About Magic Eden and Dicey
Magic Eden reached unicorn status in just 9 months after launch, one of the fastest in history. They built a category-defining NFT marketplace from scratch and are now developing Dicey, a crypto casino and sportsbook platform targeting the $180B+ iGaming and sports betting markets. The team is small and fully remote, focusing on fast shipping, data-driven decisions, and rebuilding growth operations around AI.
The role
The position focuses on personalized retention in the iGaming industry, owning the full post-signup journey. Responsibilities include expanding the player segmentation framework, designing and running targeted offers and campaigns, and managing the associated P&L lever. The role is explicitly AI-native, involving building workflows, agents, and pipelines to run lifecycle campaigns efficiently. Half the job is problem identification, the other half is running experiments to find solutions.
What you'll do
— Own retention and monetization as a growth loop, setting targets, finding leverage, and driving post-signup metrics
— Own and evolve the player segmentation framework, deciding signals and company usage
— Build the AI-native growth stack including analysis, agents, and automated pipelines for segment surfacing, offer generation, and campaign execution
— Design and ship targeted offers such as reload bonuses, lossback, wager bounties, challenges, and win-back sequences; size, specify, ship, and measure them
— Analyze data warehouse and on-chain data to find patterns and create campaigns proactively
— Expand player signals including on-chain activity, status-match programs, social account linking, and others
— Run campaigns across channels like email, in-app, Telegram, with AI handling heavy lifting
— Collaborate with engineering and design to create product surfaces that enable repeatable processes
What they're looking for
— Strong intuition for player psychology and incentive design; experience in gambling, gaming, fintech, or consumer marketplaces is helpful
— Deep analytical skills, able to independently perform cohort analyses without waiting for data scientists
— AI-native mindset, already using AI to write queries, build analyses, and automate work, with desire to advance further
— High output with good judgment, generating many ideas and prioritizing tests effectively
— Bias to do it yourself, comfortable executing emails, queries, and specs personally
— Comfortable with ambiguity and building new playbooks
Backgrounds that tend to fit
— Growth PM at data-heavy consumer companies
— MBB consultants transitioning to product ownership
— Product-minded data scientists or analysts focused on shipping rather than reporting
Why this is interesting
— Competitive, top-of-market compensation
— Defining the role of a growth PM in an AI-native company without existing playbooks
— Early involvement in personalized retention, a key industry trend
— Real ownership of segmentation framework, product surface, and P&L lever with direct access to founders
СберЗдоровье — аккредитованная IT-компания и одна из крупнейших Digital Health платформ в России. Компания развивает новое направление AI-native продуктов: мобильное приложение, ИИ-помощник, персонализированный риск-профиль и сервисы для улучшения понимания здоровья пользователя.
Ищут Middle / Senior Python Backend Developer. Основной фокус роли — backend-сервисы, API, интеграции, работа с данными пользователя и production-контур для AI-сценариев. Роль не связана с ML Engineer или research, а требует сильной backend-инженерии с использованием FastAPI, Pydantic, PostgreSQL, Redis, интеграций, надежности, безопасности и observability. Работа в кросс-функциональной команде с ML, Mobile, Frontend/PWA, QA, SA и Product.
Задачи:
— Разрабатывать и проектировать backend-сервисы на Python / FastAPI.
— Проектировать и поддерживать REST API для мобильного приложения, PWA, риск-профиля и ИИ-помощника.
— Описывать и поддерживать контракты API: request/response schemas, validation, error model, versioning.
— Работать с Pydantic, PostgreSQL, Redis и при необходимости S3-compatible storage.
— Интегрироваться с AI/ML-слоем: n8n-прототипы, FastAPI/FastMCP-сервисы, LLM API, RAG/context, Qdrant, traces.
— Строить observability: structured logs, trace/request id, metrics, dashboards, error tracking.
— Писать поддерживаемый код, покрывать критичную логику тестами, участвовать в code review и технических обсуждениях.
Требования:
— Опыт backend-разработки на Python от 3 лет.
— Хорошая база в технологиях веба: HTTP, контейнеры, хранение, веб-серверы.
— Практический опыт разработки production API на FastAPI, Django, Flask или аналогичном backend-фреймворке; FastAPI будет сильным плюсом.
— Уверенное владение Python.
— Здравый смысл в использовании ИИ-агентов.
— Хорошее понимание PostgreSQL: схемы, связи, индексы, транзакции, миграции, профилирование запросов.
— Опыт проектирования REST API и умение договариваться о контрактах с mobile/frontend/SA/QA.
— Опыт работы с микросервисами.
