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Location: Limassol, Cyprus Spotware Systems is looking for a Senior Technical Writer to join our Content & Education Team. We are seeking an experienced technical writer who combines excellent documentation skills with hands-on expertise in AI-driven production, automation and publishing. You will help build scalable workflows that deliver accurate, consistent documentation for complex financial technology products. Responsibilities : Create and maintain clear technical documentation, including user guides, illustrated how-tos and integration manuals. Design and improve AI-assisted documentation workflows, from source research and drafting to review, validation, localisation readiness and delivery. Structure and optimise documentation for AI readability, search visibility and reliable retrieval by agents. Use AI tools and agents to automate repetitive documentation tasks, while verifying technical accuracy against authoritative product sources. Maintain and enhance documentation portals (Docusaurus, MkDocs or similar platforms) and manage content through docs-as-code, Git and review workflows. Collaborate with product, engineering and other stakeholders to turn releases and new features into accurate, timely documentation. Produce release notes and selected B2B/B2C materials, including brochures, white papers and product-video scripts. Establish and apply terminology, style, accessibility and quality standards, including automated checks for accuracy, terminology, style and links. Requirements : Proven experience writing technical documentation for trading, forex, financial technology or similarly complex software products, backed with a strong portfolio. Strong English writing, editing and instructional-design skills. Practical experience with documentation platforms, Markdown, Git and docs-as-code workflows. Hands-on experience using AI assistants, agents, MCP servers, APIs or similar tools into repeatable documentation production and quality-assurance workflows, beyond prompting alone. Ability to evaluate AI-generated output critically, validate claims against product evidence and protect sensitive information. Ability to work independently across teams, prioritise delivery, respond to feedback and improve processes continuously. Conditions : Competitive remuneration reflecting your skills, contribution, and experience. Comprehensive private medical insurance for your peace of mind and well-being. Relocation support package (if applicable) — including visa and work permit arrangements to ensure a smooth move to Cyprus. Welcome Baby Bonus to celebrate life’s most joyful milestones. Birthday Voucher to make your special day even brighter. Fully equipped, modern workplace offering daily fresh fruits, Wednesday breakfasts, Thursday pizza days, and Friday snacks — because great work deserves great food. Sports and wellness benefits, including company-subsidized gym memberships and wellness programs to help you stay active and energized. Support with integration into life in Cyprus, including guidance on local healthcare, banking, and accommodation. Continuous learning and professional growth opportunities, including internal training, conferences, and skill-development initiatives. Greek language classes to help you adapt smoothly to local life and culture.

-погружаться в процессы, данные и бизнес-логику клиентского подразделения. -общаться с заказчиками и пользователями, уточнять потребности и формулировать техническое решение.

Location: Cairo, Egypt Workplace: hybrid We are looking for a Senior Data Engineer to join one of the Data Platform teams that works with the Marketing, Growth, partner, and financial data domains. You will be working with cutting edge cloud technologies (GCP, AWS, BigQuery, Databricks, K8s) and building a large scale data infrastructure for analytics, machine learning, and streaming/CDC data delivery. Key Responsibilities Build and operate batch and streaming ingestion into a layered BigQuery DWH (raw → ODS → data marts) using Airflow, Debezium CDC over Kafka with protobuf, Pub/Sub, and Dataflow Integrate external data sources end-to-end — marketing platforms (GA4, AppsFlyer, TikTok/Meta/Google Ads), payment providers, S3 buckets, and third-party APIs — including schema contracts, backfills, and reconciliation Engineer the data platform itself in Python: custom Airflow operators and connectors in a shared ETL framework, Kafka Connect on Strimzi (K8s), Cloud Functions, and API integrations with external providers Build CI/CD and change-management tooling for BigQuery: GitHub-based test-and-approval flows, SQL migration engines (Liquibase/Flyway/Bytebase), sandbox validation, backup and rollback Own reliability and correctness of pipelines: idempotency, deduplication, late-data handling, backfill and replay, freshness monitoring and alerting; write integration and unit tests Drive data governance and compliance: ITGC-compliant change management for BigQuery, IAM and least-privilege access, PII policy tags and DLP, Unity Catalog on Databricks, column-level lineage (OpenMetadata/Dataplex), and disaster-recovery planning Build internal data tools and platform services for agentic workflows with data — Streamlit apps, Slack bots, LLM-based agents and MCP servers that help teams find and use data Support analysts and business teams with data requests, fostering data-driven decision-making across the company Contribute to system design and architecture with the development team Skills, Knowledge and Expertise Strong practical Python: clean, well-structured, and tested code for services, tooling, and data pipelines Solid software design skills (OOP, modularity, design patterns) — we build platform tools for agentic workflows with data and plan to develop data-related backend services, so well-designed code is highly valued Experience building and operating