaaS, cloud services, service provider, or large-scale distributed systems environments.
Experience with AWS, GCP, Azure, or similar cloud platforms.
Familiarity with ITIL/OSS practices and SLA/SLO management.
Experience leading Production Readiness Reviews.
Experience developing onboarding or technical training materials for engineers.
Experience acting as a technical escalation point for database or infrastructure incidents.
At this point, we hope you're feeling excited about the job description you're reading. Even if you don't meet every requirement, we still encourage you to apply. Learning, developing, and growing are key parts of our culture. We're eager to meet people who believe in our mission and can contribute to our team in various ways. We want people to feel comfortable expressing their true selves and to come, stay, and do their best work here.
At Backblaze, we value being fair and good to our customers, partners, and employees. That’s why diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We believe that our dedication to cultivating a diverse workspace not only allows us to better serve our customers in over 175 countries, but further reinforces our commitment to doing the right thing. We are proud to be an Equal Opportunity Employer.
To understand more about the data we collect and process as part of your application, please view our
Backblaze Employee Privacy Notice.
На данный момент мы в поиске Senior DevOps Engineer Формат работы: Удаленный Локация и гражданство: РФ Оформление: только как ИП Сфера проекта: Нефтегазовая отрасль, enterprise-интеграции Роль предполагает не только DevOps-разработку, но и участие в архитектурных решениях: проектирование инфраструктуры с учётом требований платформы и последующая реализация.
Роль предполагает не только DevOps-разработку, но и участие в архитектурных решениях: проектирование инфраструктуры с учётом требований платформы и последующая реализация. ● Коммерческий опыт работы DevOps-инженером от 5 лет.
Задачи:
— Предоставление внутренних инструментов и облачных сервисов как услуги для всех продуктовых команд компании.
— Обеспечение масштабируемой и надежной основы для разработки.
Требования:
— Грейд Senior.
— Опыт работы с Kubernetes, Grafana, Yandex Cloud, Python, Terraform, Prometheus, Mimir, Alloy.
Условия:
— Удалённая работа.
- Разработка и поддержка CI/CD-процессов для сборки и доставки блокчейн-приложений. - Настройка, мониторинг и поддержка инфраструктуры в облачных средах (AWS, GCP, Azure).
Задачи:
— Функциональное тестирование интентов, включая проверку корректности распознавания запросов, слотов и сущностей, а также неоднозначных формулировок и нестандартных сценариев.
— Проведение E2E-тестирования полного цикла взаимодействия пользователя с голосовым ассистентом от запроса до ответа.
— Тестирование интеграций с внешними сервисами ASR, TTS, LLM и другими.
— Автоматизация тестирования с разработкой сценарных автотестов на Go или Python, формирование регрессионного набора и интеграция в CI.
— Мониторинг качества продукта в продакшене, выявление деградаций и предотвращение регрессий.
— Ручное исследовательское тестирование сложных диалоговых сценариев, поиск ошибок NLU и проверка поведения ассистента в нестандартных ситуациях.
— Работа с требованиями совместно с аналитиками и продактами: формализация требований, определение критериев приёмки и выявление потенциальных проблем на этапе проектирования.
Требования:
— Опыт работы в QA не менее 5 лет.
— Знание принципов работы голосовых ассистентов, NLU, интентов, слотов и сущностей.
— Опыт тестирования систем с недетерминированными ответами.
— Сильный опыт E2E-тестирования распределённых систем.
— Понимание REST, gRPC, очередей и межсервисных взаимодействий.
— Практический опыт написания автотестов на Go или Python.
— Умение самостоятельно проектировать тестовые сценарии и выстраивать стратегию тестирования.
— Готовность работать с неполными требованиями, задавать вопросы и влиять на качество продукта.
— Высокая самостоятельность, инициативность и системное мышление.
Будет преимуществом:
— Опыт тестирования голосовых ассистентов и диалоговых систем.
— Опыт работы с Kibana, Grafana, Prometheus, Sentry.
— Понимание тестирования stateful-диалогов и управления контекстом.
— Знание Docker и Kubernetes.
— Опыт построения мониторинга качества внешних сервисов и автоматизации регрессионного тестирования.
Задачи: разработка и поддержка CI-пайплайнов — сборка компонентов, автоматические проверки, публикация артефактов, подготовка тестовых окружений; автоматизация создания, настройки, обновления и удаления стендов разработки и тестирования;
В команду разработки СХД требуется разработчик C++ для разработки S3-шлюза, расширяющего функциональные возможности СХД заказчиков. Задачи: анализ существующего кода проекта, выявление узких мест и областей для улучшений;
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: Екатеринбург
Мы - команда сопровождения сервисов безопасности данных Сбера в Екатеринбурге. Обеспечиваем бесперебойную работу критически важных для всей страны цифровых продуктов.
В связи с активным ростом экосистемы, расширением числа продуктов и усложнением ландшафта киберугроз, мы ищем профессионала, который разделит наши ценности: надежность, проактивность и постоянное развитие.
Наши ключевые продукты:
Борьба с дипфейками: разработка и сопровождение систем определения искусственно сгенерированного контента.
Защита персональных данных: поиск конфиденциальной информации в массивах данных и её автоматическая деперсонализация.
Безопасность документов: защита файлов, содержащих коммерческую тайну и чувствительную информацию клиентов.
Обязанности
### **Чем предстоит заниматься:**
* поддержка автоматизированной системы и её сервисов
* релиз-менеджмент: сопровождение релизов, проведение приёмо-сдаточных испытаний, установка дистрибутивов на промышленные стенды
* работа с ITSM процессами
* обеспечение отказоустойчивости продукта
* развитие мониторинга системы
* управление конфигурацией инфраструктурных продуктов: PostgreSQL, Kubernetes, Kafka, Nginx, Ignite, Redis, S3
* автоматизация процессов управления, а так же разработка и поддержка процессов CI/CD (создание Jenkins Pipeline).
Требования
### От кандидата ждем:
* высшее образование
* опыт работы с OS Linux (RHEL - предпочтительно)
* работа с СУБД, составление SQL запросов
* понимание современных DevOps-концепций и опыт использования средств автоматизации DevOps
* понимание принципов виртуализации
* владение скриптовыми языками программирования (Bash, Ansible, Python, Groovy)
* опыт работы с Системами мониторинга (Zabbix, Grafana, Prometheus)
* опыт работы с Helm
* опыт работы с GIT/Nexus, Atlassian стеком (BitBucket, Jira, Confluence).
Будет плюсом:
* инструментальное владение AI для анализа, генерации и автоматизации.
Условия
### Мы предлагаем:
* работу в офисе Технохаб (Розы Люксембург, 56а)
* стабильный оклад и социальную поддержку сотрудников
* расширенный ДМС с первого дня работы для сотрудников и льготная медицинская страховка для близких
* ипотека выгоднее на 4 п.п. и льготные условия кредитования для каждого сотрудника
* бесплатная подписка СберПрайм с возможностью поделиться с тремя близкими
* скидки на продукты компаний-партнеров: Сбер Маркет, Delivery Club, Самокат, Сбер Еаптека и других
* корпоративную пенсионную программу
* корпоративное обучение за счет компании
* реферальную программу для сотрудников: можно пригласить в команду знакомых профессионалов и получить вознаграждение до 100 тыс. рублей
* корпоративный спортзал и скидки в спортзалы-партнеры
* мощное железо, дополнительные мониторы и всё, что нужно для продуктивной работы.
Автоотклики