— Умение писать тесты для критичной backend-логики.
— Готовность работать в продуктовой команде с быстро меняющимися требованиями, где API влияет на mobile, PWA и AI-сценарии.
Будет плюсом:
— Опыт работы с очередями: Kafka/RabbitMQ, Celery.
— Понимание зоны ответственности AI/ML и классического Python-сервиса.
— Знание AI/ML инструментов и подходов.
— Опыт в MedTech, HealthTech, FinTech или других доменах с чувствительными данными.
Требуется инженер, который понимает продуктовый сценарий, умеет уточнять требования, думает контрактами, состояниями, ошибками и edge cases, строит надежные интеграции с backend, mobile, PWA и AI-слоем, пишет поддерживаемый код, умеет работать с логами, trace id и production-инцидентами, аккуратно относится к медицинским и персональным данным.
Условия:
— Возможность строить AI-native health-продукт с нуля.
— Быстрый путь от backend-решения до мобильного пользовательского сценария.
— Сложные задачи на стыке backend, AI, медицинского контекста и пользовательских данных.
— Работа в кросс-функциональной команде с Product, TL, ML, Mobile, Frontend/PWA, QA, SA, DevOps/MLOps и медицинскими экспертами.
— Удаленный формат внутри РФ или офис в Москве.
— Корпоративная техника.
— Медицинская программа с телемедициной, очными приемами, психологами, стоматологией, лабораторными и инструментальными диагностиками.
— Оплачиваемые курсы английского языка.
— СберУниверситет и оплата профильного обучения и курсов.
— Поддержка спорта и wellbeing-программы.
Условия:
— Офис в Алматы, гибридный формат работы, график 5/2
— Корпоративное обучение за счёт компании, доступ к Choco University (AI-навыки, Vibecoding, AI-агенты)
— Корпоративная библиотека, ChocoFest, Speaker Day, Boosting Day
— Менторская система при онбординге для быстрого вхождения в проект
— Небольшая команда, тесное взаимодействие с CTO и минимум лишних согласований
— AI-native процессы: использование AI-инструментов в ежедневной разработке, развитие агентных подходов и автоматизации
ГибридseniorАлматы
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О проекте:
Мы строим Customer Intelligence & Personalization Platform для зарубежной экосистемы бизнесов.
Задачи:
— Принимать технические решения и самостоятельно реализовывать ключевые части платформы.
— Владеть архитектурой и развитием Data Core.
— Проектировать слои Bronze / Silver / Gold и модели данных.
— Исследовать банковские, legacy- и внешние источники, восстанавливать их семантику.
— Строить pipelines от raw-данных до подготовленных data products.
— Разрабатывать трансформации на SQL / dbt / Python.
— Определять инженерные стандарты для ELT, data modelling, metadata, lineage и data quality.
— Развивать data catalog и metadata-as-code подход.
— Проектировать data contracts и интеграции Data Core с другими компонентами.
— Переводить исследовательские решения и ручные процессы в production.
— Работать с Git, CI/CD, Docker, Linux и закрытыми Dev/UAT-контурами.
— Взаимодействовать с инженерами и data scientist в команде.
Требования:
— Опыт работы Lead / Staff / Principal Data Engineer или сильного Senior с архитектурным ownership.
— Опыт проектирования и самостоятельной реализации data platform / DWH / Lakehouse.
— Знания Core banking / legacy banking systems.
— Опыт с Customer 360 / Golden Record / MDM.
— Сильный SQL и уверенный Python.
— Опыт работы с dbt или аналогичными transformation frameworks.
— Опыт работы с Airflow / Dagster / Prefect или аналогами.
— Хорошее понимание data modelling, historization, grain и master entities.
— Практический опыт data quality, lineage и metadata management.
— Знание Data Vault 2.0.
— Опыт работы с OpenMetadata или другими data catalog solutions.
— Умение самостоятельно принимать технические решения и отвечать за результат.
— Опыт работы с плохо документированными источниками.
— Навыки работы с Git, CI/CD, Docker, Linux.
— Практический AI-native способ разработки.
Условия:
— Оформление: ИП.
— Формат работы: полная занятость.
— Локация: Ереван либо готовность к регулярным командировкам (до 2 раз в месяц на несколько дней) в Ереван для работы с данными и специалистами заказчика.
— Уровень дохода обсуждается индивидуально.
About CircleCI Engineering:
CI/CD is being reinvented with AI agents that write code, trigger builds, interpret failures, and propose fixes. CircleCI is building new interfaces for developers to understand and trust this work.
