Вакансии

Ищем Senior-специалиста на роль главного сетевого администратора, который возьмёт на себя ключевую часть сетевой и VPN-инфраструктуры проекта. Senior-уровень в сетях: TCP/IP, UDP, DNS, TLS/HTTPS, маршрутизация, NAT;

Location: Remote About GiveDirectly What if the most effective way to fight poverty was also the simplest: give people money and trust them to decide what they need? Since 2011, GiveDirectly has proven that idea at scale. We’ve delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries, and rigorous research shows the results: healthier kids, stronger businesses, sturdier homes, and more resilient families and local economies. Cash is now widely recognized as one of the most scalable, cost-effective, and dignified forms of aid. Our ambition goes beyond our own programs. We want cash to become the benchmark for aid, much as the index fund became the benchmark for investing, so that every aid dollar is held to one question: is this doing more good than giving the money directly to people living in poverty? We’re growing fast, and this is a rare and important moment to join. We expect to hit $1B in revenue in 2026 with significant growth forecast for 2027. At the same time we are building a new technology stack and operating model designed for a roughly 10x change in scale, and we are actively pursuing partnerships with major funders to move even more money in bigger ways, to people who need it. We are known for our extensive integration of technology into field processes; our quantitative approach to performance measurement; and our commitment to rigorous, independent, experimental evaluation of our impact, with multiple Randomized Control Trials completed and others in progress. How we work Our team spans 20+ countries and 69 languages. Our culture is candid, analytical, and non-hierarchical. We expect high ownership and give people real responsibility early. Our values are central to how we hire, work, and grow, and they are deliberately opinionated: Recipients first. Recipients’ preferences come before those of donors or ourselves. Team next. We optimize for organizational success, not individual success. Be proactively candid. We say what we believe and share information openly. Create positive energy. We aim to be a source of energy for colleagues, not a drain. Think rigorously; act quickly. We reason from first principles, then act rather than debate. Know yourself and grow. We own our imperfections and seek feedback to grow. Accept reality. Propose solutions. We focus on what can change and bring solutions, not just problems. Be productively ambitious. We take risks for step-change impact, not incremental progress. If they describe how you like to work and they energize you, this could be a great fit. Want to learn more? Read and listen: We are one of Time100’s Most Influential Companies of 2026, and our work has been covered by The Economist , NPR , TED , and The Washington Post . We're now preparing to deliver billions of dollars a year to people in extreme poverty, if funding allows. Read our CEO's essay on what that will take. About this role: Are you an experienced engineer at the stage of your career where, above all, you want to do good? This role is about using engineering to support fundraising: delighting our donors; helping our fundraisers; getting donations recorded and safely started on their journey to our recipients; telling donors and the public about what happens to their gifts. A bit of website development. A lot of plumbing. The good news about this position: You will make a difference to people in extreme poverty You will work independently, with few constraints You will work directly with lovely people from across our fundraising teams The trade-offs: There is only one other fundraising engineer and mostly you will be working on your own Our technology is a mixture of boring (Laravel, PHP, plain JS, HTML and CSS) and legacy (Salesforce, Wordpress, wrangling CSV files sent by our partners) We're growing, but this is a role for someone who values depth and impact over a fast title ladder. The maybe good maybe bad news about the role depending on who you are: We are all in on AI where it allows us to get more $ to people in extreme poverty If you want a role where you will be part of a bigger engineering team, working in Python or working on more complex tasks, then please take a look at our other engineering roles . This role is right for you if: You care about our mission You agree with our values You have the right to work in one of the countries we're able to hire from (you can check the current list here ). You're happy working remotely, and taking meetings across East Africa Time and US Eastern Time. You are happy to travel to meet your colleagues in the US, Europe and Africa a few weeks a year You are fluent in English You have 4+ years of engineering experience You're happy working autonomously: defining what needs doing, doing it, getting it tested and launched, fixing the bugs, and hustling to make progress every day. You're comfortable being on-call on peak donation days (Giving Tuesday and the last weeks of the year), including owning an incident: working out what matters, communicating with fundraisers, and debugging on legacy and others' code, sometimes when no other engineers are available. You are happy with our boring and legacy technologies (Laravel, PHP, plain JS, HTML, CSS, Salesforce, Wordpress, SQL, wrangling csv files etc). You don’t have to be experienced in all of them, but you do have to be genuinely happy to use them (many engineers are not…). You are happy and skilled at working directly with non-engineers on messy, poorly defined, rapidly changing, sometimes boring tasks Compensation At GiveDirectly, we strive to pay our employees generously and equitably. We use an accredited third party salary aggregator to calculate what we believe to be competitive pay based on role, location, and cost of living. We also have a no negotiation policy to ensure we are paying staff equitably across roles. Read more about our compensation philosophy here . Unless otherwise noted, the benefits stipend may be used to cover benefits or taken as additional taxable income. United States Base Salary: $181,130 Bonus at Target Performance: 15% (~$27,170, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~$31,789 in 2025) Estimated Total Compensation at Target: $208,300+ Annual Benefits Stipend: $21,393 United Kingdom Base Salary: £124,370 Bonus at Target Performance: 15% (~£18,656, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~£21,827 in 2025) Estimated Total Compensation at Target: £143,026+ Annual Benefits Stipend: £2,760 Kenya Base Salary: $112,350 Bonus at Target Performance: 15% (~$16,853, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be ~$19,717 in 2025) Estimated Total Compensation at Target: $129,203+ Annual Benefits Stipend: $8,453 This role is fully remote, so if you are not based in the US, UK or Kenya, we will share an estimated salary benchmark for the country you are based in during the hiring process. Why work at GiveDirectly? At GiveDirectly, we work to ensure that you have everything you need to excel in your role and on your team, including: A positive and supportive team with opportunities for advancement A demonstrated commitment to helping all staff develop and grow A competitive salary, including bonus A robust health benefits plan (exact details will vary by country) Unlimited PTO (that we encourage staff to take!) Desk allowance and flexible work location About this specific hiring process Take-home coding assignment Live Coding (60 mins) Systems Design (60 mins) Project Deep Dive + Behavioral (60 mins) *It’s possible that there will be adjustments to this interview process. Any changes will be communicated to you during the process. #LI-REMOTE Working at GiveDirectly GiveDirectly is an Equal Opportunity Employer. All qualified applicants are considered for employment without regard to the person’s race, color, religion, national origin, sex, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Flagging for US applicants: We invite you to " Know Your Rights " as an applicant. Commitment to Safeguarding As a global organization working with communities to eliminate extreme poverty, GiveDirectly takes the safeguarding of its recipients, staff, and partners seriously. To that end, GiveDirectly is a member of the Misconduct Disclosure Scheme , and will systematically check with previous employers about any abuse or misconduct related matters involving potential new hires. We may also employ other robust pre-hire screens, including in-depth reference checks, criminal background checks, and sanctions screens. These efforts help us continue to build and maintain trust with the communities we work with, and prevent abuse to our recipients and staff. **GD is committed to observing all local, national and international laws that protect people and basic human rights of all. GD is committed to a policy of “zero tolerance when it comes to preventing,  reporting, or responding to any form of abuse or  exploitation.” and expects anyone who works for GD to uphold the protection and safeguarding of our recipients as a priority.** Reasonable Accommodations We are committed to fostering an inclusive and accessible work environment. If you require any accommodations during the application or interview process, or to perform the essential functions of the role, please email us at careers@givedirectly.org with the email subject “Accommodation Needed”. We will work with you to ensure reasonable accommodations are made to support your needs. Want to put your best foot forward on your GiveDirectly application? Take a look at our Candidate Application Prep Guide ! Referrals Know the right person for this role? Please consider referring them . We offer a reward of $3,000 for a Senior Manager or above role, and $500 for a Manager role, paid if we end up hiring your referral. Thank you for sending great people our way!