services in a cloud environment (GCP, AWS or similar): CI/CD, containerization, monitoring and alerting Familiarity with Kubernetes and Terraform — our infrastructure runs on GCP/K8s Hands-on experience with DWH-related tasks (BigQuery or another cloud warehouse) and confident working SQL Clear communication with non-engineering stakeholders — a meaningful share of the work is data requests from analysts and business teams Demonstrated ability to take ownership of technologies or services and proactively contribute ideas to the team Nice to have Advanced SQL: complex queries, window functions, partitioning, clustering, and cost optimization Experience building reliable pipelines around CDC (e.g., Debezium): idempotency, schema evolution, backfills, and reconciliation Analytical data modeling skills: table grain, facts vs dimensions, slowly changing dimensions, and metric definitions Experience with stream processing frameworks such as Flink or Apache Beam/Dataflow Exposure to data governance and audit compliance (ITGC/SOX), Databricks Unity Catalog, or lineage/catalog tooling (OpenMetadata, Dataplex) Interest in building LLM-based agents and AI tooling for data Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Brazil, Colombia Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client The world's largest human resources consulting firm, headquartered in New York City, with main branches in 40+ countries. Over 25,000 employees operate internationally in more than 130 countries. Its services are used by 97% of Fortune 500 companies What You’ll Do Collaborate directly with business stakeholders and domain experts to understand their objectives, processes, constraints, and expected outcomes. Analyze business requirements, documentation, examples, templates, and other reference materials provided by stakeholders. Identify workflows and use cases that can be implemented or improved through Claude Code Skills. Design, implement, test, and maintain reusable Claude Code Skills. Create clear skill instructions, supporting scripts, reference materials, validation logic, and reusable workflow components. Translate complex or ambiguous business processes into structured, executable instructions for AI agents. Evaluate skill behavior using realistic scenarios, test cases, and acceptance criteria Improve the reliability, accuracy, usability, and maintainability of developed skills through iterative testing and stakeholder feedback. Technical leadership over the other engineers: review, direction, unblocking. What You Bring Strong hands-on experience using Claude Code in real software-development or business-workflow scenarios. Practical experience creating Claude Code Skills or comparable reusable capabilities for -AI coding agents. Strong understanding of modern AI engineering patterns, including agentic workflows, tool use, prompt engineering, context engineering, and structured instruction design. Proven hands-on software engineering experience and the ability to build, review, test, and maintain production-quality solutions. Ability to transform business requirements and domain knowledge into clear technical designs and executable workflows. Experience evaluating and improving non-deterministic AI solutions. Ability to own the technical shape of the whole capability, not individual skills: standards, shared components, evaluation and release strategy, backwards compatibility. Ability to define and enforce what a well-formed skill looks like, what belongs in shared infrastructure, and what gets rejected in review. Ability to make and justify platform‑level decisions - including choices around agent harnesses, integration architecture, and build‑versus‑adopt strategies, while providing clear technical rationale for foundational decisions that impact the entire platform Nice to have Hands-on experience with Claude Code, and specifically with authoring Claude Code Skills, plugins, or MCP servers. Evaluation tooling for LLM systems (promptfoo, LangSmith, custom harnesses). Consulting or professional services background. Domain exposure to HR technology, compensation & benefits, payroll, or workforce analytics. Experience building internal developer tooling or standing up a platform capability. Public artefacts: open-source agent tooling, published skills or plugins, conference talks, technical writing on agentic engineering. English level Upper-Intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Our AI-Enabled Screening Process As an AI-first company, Exadel uses an AI recruiter to conduct a brief initial screening for this highly specialized position. This conversation helps us understand each applicant’s relevant experience and alignment with the role’s core requirements. The AI recruiter supports the process but does not make the final hiring decision. Candidates who successfully complete the initial screening will be connected directly with a member of our Talent team for the next step. If you require an accommodation or an alternative screening format, please let us know. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Location: (Multiple States), United States About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: (Multiple States), United States About Improvado Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT. What we sell: extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA. Who buys it: Economic buyers: CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership Technical evaluators: VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security Segments: enterprise brands, mid-market, agencies Verticals: pharma and healthcare, financial services, retail and eCommerce, gaming, agencies Why this role, now Our messaging is not aligned. Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price. The category is crowded and moving fast. Battlecards exist but decay, and nobody owns keeping them true. Attribution, incrementality and causal measurement is where deals are won and lost — and it is the hardest thing to argue credibly without hand-waving. Analyst firms are a silent blocker. When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them. You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it. What you'll own Positioning and messaging. Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it. Competitive intelligence and win/loss. A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning. Sales enablement. The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays. Market and analyst relations. The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization. What we're looking for 4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product. Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak. B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile. Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter. Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking. Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback. Nice to have: hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming. Not a fit if: your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work. How we measure success Win rate in competitive deals against our top 3 named competitors, baseline set in month 1. Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal. Time-to-first-deal for new reps. Field adoption of enablement assets — measured, not assumed. Win/loss program running on cadence, with themes that visibly change product and GTM decisions. Message consistency: a quarterly audit across web, deck, product UI and content. What We Offer Remote-first environment Competitive compensation Medical and dental benefits 401K plan Unlimited PTO Paid holidays Professional development reimbursement

Location: Москва То, что многие компании считают своим прибыльным активом, зачастую является скрытым корнем финансовых проблем. Задача департамента по работе с проблемными активами – вовремя выявить трудности у клиентов и помочь преодолеть их. Используя передовые модели машинного обучения и искусственного интеллекта, мы создаем AI-профили клиентов, которые помогают сотрудникам быстрее разобраться в кейсе и выбрать наилучшую стратегию взаимодействия. В рамках нашего центра ИИ и комплексных решений вектор развития ориентирован на концептуальное переосмысление процессов урегулирования, автоматизацию рутинных процессов и создание дополнительного дохода в рамках работы с проблемной задолженностью. Обязанности * исследование клиентского опыта в рамках процессов оздоровления и взыскания, поиск «узких» мест в процессах и использование передовых инструментов для проведения локальных исследований (графовый анализ, LLM для поиска инсайтов, самовоспроизводящиеся ИИ-решения, disrupt-проекты) * регулярные встречи с Заказчиками для определения зон роста, предоставления непредвзятого взгляда на процессы и предложения к их трансформации * создание ИИ-решений, влияющих на клиентский опыт * построение чистого эксперимента и валидация ИИ-решения * проработка технологической реализации при поддержке команд разработчиков, data и OPS-специалистов * контроль внедрения ИИ-решения и последующего поведения решения в ПРОМ-контуре, анализ результатов внедрения * создание AI-агентов на базе LLM для оптимизации рутинных процессов: * речевая и текстовая аналитика взаимодействия с клиентом * выявление сущностей для автоматизации внутренних процессов * качественная суммаризация текста для составления профиля клиента * создание, обучение и внедрение моделей для оценки и прогноза финансового состояния клиента, скоринга, прогнозирования дефолта, антифрода и выявления мошенничества. Разработка систем подбора индивидуальных условий для урегулирования задолженности, а также применение What-If / Uplift моделирования и каскадов моделей для выстраивания процессов с использованием ИИ * графовый анализ компаний, их руководителей и бенефициаров, анализ новостного контента и других источников информации о клиентах. Требования * опыт работы 3+ лет в традиционных направлениях машинного обучения (ML), обработки естественного языка (NLP), глубокого обучения (DL) * знание библиотек и фреймворков: pandas, pyspark, catboost, pytorch, tensorflow, langchain/langgraph * опыт валидации AI-решений и их "боевого" пилотирования решений * прикладной опыт в использовании LLM, контроле качества ответов и выстраивания графовой архитектуры с использованием LLM tools / MCP * знания математической статистики и основ A/B-тестирования. _Будет плюсом:_   * опыт руководства проектами или самостоятельного обеспечения всего цикла производства ИИ-решения от гипотезы до реализации * знание основ финансового анализа и бухгалтерского учета * опыт курирования или наставничества, работа в крупных AI-проектах с смежными командами * английский язык — уровень Intermediate и выше * опыт в проектах, связанных с клиентским опытом / бизнес-анализом / исследованием очень больших данных * опыт использования AI-инструментов в разработке (LLM-ассистенты для написания и ревью кода, агенты для автоматизации рутинных операций, инструменты автодополнения вроде GitHub Copilot). Условия * возможен гибридный формат работы, локация офиса: Москва, Кутузовский пр., д.32, к.3 * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Работа на платформе PlatformEco (Node.js + SQL) — Построение интеграций с внутренними и внешними продуктами — Участие в стратегических решениях по архитектуре Требования: — Высшее техническое образование (ИТ, математика, физика, кибернетика) — Опыт разработки ИИ агентов — 5+ лет в разработке, из них 2+ года в роли Tech Lead / Team Lead команды 4–7 разработчиков (код-ревью, менторство, декомпозиция задач, участие в найме) — Реальный продакшн-опыт на одном из стеков: Node.js, Python, .NET, Java, SQL — Глубокий практический опыт построения интеграций: Event-driven архитектура (Kafka / RabbitMQ / аналоги), API Gateway, маршрутизация, rate limiting, идемпотентность, retry/backoff, обработка ошибок, саги, проектирование асинхронных систем с гарантиями доставки — Опыт работы с low-code/no-code платформами — Опыт работы в крупной корпоративной организации (5000+ сотрудников) — Понимание архитектурных паттернов: микросервисы, CQRS, Event Sourcing, Hexagonal Architecture, DDD — Проактивность — Переговорные навыки без формальной власти — Баланс «играющий тренер / лидер» — Устойчивость к корпоративной бюрократии — Прозрачная коммуникация Будет плюсом: — Рабочее понимание RAG, LLM, MCP — Опыт в страховой / финансовой / корпоративной среде — Готовность развиваться в сторону AI-агентов и автономных систем Условия: — Условия работы не указаны Контакт для отклика: @irinaalekseevnashi

