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Location: Canada (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 position. We are seeking candidates in US and Canada (EST/CST time zones) The Opportunity About Grafana Frontend The Grafana Frontend group is responsible for the end to end user experience on Grafana the observability product and Grafana the platform used by many engineers to build plugins. Our squads are responsible for dashboards, data visualization and manipulation, navigation across the ecosystem, sharing experience, content search,organisation and more. You'll also have the opportunity to work across the Grafana Frontend team and partner with other squads within the Grafana department to drive innovation and solve complex engineering challenges. The squad: DataViz We build and evolve the Grafana Visualizations. We want to give our users the ability to visualize their data in a way that’s easy to set up and understand, so they can pull out interesting and valuable insights. Some of our recent projects include: Externalisation of our core visualization to be independently releasable and remove interdependencies GraphViz : Visualize relationships, flows, and architectures using the Graphviz DOT language with live metrics from any Grafana data source. Raising the bar on quality and reliability: improving our test coverage, introduce a new testing strategy and tooling for visual regressions Refresh the look and feel of our existing visualizations . E.g Table and Gauge Our work is open source, you can browse grafana/grafana on GitHub directly to see how we build our software. Our stack is primarily Typescript, React, and uPlot and eCharts for our visualisations. What you’ll be doing Lead multi-quarter technical initiatives from problem framing through rollout. Including getting  user feedback and measuring whether what you shipped actually worked Mentor and collaborate with other engineers. Raise the engineering bar through code review, design feedback, pairing on hard problems, and writing that leaves the team better than you found it. Participate in on-call for the services you help build, and be a force multiplier in incident response and post-incident learning. Provide technical support in customer escalations and help us identify areas of high friction to address. Cross-squad collaboration: Represent the team's work outside the team, write the design proposals, run the demos, and make the case for our roadmap in cross-team discussion. 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 those who are intellectually curious , who default to transparency , possess a high bias towards action , and who are also kind and enjoy working as a team . Technical leadership . You have solid experience leading teams through projects, mentoring other engineers and serving as a force-multiplier. You communicate clearly in a fully remote, asynchronous environment. You take responsibility for operating the software you have built . You have experience being on-call, supporting software in production, ensuring reliability and responding to incidents as needed. You enjoy working on complex solutions ,  building production software systems. You’re a self-starter, capable of tackling complex engineering problems with minimal supervision. User focus and pragmatism . You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. AI experience with a practical mindset : You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. You care about our community of users and contributors and are keen to be an active Grafana Community Contributor. Bonus points for: Open-source contribution or maintainership, and comfort engaging a community in the open. Have an active interest in observability (Metrics, Logs and Traces) and have experience with tools like Grafana, Prometheus, or other observability platforms. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. In Canada, the compensation range for this role is $186,368 - $223,642 CAD. 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 States (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 position. We are seeking candidates in US and Canada (EST/CST time zones) The Opportunity About Grafana Frontend The Grafana Frontend group is responsible for the end to end user experience on Grafana the observability product and Grafana the platform used by many engineers to build plugins. Our squads are responsible for dashboards, data visualization and manipulation, navigation across the ecosystem, sharing experience, content search,organisation and more. You'll also have the opportunity to work across the Grafana Frontend team and partner with other squads within the Grafana department to drive innovation and solve complex engineering challenges. The squad: DataViz We build and evolve the Grafana Visualizations. We want to give our users the ability to visualize their data in a way that’s easy to set up and understand, so they can pull out interesting and valuable insights. Some of our recent projects include: Externalisation of our core visualization to be independently releasable and remove interdependencies GraphViz : Visualize relationships, flows, and architectures using the Graphviz DOT language with live metrics from any Grafana data source. Raising the bar on quality and reliability: improving our test coverage, introduce a new testing strategy and tooling for visual regressions Refresh the look and feel of our existing visualizations . E.g Table and Gauge Our work is open source, you can browse grafana/grafana on GitHub directly to see how we build our software. Our stack is primarily Typescript, React, and uPlot and eCharts for our visualisations. What you’ll be doing Lead multi-quarter technical initiatives from problem framing through rollout. Including getting  user feedback and measuring whether what you shipped actually worked Mentor and collaborate with other engineers. Raise the engineering bar through code review, design feedback, pairing on hard problems, and writing that leaves the team better than you found it. Participate in on-call for the services you help build, and be a force multiplier in incident response and post-incident learning. Provide technical support in customer escalations and help us identify areas of high friction to address. Cross-squad collaboration: Represent the team's work outside the team, write the design proposals, run the demos, and make the case for our roadmap in cross-team discussion. 