Задачи: — Разрабатывать, строить и оптимизировать масштабируемые backend-системы для платформы оценки рисков. — Работать с высоконагруженными потоками данных, сервисами принятия решений в продакшене и интеграциями машинного обучения. — Сотрудничать с дата-сайентистами, аналитиками рисков и продуктовыми командами для создания надежных и высокопроизводительных решений. — Запускать стратегии оценки рисков для принятия решений в реальном времени. — Эволюционировать и адаптировать архитектуру в соответствии с текущими бизнес-планами. — Обеспечивать высокое качество реализации через комплексное покрытие тестами. — Проектировать и использовать инструменты для валидации изменений, чтобы они соответствовали бизнес-требованиям. Требования: — Опыт работы с Python не менее 4 лет. — Участие в разработке сервиса или подсистемы с нуля и успешный вывод в продакшн с бизнес-эффектом. — Глубокие знания Python и его экосистемы. — Понимание жизненного цикла программного обеспечения, применение методологии MVP. — Опыт с архитектурными паттернами и принципами проектирования. — Готовность брать ответственность за архитектурные решения сервиса. — Уровень английского B1 или выше для эффективного общения с международной командой. Условия: — Поддержка релокации в один из офисов: Кипр, Грузия, Сербия или Казахстан с помощью для сотрудника и его семьи. — Гибкий формат работы: из офиса или удаленно. — Медицинское страхование. — Бюджет на образование: языковые курсы, профессиональное обучение и сертификации. — Бюджет на оздоровление: компенсация расходов на ментальное здоровье и фитнес. — Отпуск: 20 дней оплачиваемого ежегодного отпуска и оплачиваемый больничный.