Задачи: — Работать на платформе PlatformEco (Node.js + SQL) — Строить интеграции с внутренними и внешними продуктами — Участвовать в стратегических решениях по архитектуре Требования: — Высшее техническое образование (ИТ, математика, физика, кибернетика), фундаментальная база критична — Опыт разработки ии агентов — 5+ лет в разработке, из них 2+ года в роли Tech Lead / Team Lead команды 4–7 разработчиков (код-ревью, менторство, декомпозиция задач, участие в найме) — Реальный продакшн-опыт на одном из стеков: Node.js, Python, .NET, Java, SQL (не просто знание, а опыт написания, деплоя и поддержки) — Глубокий практический опыт построения интеграций: Event-driven архитектура (Kafka / RabbitMQ / аналоги), API Gateway, маршрутизация, rate limiting, идемпотентность, retry/backoff, обработка ошибок, саги — Проектирование асинхронных систем с гарантиями доставки — Опыт работы с low-code/no-code платформами, способность быстро адаптироваться к PlatformEco — Опыт работы в крупной корпоративной организации (5000+ сотрудников) с бюрократией, согласованиями, ресурсными конфликтами и кросс-функциональными зависимостями — Понимание архитектурных паттернов: микросервисы, CQRS, Event Sourcing, Hexagonal Architecture, DDD — Проактивность, переговорные навыки без формальной власти, баланс между ролью тренера и лидера, устойчивость к корпоративной бюрократии, прозрачная коммуникация Будет плюсом: — Рабочее понимание RAG, LLM, MCP с практическим опытом встраивания AI-решений в корпоративный ландшафт — Опыт в страховой, финансовой или корпоративной среде с пониманием compliance, безопасности, интеграции с legacy-системами — Готовность развиваться в сторону AI-агентов и автономных систем Условия: — Локация: Россия (удалённо / гибрид) — Зарплата обсуждается по итогам собеседования

Location: Anywhere in France, Belgium, Spain HEALTH CAN’T WAIT. Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t. Alan exists to end the wait. Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way. So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience. We are on an incredible journey to build a global leading company, with a unique culture https://alan.com/en/careers. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR. Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond. ⭐ THE ENGINEERING TEAM ⭐ In our engineering team, we build the infrastructure, interfaces, and applications to provide first-class service to our members, health professionals, and even ourselves! Being an engineer at Alan means joining a team of talented, committed and passionate engineers, with a lot of product interaction. We move fast, with a lot of ownership, and are proud to tackle big problems! Our process is very simple: those who make product decisions are the same ones who build them. Want to know more? Read this article https://blog.alan.com/tech-et-produit/engineering-organisation-at-alan if you want to discover how life as an Engineer at Alan and this article https://medium.com/alan/engineering-career-path-at-alan-e5de5c2e740c on our Engineering career pat 🛠️ THE STACK Python services on FastAPI, async SQLAlchemy and PydanticAI, Temporal for durable execution, PostgreSQL, MCP, Daytona sandboxes, various LLM model providers, Terraform on AWS, React with Vite. Our main backend is a Flask monolith. We deploy daily and believe in distributed ownership: you build it, you own it. 🤖 THE AGENTIC PLATFORM AREA In 2027, we expect to run more AI agents than we have employees. Agents already do real work at Alan. They answer members' health questions, resolve support requests, read medical documents, detect fraud, automate operational tasks, and write a large share of our code. But every team building an agent ends up solving the same hard problems again: how to call models safely with health data, how to give an agent tools and the right permissions, how to know whether a prompt change made it better or worse, how to debug what it did. The result: several agent frameworks and evaluation stacks, each with its own security and compliance story. The Agentic Platform area was created to fix that. Our mission: make it cheap, fast and safe for every Alaner or crew to build, run and improve agentic products and workflows. We own the environment agents run in (infrastructure, runtime, evaluation, observability, skills lifecycle), with security, privacy and compliance by design, and the generalist products on top: Hopper and the Agent Studio. Product teams and all Alaners own their agents, skills, and their outcomes. We give them the paved road. Two crews, one team: - Hopper is every Alaner's AI companion. Five months after it started, 80% of Alaners use it, 3k sessions are created each day, and about 30% of our pull requests are opened from it (watch how we built it https://www.youtube.com/watch?v=hAu7Ngfd0ys). - AI Product Platform builds the shared blocks every AI product at Alan runs on. For instance, our ops teams now build agents autonomously on our Ops AI Platform (read how https://medium.com/alan/how-we-bootstrapped-an-ai-agents-platform-for-operations-at-alan-fefd87ed6314, watch the talk https://www.youtube.com/watch?v=_pg1ij8k5Rw). 