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 those who are intellectually curious , who default to transparency , possess a high bias towards action , and who are also kind and enjoy working as a team . Technical leadership . You have solid experience leading teams through projects, mentoring other engineers and serving as a force-multiplier. You communicate clearly in a fully remote, asynchronous environment. You take responsibility for operating the software you have built . You have experience being on-call, supporting software in production, ensuring reliability and responding to incidents as needed. You enjoy working on complex solutions ,  building production software systems. You’re a self-starter, capable of tackling complex engineering problems with minimal supervision. User focus and pragmatism . You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. AI experience with a practical mindset : You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. You care about our community of users and contributors and are keen to be an active Grafana Community Contributor. Bonus points for: Open-source contribution or maintainership, and comfort engaging a community in the open. Have an active interest in observability (Metrics, Logs and Traces) and have experience with tools like Grafana, Prometheus, or other observability platforms. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. In the United States, the compensation range for this role is $174,986 - $209,983 USD.  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: Berlin Workplace: OnSite ABOUT PEEC AI AI search is changing how brands are discovered and chosen. People now ask ChatGPT, Gemini, Claude and Google’s AI answers what they used to search for, and AI assistants increasingly shape the journey from discovery to purchase. Winning customers now means winning over the AI systems that influence their decisions. Peec AI is an AI search platform that helps marketing teams understand and improve how their brands are discovered, represented, and recommended. We show them where they stand, what’s shaping it, and where to act. Since launching in January 2025, Peec AI has passed $20M ARR and 4,000 paying customers. We’re a Series A company backed by 20VC and Singular, with 100+ people across our Berlin HQ and our New York office. ABOUT THE ROLE We are hiring a Fullstack Engineer for our Growth team. You will run experiments across the whole self-serve journey: from the moment someone first hears of Peec AI to the day they renew, refer a friend or leave. That covers the website, signup, pricing and checkout, the trial and onboarding. It also covers the moments in the product where we ask people to do something, like connect a tool, invite a teammate or upgrade. You can work on any of these, and we decide together where the focus goes each month or quarter. You come up with the hypothesis, design the experiment and discuss it with the team. Then you run the rest of the loop yourself: build it, instrument it, ship it behind a flag, read the result and write down what happened. You report to the VP of Growth and work with our Growth PM, our growth engineer, and the marketing and design teams. WHAT YOU'LL DO - Go after big swings. We size every idea first and look for changes that could move a funnel step by 30 to 40 percentage points. It is fine if most of them fail. - Build and improve the experimentation infrastructure. Feature flags, assignment at the account level, exposure logged when someone becomes eligible, outcomes recorded on the server, and holdouts we read. - Keep conversion data accurate. Event design, funnel definitions and readouts the team can rely on. - Own what you ship after launch. You watch it, read the result on the date you set, and decide whether we keep it, change it or remove it. - Build internal tools that let the team run more experiments with less manual work. WHAT WE'RE LOOKING FOR - You have run growth experiments end to end. You formed the hypothesis, designed the test, built it and read the result. Not advised on them, not analysed someone else's. - You write production code today. Strong React and TypeScript on the frontend, comfortable in Node.js and databases on the backend. Our stack is React, Node.js and Next.js. - You know what your volume can detect. You can size a test, say how long it needs to run, and tell us when a result is not readable. - SQL and analytics fluency. Funnels, cohorts, event design. - B2B SaaS experience. - You ship with Claude Code, Cursor or equivalent. - Product judgement. You can tell which changes need a test, which can ship without one, and which are not worth building. - Product taste. You care about how the things you ship look and feel. You can turn an idea into a screen that belongs in our product, and you know when to bring in our design team. BONUS POINTS - You set up an experimentation practice from scratch and grew it into a regular part of how the team works. - Product-led growth experience. Onboarding, activation, paywalls, pricing, checkout. - Acquisition experience. Website and signup experiments, SEO or paid funnels. - Experiments on low-volume B2B funnels, where only big changes are readable. - Experimentation platforms and feature flags. Statsig, GrowthBook, PostHog, or your own. - Billing and subscriptions. Stripe or similar. - You founded a company, or you were an early engineer at one. - Side projects and experiments you can show us. WHAT WE OFFER - Exciting and challenging work with real impact and ownership at one of Europe's fastest-growing Series A startups - Regular team events and off-sites - Aggressive equity compensation package - Paid Dinner & Uber home when working late - The most beautiful office space and work environment in Berlin