Задачи: — Готовить данные (API, SQL, файлы) и собирать прототипы для AI-ассистента до передачи в продакшен. — Подготавливать контекст для RAG, тестировать поиск и сопоставление сущностей. — Формировать golden dataset и автоматизировать тестирование ассистента (массовый прогон сценариев). — Считать метрики качества (retrieval, hallucinations) и локализовывать причины ошибок. Требования: — 5+ лет опыта в Data Engineering / разработке аналитических решений. — Уверенный Python и SQL, опыт с API, ETL/ELT, DWH. — Понимание принципов LLM, RAG, retrieval, embeddings (опыт работы — жирный плюс, но если глубоко погружен в тему — welcome). — Умение быстро собирать PoC, исследовать источники и находить нестандартные решения. Условия: — Удалёнка из любого города РФ или офис по желанию. — Оформление по договору ИП. — Зарплата 350 000 – 400 000 ₽ Gross.

Требования: — B.E/B.Tech/M.E/M.Tech в области электроники — Опыт работы в области верификации не менее 1 года

About this role As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale. This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses. What You Will Do: — Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance — Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability — Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns — Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow — Optimize performance, reliability, and cost of the ML platform — Evaluate and integrate emerging Databricks features — Stay ahead of the curve by engaging with the latest developments in machine learning and AI — Serve as senior ML technical advisor to Faire’s data science and production engineering teams — Represent Faire at ML conferences and meetups — Mentor ML engineers and raise the overall bar for Machine Learning at Faire What it takes: — 10-12 years of experience building and improving large-scale ML or data platforms — A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field — Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization — Proven ability to design systems that support multiple data science teams and production workloads — Strong background in distributed systems, ML infrastructure, and cloud architecture — Demonstrated technical leadership across teams and orgs; ability to influence without authority — Experience integrating LLM workflows into enterprise platforms is a plus — Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus Tech Stack: Faire uses a modern cloud based tech stack. For this role, you’ll want to be proficient with the following: — Languages: Python, SQL, Kotlin — ML Frameworks: PyTorch, PySpark, MLFlow — Big Data & Processing: Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL — Cloud & Infrastructure: AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform — Generative AI: Claude Sonnet 4.5, ChatGPT 5.2 Conditions: Hybrid work format with office presence 3 days per week (Tuesdays, Thursdays, and a flex day) and flexibility to work remotely up to 4 weeks per year. Remote work possible for candidates located in Ontario, Canada. Salary Range: $248,000 to $341,000 per year, eligible for equity and benefits. Actual base pay depends on skills, experience, market demands, and location. Base pay range subject to change.