Team-Agnostic Placement:
Hiring is for CircleCI as a whole, not a specific team. Placement depends on where your strengths create the most leverage. Possible areas include CI pipeline experience, deploy and release tooling, notification infrastructure, monetization flows, AI agent surfaces, or the foundational web platform. The role involves full-stack ownership and high craftsmanship.
What You'll Do:
— Build AI-natively, using AI as the default approach to problem solving.
— Invent new interfaces for software delivery that support autonomous pipelines and human judgment.
— Own the full stack by building features end-to-end in Go, React, and TypeScript.
— Focus on reliability and responsiveness as design concerns.
— Champion observability using Honeycomb, Datadog, and Rollbar to improve systems.
— Proactively identify and close gaps without being asked.
What You'll Bring:
— AI-native engineering practices with daily use of AI tools and understanding of their impact.
— At least 3 years of production full-stack experience with a track record of shipping real products.
— Strong skills in React and TypeScript, and comfortable owning backend services in Go including API design, data modeling, and service integration.
— System design skills with conscious tradeoffs and documentation.
— Production mindset focusing on latency, responsiveness, and reliability in distributed environments.
Additional Information:
The role is remote based in Ontario, Canada. Salary range is $127,000 to $159,000 CAD per year. CircleCI is an equal opportunity employer and provides accommodations for individuals with disabilities during the application and interview process.
Plurio (ex-Elly Analytics) — AI-платформа для перформанс-маркетологов, которая автоматизирует анализ кампаний, находит точки роста и перераспределяет бюджеты без ручной работы. Компания работает в сегменте B2B на рынке США. Размер команды — 50+ человек, инвестиции — более $5.5M (AltaIR Capital, DVC и другие).
Требования:
— Опыт медиабаинга для крупных клиентов с бюджетами на performance-маркетинг от $500к в месяц
— AI-native
— Свободный английский язык
Условия:
— Удалённая работа с пересечением часовых поясов US / EMEA
Фаундеры: Всеволод Устинов и Кирилл Касимский, с опытом более 20 лет в рекламном бизнесе.
Typeform is a form builder helping over 150,000 businesses collect data with forms, surveys, and quizzes. The company is fully remote and hires candidates based in the UK, Ireland, Germany, Portugal, or The Netherlands.
Product Operations is central to how Product and R&D teams work, creating systems and practices to focus on solving the right problems and delivering products. AI is increasingly important, with teams experimenting with tools like Glean and Claude, automations, agents, and AI usage throughout product development.
The role of AI Product Operations Lead involves building and operating internal AI Operations capability for R&D. It requires turning ambiguous opportunities into reliable solutions by identifying high-value AI problems, understanding workflows, designing solutions, building or coordinating delivery, and being accountable for performance after launch.
Responsibilities include:
— Building and improving a backlog of AI opportunities across R&D, prioritizing impactful AI jobs.
— Taking ambiguous problems from discovery to delivery: understanding users and workflows, exploring options, designing systems, implementing, testing, documenting, launching, measuring, and improving.
— Designing simple AI-native solutions fitting naturally into workflows, deciding when prompts, automations, integrations, agents, databases, or custom apps are appropriate.
— Helping R&D get value from enterprise AI tools like Glean and Claude, partnering with IT and InfoSec on access, configuration, connectors, enablement, and support.
— Owning the lifecycle of AI systems including automations, skills, agents, and internal web apps.
— Establishing evaluation, testing, reliability, observability, security, and maintenance practices, improving systems over time.
— Partnering across R&D to uncover needs, unblock delivery, clarify ownership, and involve experts.
— Running and evolving R&D AI governance and enablement practices, providing leaders visibility into work, risks, adoption, and outcomes.
— Participating in broader AI governance efforts as an R&D contributor.
— Working with Finance and partners to improve visibility into AI tool usage, spend, and value to inform investments.
— Exploring and supporting autonomous agents to improve planning, discovery, design, build, evaluation, and management across product development.
Requirements:
— Strong practical experience applying AI to real-world problems, building usable solutions.
— Proven track record taking ambiguous problems from discovery through implementation, testing, adoption, and improvement.
— Excellent systems thinking to understand people, processes, tools, data flows, integrations, permissions, and constraints, making trade-offs.
— Strong user and workflow discovery skills to understand real jobs and simplify solutions.
— Hands-on technical fluency building, modifying, troubleshooting internal workflows, automations, agents, or apps.
— Practical experience with modern development tools like GitHub, repositories, pull requests, application hosting, deployment, logging, and troubleshooting.
— Ability to manage work independently: prioritizing backlog, handling dependencies and risks, documenting decisions, communicating with stakeholders.