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

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

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

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The IT Operations team keeps Anthropic running. We make sure every employee can do their best work without friction. We're hiring an IT Operations Engineer to develop our global asset management and hardware lifecycle program across our offices in San Francisco, New York, Seattle, London, Dublin and Sydney. You will bring program expertise to how we track hardware as inventory through its whole life: procurement and receiving, the inventory of record, assignment, refresh, collection and recovery, e-waste and secure disposal, and reseller relationships, iterating and scaling practices as we mature. The same person runs day-to-day operations for our corporate mobile program in addition to expertise in management of laptop and workstation lifecycle operations. You'll partner with several teams within the IT, Security and business operations organizations: IT Hardware Ops runs procurement, fleet logistics, onboarding and offboarding, the storage room, and physical intake. The Endpoint pod owns MDM, device policy and enrollment. Finance owns the budget and vendor contracts. Hardware requests that come through the IT Support queue land with the IT Support team, and you'll help define how they are handled. Responsibilities Strategy and Tooling Develop the global asset management strategy: the lifecycle model, the data we keep on every device, and how each office executes against it Select, implement and administer the asset management tool, define its data model and integrations, and partner with IT Engineering where the work needs platform-level access Contribute to and develop the processes on-site engineers in each office execute against, including the storage room process Support the evaluation and onboarding of a hardware lifecycle services vendor and, once in place, run the day-to-day relationship Inventory and Assignment Establish the inventory of record across systems and keep it accurate, from receiving through disposal: every device, its state, its location, and who has it Run audits of who-has-what and reconcile physical counts against the system of record Manage demo, loaner, and travel device inventories, ensuring devices are accurately tracked through complex logistical deployments Maintain up-to-date inventory counts and make strategic purchasing decisions in support new hire onboarding and peripherals stock levels Procurement and Refresh Support hardware purchasing through our reseller and vendor relationships, working from the refresh calendar Build out the refresh calendar and advance it across offices Reconcile purchase orders, deliveries and invoices with Accounting and vendors so that what was ordered, received, and billed line up Collection, E-waste and Disposal Develop device collection and recovery workflows: offboarding returns, refresh swaps, remote-employee returns and the BPO fleet, including the shipping and tracking that goes with them Build the e-waste program: certified recycling and secure disposal partners in each region, data destruction records, and the chain of custody from collection to certificate Handle equipment under legal hold or other chain-of-custody requirements BPO and Contingent Fleet Provision, track and recover the device fleet for our BPO partners, and be the day-to-day hardware contact for those vendors Corporate Mobile Run day-to-day operations for the corporate mobile program and write its runbook Manage deployment, break-fix, and carrier relationships associated with a mobile device fleet Automation Identify repetitive work throughout the operation and automate it with the tools at hand (scripts, systems integrations / connectors, AI tools) You may be a good fit if you Have implemented an asset management and lifecycle program for a multi-office fleet, not only run one: taken it from spreadsheets or nothing to a system of record and defined the processes around it (procurement, inventory, assignment, refresh, collection and disposal), ideally in a fast-paced or high-growth environment Have selected or implemented an asset management platform such as Jira