Задачи: — Создавать и поддерживать платформу наблюдаемости, которая собирает телеметрию клиентов — события, логи и трассировки — с использованием OpenTelemetry и лучших отраслевых практик — Разрабатывать возможности дашбордов и визуализации для команд поддержки и полевых команд, обеспечивая видимость состояния системы в реальном времени, выявление проблем и трендов, а также помогать клиентам сохранять устойчивость в масштабе — Проектировать и реализовывать систему уведомлений и оповещений, основанную на данных телеметрии и эвристиках с использованием AI-агентов и lakehouse-интеллекта — Писать инфраструктуру как код с помощью Helm и Terraform для упрощения развертывания и эксплуатации внутри Dremio — Создавать и поддерживать фреймворки приложений, стандартизирующие разработку между командами, решая сквозные задачи, такие как внедрение зависимостей и контроль доступа на основе ролей в масштабе — Сотрудничать с командами SRE и DevOps для определения лучших практик и предоставления стандартизированных решений для общих инженерных рабочих процессов — Взаимодействовать с сообществом разработчиков для понимания их проблем и превращения этих знаний в улучшения платформы — Помогать определять и реализовывать дорожную карту и этапы интеграции с платформой SAP HANA/BDC для обеспечения единого опыта Требования: — Степень бакалавра, магистра или выше в области компьютерных наук или смежной области — Опыт работы в разработке программного обеспечения не менее 5 лет — Опыт работы с Java не менее 2 лет — Опыт работы с инфраструктурой как кодом (Helm, Terraform или эквивалент) не менее 2 лет — Глубокий опыт работы с одной из основных облачных платформ (AWS, Azure или GCP) — Практический опыт работы с OpenTelemetry или аналогичными платформами наблюдаемости — Опыт работы с Kubernetes и Docker — Хорошее понимание основ сетевых технологий (TCP/IP, DNS, HTTP) — Желание изучать новые технологии и умение решать сложные задачи Преимущества: — Опыт создания SaaS микросервисов и распределённых систем — Опыт работы с многопоточными или асинхронными моделями программирования — Владение NoSQL базами данных (MongoDB, RocksDB) или Redis — Опыт работы с CI/CD инструментами (Jenkins, ArgoCD) — Знание других языков программирования, таких как C++, Go, Python, Node.js, Rust и др. — Опыт в обработке запросов, распределённых системах, контроле конкуренции, репликации данных или системах хранения — Опыт настройки Java GC/heap, Apache Arrow, SQL операторов или оптимизации путей данных Условия: — Удалённая работа из Португалии или другого места — Полная занятость Компания Dremio — это платформа lakehouse для самообслуживания аналитики и ИИ, использующая открытые технологии, включая Apache Iceberg и Apache Arrow, обеспечивающая гибкость и скорость получения инсайтов при снижении затрат.

Задачи: — Настройка и поддержка ноутбуков, рабочих станций, программного обеспечения и учетных записей пользователей — Поиск и устранение неисправностей аппаратного обеспечения, программного обеспечения, сети и проблем с подключением — Поддержка сред Windows и Microsoft 365 — Обслуживание и устранение неисправностей систем видеонаблюдения (CCTV), контроля доступа, распознавания лиц и видеоконференций — Предоставление поддержки сотрудникам на месте и удаленно — Координация с поставщиками и сервисными провайдерами при необходимости Требования: — Опыт администрирования Windows и работы с компьютерным оборудованием — Базовые знания сетевых технологий (IP-адресация, DNS, DHCP, Wi-Fi) — Сильные навыки поиска и решения проблем — Хорошие коммуникативные навыки и ориентированность на клиента — Знание английского языка обязательно; знание русского и/или греческого будет преимуществом — Наличие водительских прав и собственного автомобиля желательны — Интерес к технологиям и готовность изучать новые системы Условия: — Зарплата €1,600–2,000 нетто в месяц, в зависимости от опыта — Профессиональная и международная команда — Возможности для профессионального роста и развития — 21 день оплачиваемого ежегодного отпуска — 5 дополнительных оплачиваемых дней больничного в год — Офис в Пафосе, Кипр — Рассматриваются кандидаты, уже проживающие на Кипре или готовые к самостоятельной релокации

Задачи: — Разрабатывать и улучшать RAG-приложения: chunking, embeddings, retrieval и reranking. — Строить LLM-воркфлоу и агентов с использованием LangChain, LangGraph, LlamaIndex, CrewAI или аналогичных. — Разрабатывать переписывание запросов, классификацию намерений, маршрутизацию и структурированное извлечение. — Интегрировать LLM API/модели в производственные системы. — Работать с OpenAI, Gemini, Hugging Face и PyTorch. — Вносить вклад в SFT, LoRA, QLoRA, PEFT и оценку LLM. — Работать с OCR, PDF/DOCX, STT и памятью для диалогов. — Создавать API с Python / FastAPI и работать с Docker, Git, тестированием и CI/CD. — Мониторить и улучшать качество моделей, задержки и стоимость. — Брать ответственность за отдельные функции/компоненты под наставничеством старшего инженера. Требования: — 2–4 года опыта в NLP / ML / Information Retrieval / Applied AI. — Сильные навыки Python. — Практический опыт с LLM / RAG / AI-agent приложениями. — Понимание трансформеров, embeddings, prompting, retrieval, chunking и reranking. — Опыт с LangChain / LangGraph / LlamaIndex / CrewAI. — Опыт с Qdrant / Pinecone / Milvus / Weaviate / Elasticsearch. — Опыт с OpenAI / Gemini / Hugging Face и знание PyTorch. — Понимание оценки LLM и снижения галлюцинаций. — Навыки FastAPI, REST, Docker, Git. — Многоязычный NLP будет плюсом. — Профессиональный английский. Желательно: — Знания SFT / LoRA / QLoRA / PEFT. — Знания BM25 / RRF. — Опыт с RAGAS / DeepEval / LangSmith / Langfuse. — Опыт с OCR/STT. — Опыт с Graph RAG. — Опыт с vLLM/TGI/Triton. — Оптимизация под GPU. — Знание корейского языка. Условия: — Работа в Инчхоне, Южная Корея. — Полная занятость. — Формат работы: офис / гибрид. — Конкурентная зарплата, обсуждается индивидуально. — Возможна поддержка с визой и релокацией.