🧩 PROBLEMS YOU'LL ONLY FIND HERE Run agents at scale - 🧠 One runtime for every AI product. A shared agent framework, from a single model call to multi-agent workflows with live streaming, and one gateway to every model: routing, failover across providers, quotas and cost per use case built in. - ⏳ Agent sessions that last for hours. Durable sessions, started from the web, Slack, Linear or GitHub, that survive pod restarts and deploys, and pick up exactly where they left off. - 📦 Sandboxes at scale. An isolated environment for every agent session and every evaluation, on an infrastructure compliant with sensitive data, with negligible boot overhead. Make agents trustworthy and proactive - 🔌 One tool gateway to the whole company. An MCP gateway that connects agents to internal tools and data, external services, computer use, managing identity and credentials. - 🔐 Agents safely acting on critical data. We give each agent no more than the access it needs. Every tool call goes through identity, permissions, confirmations and audit. No sensitive data leaks. - 🧪 Evals you can replay in time. Re-run an agent or skill against production as it was at a past point in time, on real data, safely isolated. Anyone can ship knowing their change is an improvement rather than a regression. - 🔁 Agents and skills that proactively fix themselves. Every run is traced, and every human correction, failed tool call or escalation becomes a prioritized fix that Hopper can apply. Put agents in everyone's hands - 📚 Skills as a product. A registry where Alaners and teams publish, share and version their skills, so that nothing needs to be repeated twice. - ✨ AI that non-engineers can own. Alaners who ship code through Hopper, Operators or Sales who build their own agents or skills in our Studio and operate them from their day-to-day tools. - ⏰ Automations and artifacts. Agents that run on a schedule or on an event, and build the dashboards and hosted sites that become the go-to places for collaboration. ⭐ IS IT YOU WE’RE LOOKING FOR? What you'll do - Own some of the problems above end to end, from design to production, with significant influence on architecture and code quality - Work closely with the people who use what you build: Alaners, product teams, ops - Own reliability, cost and security in production - Mentor engineers, contribute to our product and engineering culture, and help build the team Experience we value - 3+ years in software engineering, with solid backend fundamentals - Platform-leaning or product-leaning: both are welcome. Depth in at least one of: distributed systems and runtimes, evaluation and data quality, security and authorization, product UX - A good sense of user and developer experience, whatever you build - You built products, platforms or infrastructure used by other people - Experience with LLM APIs, agent frameworks, evals or MCP is a strong plus; ML or MLOps experience is a plus Mindset we value - You measure success by adoption, not by what is available - You make concrete tradeoffs between speed, reliability, cost, security and user experience - You simplify complexity with clear abstractions and maintainable code - You care about whether people can understand and verify what an AI system did - You keep up with the latest AI technology and know the open-source AI ecosystem - Self-directed, pragmatic, humble, collaborative, enthusiastic about learning and teaching - Excited about AI changing who can build, investigate and automate work Above all, we look for high potential and curiosity: make sure to show us this when you apply. Everything else is a bonus. You should be fluent in English (no French required). 🌍 HOW WE WORK - Location: you must be legally eligible to work in France, Belgium, or Spain. - Remote work: we offer remote work flexibility, but we value in-person collaboration. 🙌 PERKS & BENEFITS https://alan.com/en/careers/a/salary-equity At Alan, we believe that being in good health is a basic need, and it starts with our employees. This is why Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. Therefore, we offer: - Fair rewards. Generous equity packages complement your base salary. - Flexible Office. Amazing office space at our HQ, sponsored co-working hubs or a full-remote experience with home office equipment sponsorship, we want you to live where you’re the happiest. - All the tools you need. Top of the range equipment: Macbook Pro, keyboard, laptop stand, monitor, and noise-canceling headphones. - Flexible vacation policy and flexible working hours. Organize your time as you wish. - Delightful healthcare insurance: Extremely comprehensive health insurance - 100% for you and your children, 90-100% for partners depending on your country (permanent contracts only). - Transport. Country-specific commuter benefits. - Learning & Training opportunities. A highly flexible Training policy free books and budget to attend and speak at conferences if the opportunity arises. - Personal growth through coaching: At Alan, coaching isn't just a perk - it's core to who we are. Every Alaner is paired with a dedicated coach from day one, who helps maximize their impact, nurture engagement, and navigate Alan's values to develop their full potential. Learn more about our coaching culture https://alan.com/en/blog/discover-alan/a/alan-culture-excellence-through-coaching. - Parental leave. Extended parental leave for all new parents.   IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply as it can only bring learnings or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. 🔄 A quick note about the process Note: While you're applying for a specific area, you may join a different engineering team based on where we think you'll have the most impact. Check out descriptions of other areas here https://www.notion.so/alaninsurance/Software-Engineering-Areas-Alan-2c61426e8be7805bacd2cdbc08c32640?source=copy_link.