— Strong approach to evaluation and reliability, defining "good", testing, collecting feedback, and improving live systems.
— Ability to work effectively across technical and non-technical teams, asking questions, challenging assumptions, seeking expert input, and progressing without close supervision.
— Good judgment on responsible AI, security, access, governance, and knowing when to involve partners.
The role reports to VP of Product Operations and collaborates with Product, Engineering, Design, Research, Data Science, IT, InfoSec, and AI practitioners across Typeform.
About Peec AI
Peec AI is the visibility platform for the age of AI search. The way people discover brands is being rewritten. ChatGPT, Claude, Google AI Mode and Copilot now sit between companies and their customers, and most brands have no idea what those models say about them. We built the platform marketing teams use to measure, understand and improve how they show up inside AI answers. We went from 0 to $15M ARR in 18 months. We're around 80 people, based in Berlin with a growing presence in New York, and we're moving fast enough that the people joining now are writing the playbook everyone after them will run. The core Peec AI product is how a brand sees itself inside AI search. Most of what it needs to become has not been built yet, and this PM will define and own it. We're looking for someone to decide what an entire product surface should be and then ship it.
What You'll Do
— Take new product areas from nothing to shipped, owning the problem end to end
— Define what a brand's presence inside AI search should look like, working directly with our founders and customers on a category that is still being written
— Go broad on the problem space before narrowing on solutions, and hold that discipline when everyone wants an answer immediately
— Partner with Data, Engineering and Design to build and launch AI-native features at scale
— Set the bar for how the product looks and feels, not just what it does
— Own the customer relationship for your product area. Discovery calls, onboardings, and see people actually use what you built
Who You Are
— 3+ building excellent software products, ideally at a startup or fast-moving company
— You have built new products rather than maintained and improved existing ones, and you can point to what you shipped
— Experience shipping AI-powered products and systems that operate at scale
— Genuine design judgement
— Technical enough to work as a peer with engineers and data scientists
— Experience in a product-led growth environment
— You operate with very little direction. You pick up an ambiguous area and come back with a direction
— Excited to be in our Berlin office five days a week
— We care more about what you have built than how long you have been building. If you have fewer than three years but the work speaks for itself, apply anyway.
Bonus Points
— A design background, or a portfolio of things you have designed yourself
— Previous founder experience
— Background in Computer Science or a technical field
— Previous experience building AI-driven or search-related products
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
Plurio (ex-Elly Analytics) — AI-платформа для перформанс-маркетологов, которая автоматизирует анализ кампаний, находит точки роста и перераспределяет бюджеты без ручной работы. Компания работает в сегменте B2B на рынке США. Размер команды — 50+ человек, инвестиции — более $5.5M от AltaIR Capital, DVC и других.
Требования:
— Релевантный опыт работы с крупными рекламными аккаунтами с бюджетом от 500 тыс. долларов в месяц
— Опыт работы с AI-native технологиями
Условия:
— Удалённая работа с пересечением часовых поясов US / EMEA
Фаундеры компании: Всеволод Устинов и Кирилл Касимский, с опытом более 20 лет в рекламном бизнесе.
Plurio is an AI agent that automates media buying on Meta, Google, and TikTok for teams spending $300K–$15M a month, handling daily analysis, optimization calls, and execution directly in ad accounts. The system runs $500M+ per year in ad spend and has grown 5× since March. The AI marketing engineer role involves owning the client's marketing targets and improving metrics by automating media buying.
Задачи:
— Onboard clients by connecting their full-funnel data and ad accounts, setting business context including unit economics, P&L, products, geos, funnels, and media buying playbook.
— Adapt and build automation skills and rules from Plurio's catalog or create new ones as needed, backtesting on historical data before deployment. Rules are deterministic SQL with campaign logic and guardrails.
— Explain agent decisions and methodology changes to clients' Heads of UA and CMOs, assist marketers in running the agent, and handle discussions about spend and KPIs.
— Standardize successful approaches into reusable templates and methodologies for future clients.
Требования:
— Managed approximately $500K+/month in ad spend hands-on on one or multiple channels (Meta, Google, TikTok).
— Deep understanding of buying mechanics: account structure, optimization events, creative testing thresholds, scaling, burnout, budget allocation, attribution windows.
— AI-native with experience automating parts of buying via rules, scripts, or skills in Cursor, Claude, or platform APIs.
— Systems thinking: ability to logically chain goals, plan roadmaps, and clearly explain processes.
— Client-facing experience communicating with Heads of UA, defending ideas with data and experiments, and maintaining relationships.