Assets, Snipe-IT or similar, and developed the data model Have run an e-waste or secure disposal program with certified partners and chain-of-custody records Have managed reseller or vendor relationships for hardware purchasing and asset disposal Write things down: runbooks, how-to guides and knowledge base articles Recognize when a request reaches past this role and route platform work to IT Engineering, policy to the Endpoint pod, and budget to Finance Strong candidates may also Have supported a corporate mobile program or carrier account Have basic scripting experience (Bash or Python) for inventory or reporting automation Have experience using AI tools to improve personal or team productivity Have been the hands-on asset contact for an ISO 27001 or SOC 2 audit: pulled extracts from the register, produced disposal certificates and evidence of returned assets Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $180,000 — $230,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Ищем разработчика, который поможет выстроить тестовую инфраструктуру мобильного приложения Holisto и сделать разработку быстрее и стабильнее. Приложение уже имеет рабочую версию V3 на Flutter, которая тестируется на первых пользователях. В планах выпуск V4 с улучшениями по результатам beta-тестов и V5 для публичного запуска. Задача — работать с уже существующим продуктом, обеспечивая, чтобы новые изменения не ломали уже работающие функции. Задачи: — разобраться в существующем коде и логике V3 — восстановить требования по уже реализованным функциям — превратить основные сценарии в тест-кейсы — писать Flutter-тесты — постепенно покрывать критические пользовательские сценарии golden и E2E тестами — подключать тесты и покрытие к CI — ловить регрессии между версиями V3, V4, V5 — находить edge cases до того, как их обнаружат beta-пользователи — тестировать AI-функции Holisto, развивая подход к автоматическому тестированию LLM Особенность: значительная часть разработки автоматизируется через AI-агентов, тест-кейсы служат машинопроверяемыми контрактами, которые помогают выявлять ошибки до релиза. Требования: — знание Dart / Flutter на уровне чтения чужого кода и самостоятельного написания тестов — базовое понимание unit, widget, integration, E2E тестирования — умение точно формулировать требования — внимательность к деталям — интерес к AI / LLM и современной разработке — желание разбираться в существующем продукте, а не только писать новые функции — коммерческий опыт не обязателен, важна хорошая база и способность быстро разбираться Условия: — удалённая работа, частичная занятость, можно совмещать с учебой или основной работой — формат и мотивация обсуждаются отдельно в зависимости от опыта и уровня вовлечённости — возможно получение доли в зарегистрированной Delaware-компании — возможность перехода на оплачиваемый формат при хорошем результате — роль может вырасти вместе с engineering-командой Holisto Дополнительно приветствуется опыт работы с CI/CD, использование AI-инструментов в разработке, наличие GitHub / pet-проектов / примеров кода.

Задачи: — разобраться в существующем коде и логике V3 — восстановить требования по уже реализованным фичам — превратить основные сценарии в test cases — писать Flutter-тесты — постепенно покрывать критические user flows golden и E2E тестами — подключать тесты и coverage к CI — ловить regressions между V3 - V4 - V5 — находить edge cases до того, как их находят beta users — тестирование AI-функций Holisto, развивать подход к автоматическому тестированию LLM Требования: — Dart / Flutter на уровне «читаю чужой код и могу самостоятельно написать тест» — базовое понимание unit / widget / integration / E2E testing — умение точно формулировать требования — внимательность к мелочам — интерес к AI / LLM и современной разработке — желание разбираться в существующем продукте, а не только писать новые фичи — коммерческий опыт не обязателен Условия: — удалённая работа, частичная занятость (part-time) — можно совмещать с учебой или основной работой — формат и мотивацию обсуждаем отдельно в зависимости от опыта и уровня вовлечённости — возможно получение доли в уже зарегистрированной Delaware-компании — возможен переход на оплачиваемый формат при хорошем результате — роль может постепенно вырасти вместе с engineering-командой Holisto