Location: Москва Ищем менеджера продукта, который возьмет на себя развитие десктопного AI-приложения для разных ролей в процессе разработки ПО: аналитиков, QA, product/project-менеджеров и других специалистов. Обязанности * Отвечать за продуктовую стратегию и развитие GigaCode Desktop.   * Исследовать задачи разных ролей PDLC и находить сценарии, где AI-агенты дают максимальную ценность. * Формировать и приоритизировать roadmap продукта. * Проектировать отдельные role-based сценарии и рабочие пространства, например для: системного и бизнес-аналитика; QA; владельца продукта; project/product manager; других ролей PDLC. * Развивать агентские сценарии: Skills, MCP, subagents, интеграции с корпоративными системами и инструментами пользователей. * Работать с UX/UI командой над простым интерфейсом для сложных агентских возможностей. * Проверять гипотезы через интервью, прототипы, пилоты и продуктовую аналитику.  * Определять продуктовые метрики: activation, adoption, retention, частоту использования ключевых сценариев и эффект для пользователей.  * Работать вместе с разработкой, дизайном, аналитиками, ML/AI-командами и внутренними заказчиками. * Доводить продуктовые инициативы от идеи и discovery до запуска и измеримого результата. Требования * Опыт работы Product Manager / Product Owner с digital-продуктами. * Умение самостоятельно проводить discovery: исследовать пользователей, формулировать проблемы и проверять гипотезы. * Сильное продуктовое мышление: способность отличать реальную пользовательскую ценность от просто интересной технологии.  * Умение проектировать сложные пользовательские сценарии и превращать их в понятный продукт.   * Опыт работы с кросс-функциональными командами разработки.   * Понимание продуктовых метрик и умение принимать решения на основе данных.   * Способность работать в условиях высокой неопределенности и самостоятельно формировать направление развития продукта.  * Технический бекграунд (разработка, системная аналитика) * Глубокая экспертиза в использовании агентов Codex, Claude  **Будет большим плюсом** * Опыт создания AI-продуктов, copilots или AI-агентов. * Понимание современных LLM, tool calling, MCP, skills и multi-agent подходов.   * Опыт работы с developer tools, enterprise-продуктами или внутренними платформами. * Понимание процессов разработки ПО и ролей внутри PDLC.  * Опыт создания продуктов сразу для нескольких пользовательских сегментов. Условия * комфортный современный офис рядом с м. Тульская * возможность выбрать удобный график – офис/гибрид * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера

Location: Москва Ищем опытного Product Owner в трайб Маркетплейс интеграционных сервисов в кластер развития продуктов канала API. Мы занимаемся выводом текущих продуктов банка в канал API, внедряем новые и сопровождаем текущие. Обязанности Чем предстоит заниматься: * управление командой разработки: проводить церемонии  (стендапы, планирование, груминги) * управлять бэклогом: декомпозировать бизнес-требования в технические пользовательские истории (User Stories) для команд разработки. Активное участие в планировании спринтов и продуктовых бэклогов (Agile/Scrum, Kanban) * отвечать за Developer Experience (DX): контролировать качество API-документации по своим продуктам (Swagger/OpenAPI), SDK и тестовой модели * улучшать клиентский путь по интеграциям * стейкхолдер-менеджмент: Выступать связующим звеном между клиентами, партнерами, поддержкой, безопасностью и внутренними продуктовыми командами: координация взаимодействия внутри своей команды и со смежными подразделениями для эффективного выполнения поставленных задач * запуск и поддержка: планировать релизы, проходить приемо-сдаточные испытания, взаимодействовать с пилотными клиентами и собирать и анализировать обратную связь * оценка эффективности: определять метрики успеха продукта и отслеживать их достижение, оценивать реальную пользу и наращивать пользовательскую базу Требования * опыт работы от 5 лет в роли Product Owner / Product Manager (управление цифровыми продуктами) * понимание того, как устроены современные API (REST, GraphQL, gRPC и SOAP) * понимание чем синхронные вызовы отличаются от асинхронных. Зачем нужны Webhooks и MCP  * представление об очередях сообщений (Kafka, RabbitMQ) и паттернах микросервисной архитектуры на уровне бизнес-логики * опыт выведения цифровых продуктов в промышленную эксплуатацию и их масштабирование * умение аргументированно отстаивать свою точку зрения, просто и понятно формулировать свои мысли как для команды, так и для различных стейкхолдеров * обладание системным мышлением. Видеть продукт не как набор изолированных фич, а как часть большой экосистемы * способность быстро разбираться в сложных технических вопросах и обеспечивать передачу необходимой информации другим участникам команды * умение структурировать информацию, описывать сложные вещи простым и понятным языком * умение работать в команде: дружелюбность и открытость к взаимодействию, стремление к развитию Будет преимуществом: * опыт работы в банковской сфере или участие в fintech-проектах * умение читать спецификации (OpenAPI / Swagger, AsyncAPI) * знание инструментов API-аналитики и мониторинга (например, Grafana) Условия * комфортный современный офис * корпоративный спортзал и зоны отдыха * уникальная система обучения Сбера для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС и льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.