Задачи: — работа с анимацией людей; — анимация техники; — работа с жидкостями; — настройка освещения (будет большим плюсом); — создание 30-секундного зацикленного ролика (loop). Требования: — умение работать с плагином ANIMA. Условия: — срок выполнения задачи — до понедельника. — оплата обсуждается индивидуально.

Задачи: — Разрабатывать и внедрять решения автоматизации на протяжении всего жизненного цикла сотрудника: от найма до увольнения — Использовать Low-Code / No-Code платформы для быстрого создания рабочих процессов, запуска автоматизаций и поддержки бизнес-пользователей — Моделировать и поддерживать базы данных HR, обеспечивая масштабируемость и надежность — Писать пользовательские скрипты на JavaScript для интеграций, трансформации данных, вызовов API и автоматизации рабочих процессов — Интегрировать HR-системы и внутренние инструменты через REST API, вебхуки, JSON, OAuth и другие распространённые методы — Работать с Airtable или аналогичными платформами для структурирования данных, создания кастомных представлений и триггеров автоматизаций — Мониторить и оптимизировать существующие автоматизации, анализировать метрики и устранять узкие места — Сотрудничать с HR, IT и заинтересованными сторонами для преобразования бизнес-процессов в технические рабочие процессы — Предлагать идеи, экспериментировать с новыми инструментами и улучшать процессы автоматизации — Документировать созданные решения, обучать коллег и создавать базу повторно используемых практик Требования: — Уверенные навыки моделирования баз данных: реляционные или полуструктурированные модели — Отличное владение JavaScript, включая асинхронные паттерны и модули — Опыт работы с Low-Code/No-Code инструментами (Make, n8n, Zapier, Power Automate, Retool, Bubble и др.) — Знание Airtable или аналогичных платформ будет плюсом — Понимание API, REST, вебхуков, JSON, OAuth и интеграционных паттернов — Способность анализировать и переводить бизнес-процессы HR в автоматизированные рабочие процессы — Аналитический склад ума, внимание к деталям и умение оптимизировать решения — Отличные коммуникативные навыки для взаимодействия с техническими и нетехническими командами — Самостоятельность и инициативность в работе — Уровень английского B2 и выше для эффективного общения в международной команде Плюсы: — Опыт работы в HR-технологиях, HRIS, финтехе или стартапах — Знание других языков программирования (Node.js, Python) и инструментов визуализации данных (SuperSet, Power BI, Tableau, Looker) — Знание SQL, облачных платформ (AWS, GCP, Azure) и RPA (например, UIpath) — Понимание вопросов конфиденциальности данных, соответствия GDPR и безопасности, особенно в HR — Готовность работать в условиях неопределённости и создавать новые системы Условия: — Поддержка релокации в Мексику для сотрудника и семьи — Гибкий формат работы: офис или удалённо — Медицинское страхование — Бюджет на образование: языковые курсы, профессиональное обучение и сертификации — Бюджет на здоровье: компенсация расходов на ментальное здоровье и фитнес — Отпуск: 20 дней оплачиваемого отпуска и оплачиваемый больничный