Задачи: — разобраться в существующем коде и логике V3 — восстановить требования по уже реализованным функциям — превратить основные сценарии в test cases — писать Flutter-тесты — постепенно покрывать критические user flows golden и E2E тестами — подключать тесты и coverage к CI — ловить регрессии между версиями V3, V4, V5 — находить edge cases до того, как их находят beta users — тестирование AI-функций Holisto, развивать подход к автоматическому тестированию LLM Требования: — Dart / Flutter на уровне чтения чужого кода и самостоятельного написания тестов — базовое понимание unit, widget, integration, E2E testing — умение точно формулировать требования — внимательность к деталям — интерес к AI / LLM и современной разработке — желание разбираться в существующем продукте, а не только писать новые функции — коммерческий опыт не обязателен, важна хорошая база и способность быстро разбираться Условия: — удалённая работа, частичная занятость (part-time), можно совмещать с учебой или основной работой — формат и мотивация обсуждаются отдельно в зависимости от опыта и уровня вовлечённости — возможно получение доли в зарегистрированной Delaware-компании — возможен переход на оплачиваемый формат при хорошем результате — роль может вырасти вместе с engineering-командой Holisto Особенности: — значительная часть разработки автоматизируется через AI-агентов — тест-кейсы являются машинопроверяемыми контрактами — поддержка тимлида, помощь с погружением и review каждого PR Дополнительно: — приветствуются примеры кода, GitHub, pet-проекты — в отклике желательно указать опыт с Dart / Flutter, виды тестов, опыт с CI/CD, используемые AI-инструменты, время, готовое уделять проекту

Задачи: — разобраться в существующем коде и логике V3 — восстановить требования по уже реализованным функциям — превратить основные сценарии в test cases — писать Flutter-тесты — постепенно покрывать критические user flows golden и E2E тестами — подключать тесты и coverage к CI — ловить регрессии между версиями V3, V4, V5 — находить edge cases до того, как их находят beta users — тестирование AI-функций Holisto, развивать подход к автоматическому тестированию LLM Требования: — Dart / Flutter на уровне чтения чужого кода и самостоятельного написания тестов — базовое понимание unit, widget, integration, E2E testing — умение точно формулировать требования — внимательность к деталям — интерес к AI / LLM и современной разработке — желание разбираться в существующем продукте, а не только писать новые функции — коммерческий опыт не обязателен, важна хорошая база и способность быстро разбираться Условия: — удалённая работа, частичная занятость (part-time), можно совмещать с учебой или основной работой — формат и мотивация обсуждаются отдельно в зависимости от опыта и уровня вовлечённости — возможно получение доли в зарегистрированной Delaware-компании — возможен переход на оплачиваемый формат при хорошем результате — роль может вырасти вместе с engineering-командой Holisto Особенности: — значительная часть разработки автоматизируется через AI-агентов — тест-кейсы являются машинопроверяемыми контрактами — поддержка тимлида, помощь с погружением и review каждого PR Дополнительно: — приветствуются примеры кода, GitHub, pet-проекты — в отклике желательно указать опыт с Dart / Flutter, виды тестов, опыт с CI/CD, используемые AI-инструменты, время, готовое уделять проекту