Проектировать архитектуру мультиагентных систем для автоматизации клиентской поддержки, включая RAG, управление состояниями и оркестрацию ИИ-агентов. Разрабатывать и развивать workflow-системы для управления взаимодействием агентов, многошаговыми диалогами и интеграциями с внутренними сервисами.

-Разрабатывать агентов на LangGraph: tool calling, многошаговые сценарии, human-in-the-loop, обработка ошибок. -Строить RAG по внутренним документам: разбор PDF/DOCX, сканов и таблиц, индексация, гибридный поиск (BM25 + dense), реранкинг.

Location: Remote US Please note that all communications regarding this position will be sent exclusively from an email address ending in @planetscale.com Any correspondence relating to this role will only originate from this domain. About the role More and more PlanetScale databases are created, connected and queried by AI agents. Cursor, Claude Code, Codex and a growing list of other tools now sit between developers and their infrastructure. You will own that experience end to end. You'll make sure PlanetScale shows up everywhere developers build with AI, that our MCP server and CLI work flawlessly in every agent, and that we can measure how well it all works. Then you'll show the world how to do it well through demos, docs, blog posts, videos, and conferences. This is a hands-on role combining engineering, content creation, and a strong public voice. You'll work closely with the teams that build our MCP server, CLI, API and docs. The landscape of how developers work with AI changes fast. You'll have the opportunity to move quickly, experiment, and take the lead on the future of AI use with databases and infrastructure. Make PlanetScale great with AI tools Build and maintain the plugins for PlanetScale in every AI marketplace and directory: agent plugins, skill registries, MCP directories, IDE extension stores and AI app builders Own our integrations with AI coding tools, agent frameworks and platforms Stay current with AI tools as they launch and ensure our customers have a great experience from day one Test the PlanetScale MCP server and CLI across Claude Code, Cursor, Codex, VS Code and other clients, and catch regressions before users do Find friction in creating a database, connecting, running migrations and debugging queries from inside an agent, then fix it or drive the fix with the owning team Improve the context agents rely on: tool descriptions, skills, llms.txt, docs written for agents, and error messages agents can act on Attention to AEO (answer engine optimization): make sure agents find and recommend PlanetScale Build and maintain skills for working with Postgres, MySQL, Vitess, Neki, and PlanetScale Measure how well we're doing Build evals that run real agent tasks against PlanetScale databases Benchmark how agents perform with PlanetScale and work towards continuous improvement Track how often AI assistants and agents recommend PlanetScale for database questions, and whether what they say about us is accurate Instrument and report on agent usage: databases created by agents, time to first connection, MCP versus CLI usage, and where sessions fail Show people how to do it well Build demos and sample apps that show PlanetScale and AI tooling at their best Write docs, guides and blog posts on using databases effectively with AI, including safe access, branching and performance assessment Make videos and attend conferences to communicate with our audience how to build effectively with AI These attributes best describe you Daily use of AI coding agents, with strong opinions about what makes a tool work well with them Experience building an MCP server, plugin, CLI or SDK that real developers use Software engineering background in languages like TypeScript and Go, and comfort with APIs, OAuth and the command line Experience with writing docs, blogs, and / or video content creation Good at communicating with a broad audience and customers alike on socials Experience working with relational databases (Postgres, MySQL, SQLite), schema design, migrations, connection handling, and Postgres or MySQL in production Data fluency: designing evals, writing the queries behind a dashboard, and telling a real trend from noise Clear communication of technical ideas in writing, on video and on stage Independence and speed: spotting a gap, shipping a fix, and telling people about it Genuine curiosity about the AI tooling landscape and a habit of keeping up with it Bonus points Contributions to the MCP spec, SDKs or popular open-source MCP servers Experience writing agent skills, plugins or rules files for Claude Code, Cursor or Codex Experience with LLM eval tools and building benchmarks for agents Experience with AEO or GEO, or with tracking how LLMs surface and recommend a product A blog, YouTube channel or GitHub that developers already follow Experience with Vitess, database sharding, or running databases at scale Why PlanetScale We're redefining how high-growth companies manage data at scale—and we work with some of the most exciting brands in gaming, consumer tech, and B2B SaaS. As a Software Engineer, you'll be at the core of building the platform that powers world-class apps used by hundreds of millions of users worldwide. PlanetScale is a profitable company with a philosophy centered around building small teams of p99 individuals and is recognized as one of the fastest growing companies in America. At PlanetScale we believe in supporting people to do their best work and thrive no matter the location. Our mission is to build a diverse, equitable, and inclusive company. We strive to build an inclusive environment where all people feel that they are equally respected and valued, whether they are a candidate or an employee. We welcome applicants of any educational background, gender identity and expression, sexual orientation, religion, ethnicity, age, citizenship, socioeconomic status, disability, pregnancy status, and veteran status. If you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate! Total Compensation and Pay Transparency An employee's total compensation consists of base salary + variable comp where appropriate + benefits + equity. A member of our Talent Acquisition team will be happy to answer any further questions when we engage with you to begin the interview process. Base Salary Range: $170,000 - $220,000