Задачи: — Владение AI-функциями от концепции до продакшена, интеграция LLM и кастомных моделей. — Работа с задачами реального времени в области live-стриминга: модерация контента, рекомендации и прочее. — Обучение и донастройка моделей на продакшен-данных с обеспечением производительности под реальной нагрузкой. — Оценка и выбор между созданием собственных моделей и покупкой готовых на основе данных. — Тесное сотрудничество с продакт-менеджерами и кросс-функциональными командами для разработки функций. Требования: — Опыт разработки ПО 5+ лет с практическим опытом работы с LLM. — Подтверждённый опыт обучения и деплоя моделей машинного обучения. — Сильные навыки Python и PyTorch, знание production-level сервинга. — Понимание принципов production engineering: мониторинг, отладка, оптимизация. — Английский на уровне Intermediate или выше. Плюсы: — Опыт работы с real-time видео/аудио инференсом, модерацией контента или рекомендательными системами. — Знакомство с ML инфраструктурой: Docker, Kubernetes, GCP. Условия: — Конкурентная зарплата, бонусы и опционы (все являются партнёрами). — Официальное трудоустройство на Кипре с поддержкой визы для сотрудника и супруга. — Комфортный офис в Лимассоле с питанием и перекусами. — Медицинская страховка: 100% для сотрудника, 75% для семьи. — Доступ к матчам и мероприятиям Aris Limassol F.C. — Возможности профессионального роста и командных активностей. Формат работы: onsite (офис в Лимассоле).