— Ability to convert proven results into templates and methodologies for scaling.
— Strong English communication skills.
Условия:
— Competitive base salary plus performance bonus based on client results.
— Two grades hiring: Middle ($72,000–$96,000/year) and Senior ($102,000–$126,000/year) on-target earnings, gross.
— Remote work worldwide within timezones up to UTC+5.
— Provided laptop, software, and AI tools including Cursor, Claude, Codex, and shared AI infrastructure.
— 50% coverage of relevant educational costs.
— Vacation: two weeks twice a year plus holidays.
— Employment via Deel contract.
Процесс отклика:
— Apply via the "Apply for this role" button on the linked page with social media and contacts.
— Recruiter contacts within two days.
— Calls with leadership and CPO including background, methodology, compensation, math, and AI mechanics.
— Presentation of a built project.
— Offer.
Plurio is an AI agent that automates media buying on Meta, Google, and TikTok for teams spending $300K–$15M a month, handling daily analysis, optimization calls, and execution directly in ad accounts. The system runs over $500M/year in ad spend and has grown 5× since March. The role involves owning the Meta Ads methodology encoded as deterministic rules and skills within the AI agent, improving and testing the algorithm to run Meta media buying end to end from inputs like goals, parameters, and creatives. Responsibilities include maintaining a single source of truth methodology, improving it by generating and testing hypotheses on historical data, building a testing machine to automate testing cycles, and creating implementation and control skills for account audits and adaptations. The ideal candidate is a top expert in Meta methodology with experience running media buying at scale (~$500K+/month), possessing deep knowledge of Meta account architecture, creative testing, data analysis, and decision logic beyond simple rules. They should be AI-native, able to build pipelines and automation by hand, and convert logic into deterministic skills backtested before deployment. The team includes top performance marketing and product experts from major agencies and ad platforms. The position offers up to $180,000/year gross, remote work worldwide within UTC+5 timezone, provided tools including AI infrastructure, 50% education cost coverage, two weeks vacation twice a year plus holidays, and employment via Deel contract. Application is through the "Apply for this role" button on the provided link, followed by recruiter contact and interviews with leadership.
Задачи:
— Разработка и выполнение стратегии кампаний для сегмента Global Strategic.
— Создание и управление планами выхода на рынок, формирование стратегии сегмента.
— Сотрудничество с маркетологами на местах для реализации стратегии.
— Взаимодействие с продуктовыми маркетологами, командой маркетинга и руководством продаж для перевода стратегии в конкретные программы, направленные на увеличение воронки продаж и дохода.
— Работа в рамках AI-native подхода к организации доходов для определения и реализации этого подхода в сегменте Global Strategic.
Требования:
— Опыт в стратегии выхода на рынок и ростовом маркетинге для стратегического или корпоративного сегмента.
— Сильные навыки сотрудничества с кросс-функциональными командами (продуктовый маркетинг, руководство продаж, маркетинг на местах, операции с доходами).
— Способность разрабатывать и реализовывать кампании, которые переводят стратегию в действие.
— Удалённая работа с местоположением в США.
— Доказанный опыт создания и реализации инициатив по росту для глобальных стратегических сегментов.
— Аналитический склад ума с умением измерять влияние и оптимизировать программы.
— Опыт работы в AI-native или технологически ориентированных средах будет плюсом.
Кто вы:
— Стратегический мыслитель с сильными навыками сотрудничества и влияния на кросс-функциональные команды.
— Маркетолог, ориентированный на данные, способный переводить стратегию в измеримые программы.
— Самостоятельный специалист, комфортно работающий в удалённой среде с базированием в США.
Описание команды:
— Команда сегментного маркетинга, ориентированная на рост воронки продаж и дохода по приоритетным сегментам, сотрудничает с руководством продаж, маркетингом, поддержкой продаж и операциями с доходами для создания программ, влияющих на бизнес.
Задачи:
— Работа над критически важным продуктом с полной ответственностью от обсуждения ТЗ до контроля в проде
— Решение интересных задач, не связанные с рутинными CRUD операциями или простым изменением интерфейса
Требования:
— Коммерческий опыт работы от 2 лет
— Уверенное владение стеком TypeScript, Go и React
— Ответственность и проактивность
— AI-native
Условия:
— Гибридный формат работы в Алматы
— Трудоустройство по ТК РК
— 28 дней отпуска в год
— Годовой бонус по результатам KPI
— Медицинская страховка и дополнительные бонусы
ГибридseniorАлматы
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Все вакансии в одном месте — страница 2 · Job Hunters