Responsibilities: — Develop high-quality features and improvements in React and TypeScript, focusing on maintainability and readability. — Own features end-to-end across the UI, BFF, and async jobs, integrating with Java backend services. — Integrate UI with backend services, consuming and shaping their APIs. — Participate in design discussions and contribute to UI architecture, state boundaries, and API contracts. — Build and maintain BFF endpoints using Node.js and Fastify for UI-specific data shaping. — Design async flows for long-running analyses using BullMQ, ensuring retry-safe, idempotent jobs with clear UI status. — Optimize data-heavy reporting views with virtualization, pagination, and backend aggregation. — Use AI-assisted development tools (e.g., Claude CLI / Claude Code) efficiently, applying good judgment. — Evaluate trade-offs considering simplicity, cost, stability, and performance. — Collaborate with the team to break down work, estimate tasks, and deliver incrementally. — Work closely with backend, product, and data teams for smooth feature integration. — Engage actively in code reviews to maintain high-quality standards. — Keep up with industry trends and suggest practical improvements. Qualifications: — 7+ years of hands-on frontend development experience with strong React and TypeScript skills. — Experience owning frontend features end-to-end in production with clear separation of concerns and safe typing across API boundaries. — Solid understanding of frontend performance and scalability including re-render costs, virtualization, pagination, and progressive loading. — Comfortable working across frontend/backend boundaries, integrating with backend services and designing API contracts. — Proficient with AI-assisted development tools, able to decompose complex tasks, supervise workflows, review generated code critically, and ensure correctness, security, testing, and maintainability. — Experience with Vite (build configuration, code-splitting, developer experience) is a plus. — Experience with SQL and NoSQL databases. What we offer: — Referral Program to help grow the team. — Premium IT Equipment such as MacBook Pro or hardware of choice. — Excellent work-life balance with flexible hours and full remote possible. — Competitive compensation and benefits package. — Opportunity to work alongside top experts worldwide contributing to the Java ecosystem.

Задачи: — Отвечать за часть системы целиком в области Web Scraping, Data Engineering, AI и автоматизации для зарубежных клиентов. Требования: — Опыт продакшн-разработки на Python не менее 3 лет. — Уровень Middle, способный самостоятельно вести часть системы. — Ежедневная работа с LLM и агентами. — Проактивность и умение дебажить чужой код в продакшене. Условия: — Зарплата до 2500 долларов США на B2B. — Полная удалённая работа (кроме России). — Гибкий график. — Оплата AI-тулинга. — Процесс найма: интро-звонок, технический разговор, оффер. Технологический стек: Python 3.12, FastAPI, Celery, RabbitMQ, Redis, PostgreSQL, Playwright, Docker, Kubernetes, OpenTelemetry.

Action1 предоставляет облачный подход к управлению обновлениями, защите эндпоинтов и повышению производительности в области IT. Компания вошла в Inc. 5000 как самая быстрорастущая founder-led компания по кибербезопасности в США. Фаундеры — Alex Vovk и Mike Walters, основатели Netwrix, которую продали в 2018 году. В компании работает много русскоязычных сотрудников. Размер команды — 51-200 человек.

Компания Action1 предоставляет облачный подход к управлению обновлениями, защите эндпоинтов и повышению производительности в области IT. Компания входит в Inc. 5000 как самая быстрорастущая founder-led компания по кибербезопасности в США. Фаундеры — Alex Vovk и Mike Walters, основатели Netwrix, которую продали в 2018 году. В компании работает много русскоязычных сотрудников. Технологии и инструменты, используемые в работе: Python, uv, FastAPI, PydanticAI, PostgreSQL, Docker, Docker Compose. Размер команды — 51-200 человек. Формат работы — удалённый (Remote) из ряда стран.

Задачи: — заниматься безопасностью корпоративной Wi-Fi и локальной сети; — работать с сегментацией, WPA3, гостевым трафиком и контролем подключаемых устройств; — проводить security review рабочей платформы: проверять конфигурации, открытые порты и эндпоинты, типовые уязвимости; — выполнять точечные задачи по инфраструктурной безопасности совместно с CSO. Требования: — практический опыт в сетевой безопасности; — понимание принципов защиты сетевой инфраструктуры; — готовность работать из офиса; — ответственность и умение доводить задачи до результата. Будет плюсом: — опыт web- или инфраструктурных security-аудитов; — учебные проекты / pet-projects в security; — опыт в iGaming, платежных компаниях или другой регулируемой сфере. Отдельно ценится техническая аккуратность при работе с production: важно понимать границы допустимых действий и уточнять, что именно можно тестировать в боевом контуре.