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: AI agents at Honeycomb investigate, reason, and act on real observability data. They live in Canvas: the agentic workspace where engineers go to understand their systems. The Agentic Intelligence team has shipped Canvas, the Honeycomb MCP server, and the Canvas Agent and Canvas Skills surfaces. What we're looking for today is someone who brings deep agent expertise and uses it to expand what the team can build: new agents, new surface area in Canvas, memory, spatial awareness, improved performance on our Bedrock loop. Honeycomb's data store is fast and accepts high cardinality data; that's what makes agents built on top of it different from anything built on a conventional observability backend. This role is about taking advantage of that building agents that can do things no other observability product can do because the underlying data makes it possible. Some of this work will start as a prototype. The expectation is that the code makes it through the full arc, from the rough first version through to something that holds up in production. What you'll do Design and deliver production-grade agents. Build agents that investigate, reason, and act on live observability data inside Canvas. These agents must be trustworthy to engineers in high pressure situations, including mid-incident. Take one from rough first version to something that holds up under production traffic. Own the agent work; support the whole product. Scope, build, ship, and maintain the agents including the evals that tell you whether they got better or are just different. This role is agent-focused and also includes some fullstack development. Build agents only Honeycomb can build. Use a data store that returns high-cardinality queries in seconds to reason over signal a conventional backend can't serve at this fidelity correlating across services, drilling into a single trace, comparing before and after a deploy. Extend the surface, and decide what's next. Ship new capability into Canvas, the MCP server, and Canvas Skills memory, spatial awareness, a faster Bedrock loop and make the case for what comes after with working code. Distinguish hype from signal in a field with plenty of both. Define what "good" means for agents here. Set the bar: measurable against real evals, maintainable, and honest about their limits. Example projects Multiple agents collaborating on one shared Canvas investigation each claiming a hypothesis, publishing findings, and narrowing the search space for the others so it resolves faster (blog). Auto-investigation the moment an SLO burn alert fires the agent forms hypotheses and prepares visualizations before a human looks, cutting mean-time-to-insight for on-call (o11ycon 2026). Skills that encode a team's domain expertise e.g. Kubernetes thresholds so agents and human colleagues can lean on them (o11ycon 2026). What you'll bring: AI and agent engineering experience. You've shipped LLM-based systems people relied on in production not demos, not fine-tuned models in a research context. You know where agent systems break and how to design around it. End-to-end ownership. On a small team there's no handoff queue. You can take something from rough prototype to production-grade without needing someone behind you to do the durable engineering. Current judgment, not just past experience. You have informed opinions about what's shifted in agent design in the last six to twelve months that would change how you'd build today. Agent architecture depth. You understand how a fast, high-cardinality data store changes what an agent can reason about, and how to design for that. Product judgment. You can look at what the agent layer does today and see what it should do next and make that case with a prototype, not a deck. Even better Observability or developer-tools background. Engineers are your users; you'll ramp faster with fluency in that world, and the work is better. Familiarity with eval frameworks, agent tooling, RAG, and prompt engineering. Base Salary based on level of experience $250,000 — $280,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Foster City, CA Workplace: Hybrid Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. ABOUT THE ROLE: Help turn “I built a business” into “I have customers.” As a Staff Software Engineer on Replit’s Money team, you’ll help shape Agentic Ads: an emerging area focused on using AI to make customer acquisition more accessible to businesses built on Replit.   This role focuses on intelligent, advertiser-facing software—not ad-serving infrastructure, an ad exchange, or a real-time bidding engine. You’ll tackle problems at the intersection of AI, business growth, measurement, and trustworthy automation, turning complex decisions into clear, useful experiences.   You’ll help define a new product area, working closely with product, design, and engineering to discover customer needs and deliver practical solutions. This is a hands-on Staff role: you’ll own architecture, lead delivery across teams, mentor engineers, and turn an ambitious vision into incremental customer value. YOU WILL: - Set technical direction for Agentic Ads, translating customer needs into an architecture and roadmap that balance rapid learning with long-term reliability. - Build agent-powered experiences that help businesses make informed growth decisions, translating user goals into understandable recommendations and appropriately authorized actions. - Design extensible integrations with external services, using well-defined APIs and abstractions that accommodate changing provider capabilities and requirements. - Partner with product and data teams to establish reliable measurement, connect product activity to business outcomes, and address data quality, delayed feedback, and uncertainty. - Develop intelligent automation that learns from performance signals and helps users improve outcomes within their goals and constraints. - Make financial control a product requirement: scoped authorization, explicit approvals, budget limits, auditable decisions, clear reporting, and reliable pause controls. Distinguish recommendations from actions that commit customer spend. - Make cross-platform workflows reliable with durable state, idempotency, safe retries, reconciliation, observability, and recovery from partial failures, expired credentials, rate limits, and provider API changes. - Establish agent evaluations and production monitoring for plan quality, tool selection, policy compliance, spend safety, and verified execution. Partner on experiments that distinguish attributed results from incremental customer value. - Lead ambiguous initiatives across product, design, AI, data, security, and partnerships. Stay hands-on with implementation, define incremental milestones, mentor engineers, and own the quality and operation of what the team ships. REQUIRED SKILLS AND EXPERIENCE: - A track record of Staff-level technical leadership on complex customer-facing products or platforms: setting direction, resolving ambiguity, and delivering through launch and production operation across multiple teams. - Strong hands-on software engineering and system design skills across APIs, data modeling, distributed systems, asynchronous workflows, and customer-facing product experiences. - Experience building and operating third-party integrations that remain correct under duplicate requests, partial failures, rate limits, changing schemas, and inconsistent external state. - Practical experience shipping LLM-powered products or agentic workflows, including tool use, orchestration, evaluations, and safeguards for actions taken against external systems. - Strong data and measurement judgment: experience using instrumentation and experiments to evaluate product outcomes, and the ability to reason about noisy data, delayed feedback, uncertainty, and correlation versus causation. - Sound judgment around systems that act on a user’s behalf, including authentication, authorization, sensitive data, approval boundaries, and limits on consequential actions. - Demonstrated ability to align cross-functional teams, explain technical trade-offs, mentor engineers, and drive execution without relying on reporting authority. - A product-minded approach to simplifying complex workflows for non-experts, with hands-on ownership from prototype through reliable production operation. PREFERRED QUALIFICATIONS - Experience building advertiser-facing products, marketing automation, campaign-management tools, growth platforms, or software that helps businesses acquire customers. - Experience integrating advertising or marketing APIs; familiarity with account onboarding, campaign lifecycles, and platform requirements. - Working knowledge of conversion tracking, attribution, customer acquisition cost, return on ad spend, budget pacing, and the limits of optimizing with low conversion volume. - Experience with experimentation, incrementality measurement, constrained optimization, recommendation systems, or decision-making under uncertainty. - Experience building permissioned, multi-tenant products with approval workflows, budget controls, audit trails, and privacy-aware handling of customer and conversion data.   BONUS POINTS: - Experience with agent tooling, durable workflow execution, delegated authorization, or evaluation frameworks for agents that take consequential actions. - Experience connecting application events or server-side conversion signals to advertising platforms, or integrating creative generation and landing-page experimentation into growth workflows. - Experience building for small businesses or first-time advertisers, where clear guidance, limited budgets, and sparse data shape the product. - These are additional strengths, not a checklist. Experience with every ad platform is not expected; ad-serving infrastructure experience and an ML research background are not prerequisites. WHAT WE VALUE: - Customer outcomes: success means helping a business acquire qualified leads and customers—not merely connecting an account, launching a campaign, or increasing spend. - User control and trust: agents explain recommendations, act within explicit authority, and make budgets, costs, and consequential changes understandable. - Evidence over activity: we validate measurement, acknowledge uncertainty, and test whether a change improves business outcomes rather than treating attribution as proof of causality. - End-to-end ownership: we own the journey from a business goal through campaign execution, measurement, and ongoing improvement. - Pragmatic technical leadership: we build on existing ad platforms, ship focused increments, and invest in correctness and extensibility where they matter. - Clear collaboration: we document decisions, surface risks early, and help other teams and partners succeed. Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑‍💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only) Want to learn more about what we are up to? - Self-driving Company https://replit.com/blog/self-driving-company - Replit Agent at Scale https://replit.com/blog/evaluating-and-improving-agent-at-scale - AI Adoption https://replit.com/blog/ai-adoption - Build Open-Source Apps https://replit.com/build/open-source-app-builder   Interviewing + Culture at Replit - Operating Principles https://blog.replit.com/operating-principles - Reasons not to work at Replit https://blog.replit.com/reasons-not-to-join-replit To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

Задачи: — Взять на себя ключевую часть сетевой и VPN-инфраструктуры проекта. Требования: — Senior-уровень в сетях: TCP/IP, UDP, DNS, TLS/HTTPS, маршрутизация, NAT; — серьёзный практический опыт с VPN, туннелированием и Xray; — опыт работы именно с крупными VPN-проектами; — глубокое понимание DPI, фильтрации трафика, блокировок и причин деградации соединений; — сильный Linux и сетевая диагностика; — опыт с dedicated-серверами, VPS/VDS, CDN, дата-центрами и хостинг-провайдерами; — плюсом будет практический опыт колокации собственного оборудования; — умение проектировать отказоустойчивую инфраструктуру, способную переживать сбои и изменения сетевых ограничений без постоянного ручного вмешательства; — способность быстро исследовать изменения в сетях, ставить эксперименты, находить причины проблем и внедрять решения; — постоянная погружённость в VPN-индустрию и понимание того, что в ней происходит прямо сейчас; — опыт работы в крупном VPN-сервисе и знание индустрии изнутри; — хорошее ориентирование в рынке хостингов и дата-центров, понимание особенностей разных провайдеров и умение строить масштабируемую и отказоустойчивую инфраструктуру для сотен тысяч пользователей; — VPN-инфраструктура и сети — основная профессиональная специализация. Условия: — полностью удалённо, full-time; — только основная работа — без параллельной работы и учёбы; — зарплата 350 000–1 000 000 ₽ на руки, итоговая сумма зависит от уровня, опыта и компетенций.

Задачи: — Взять на себя ключевую часть сетевой и VPN-инфраструктуры проекта. Требования: — Senior-уровень в сетях: TCP/IP, UDP, DNS, TLS/HTTPS, маршрутизация, NAT; — серьёзный практический опыт с VPN, туннелированием и Xray; — опыт работы именно с крупными VPN-проектами; — глубокое понимание DPI, фильтрации трафика, блокировок и причин деградации соединений; — сильный Linux и сетевая диагностика; — опыт с dedicated-серверами, VPS/VDS, CDN, дата-центрами и хостинг-провайдерами; — плюсом будет практический опыт колокации собственного оборудования; — умение проектировать отказоустойчивую инфраструктуру, способную переживать сбои и изменения сетевых ограничений без постоянного ручного вмешательства; — способность быстро исследовать изменения в сетях, ставить эксперименты, находить причины проблем и внедрять решения; — постоянная погружённость в VPN-индустрию и понимание того, что в ней происходит прямо сейчас; — опыт работы в крупном VPN-сервисе и знание индустрии изнутри; — хорошее ориентирование в рынке хостингов и дата-центров, понимание особенностей разных провайдеров; — VPN-инфраструктура и сети — основная профессиональная специализация. Условия: — зарплата 350 000–1 000 000 ₽ на руки, итоговая сумма зависит от уровня, опыта и компетенций; — формат работы полностью удалённый, full-time; — занятость только основная работа — без параллельной работы и учёбы. Для отклика нужно написать кратко о своём опыте: в каких VPN-проектах работали, их масштаб, зона ответственности, стек и наиболее сложные задачи.

Задачи: — Развивать и поддерживать IT-инфраструктуру. — Администрировать Linux/Windows, обеспечивать безопасность сетей. — Настраивать мониторинг, резервное копирование и защиту от угроз. Требования: — Опыт системного администрирования и сетевой безопасности. — Знание AWS, Bash, Prometheus, LXC, TCP/IP. — Опыт работы с SIEM, виртуализацией и сетевой безопасностью. — Английский уровень B2. Условия: — Полностью удалённая работа. — Полный рабочий день. — Оформление ИП/самозанятость или по договору ГПХ.