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: You'll be the product manager for our Canvas and Agentic AI teams - the teams building Honeycomb's AI-powered investigation experience. Canvas lets engineers use natural language to query, visualize, and understand their production systems. We're pushing well past chat: we're building Skills (pre-configured workflows that encode domain expertise into repeatable, executable actions), Auto-Investigations (agent-driven investigations that kick off before a human gets paged), and a rearchitected Canvas that's both interactive and collaborative. You'll work in a tight triad with engineering and design leads, owning the roadmap for how AI shows up in Honeycomb, from the product UI to our MCP server. You'll partner with our Director of AI Strategy, Research & Development teams, and our customer-facing teams to stay grounded in what customers actually need while pushing toward something meaningfully different from what exists today. This is a role for someone who can hold both execution and ambiguity: shipping production features while navigating a product space where the right answers are still emerging. What you’ll do in the role: Define AI product strategy in service of Honeycomb's vision Synthesize AI trends, customer needs, and technical capabilities into clear strategic recommendations Help the product organization understand where and how AI creates genuine customer value vs. where it's hype Identify emerging observability challenges created by AI adoption (e.g., LLM drift, prompt regression, low-context generated code) Make informed bets about which AI technologies and approaches warrant investment Conduct research that bridges technology and customer reality Build deep understanding of how customers are adopting AI in their engineering workflows Identify patterns across customer conversations that signal future market needs Stay current with AI/ML developments (RAG, fine-tuning, agentic systems, etc.) and translate implications for observability Engage with technical communities, researchers, and early adopters to spot trends before they go mainstream Enable AI innovation across the product portfolio Partner with product teams to identify high-value opportunities to leverage AI capabilities Provide guidance on AI approaches, trade-offs, and best practices without centralizing all decisions Help teams understand how their work fits into our broader AI strategy and how to leverage shared capabilities Synthesize cross-portfolio learnings and socialize what's working (and what isn't) Evangelize the AI-observability connection Articulate Honeycomb's point of view on AI observability both internally and externally Help customers understand how observability needs evolve as they adopt AI Contribute to thought leadership through writing, speaking, and community engagement Build credibility with technical audiences who care deeply about how we use AI, not just that we use it What you’ll bring to the role: Proven AI product experience 5+ years in product management with at least 1+ year shipping AI/ML-powered products Track record of taking AI features from concept to customer impact, including things that didn't work Deep understanding of how engineering teams actually build, deploy, and operate AI systems (not just theoretical knowledge) Familiarity with current AI/ML techniques and the judgment to know when they're applicable vs. overhyped Strategic thinking with customer empathy Ability to synthesize disparate signals (research, customer feedback, technical trends) into coherent strategy Comfort operating with ambiguity and making decisions without perfect information Pattern recognition across conversations—spotting what customers aren't yet saying clearly Strong judgment about when to say "no" or "not yet" despite exciting technology Technical credibility without needing to be the expert Enough technical depth to have earned respect from engineers and architects Genuine curiosity about how things work, paired with humility about what you don't know Ability to evaluate trade-offs between different AI approaches (RAG vs. fine-tuning, model selection, etc.) Understanding of observability principles and why they matter in production systems Communication and collaboration skills Excellent written and verbal communication—can explain complex ideas clearly to varied audiences Ability to influence without authority across product, engineering, and go-to-market teams Comfort presenting to customers, executives, and technical audiences Collaborative mindset that elevates others' work rather than centralizing control Curiosity and learning orientation Demonstrated ability to stay current in fast-moving domains (AI is evolving weekly, not yearly) Intellectual humility—you're more interested in learning than being right Excitement about the intersection of AI technology and real customer problems Energized rather than exhausted by the pace of change in AI Base Salary based on level of experience $272,739 — $320,829 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.

⭐ Необычная задача: ревьюить код и проверять PR не только живых людей, но и самих AI-агентов.

Location: Europe or US Workplace: Remote About the team The Control Plane Platform team is building the shared foundation that every product in ClickHouse Cloud is built and shipped on. We give ClickHouse engineering teams one place to own and deploy their product, remove the overhead of rebuilding common plumbing, and keep the customer experience consistent as the number of integrating teams grows. The team owns API gateways and API standards, shared platform services, deployment and infrastructure patterns, testing and CI, local developer experience and Control Plane observability. About the role We’re looking for an Engineering Manager to lead our Platform team. This is a high-impact, high-trust role at the center of our Cloud product, combining people leadership, technical direction, product thinking, and operational ownership while maintaining the reliability customers expect. You’ll work hand-in-hand with Product, Infrastructure, Security, Support, and engineering teams across ClickHouse. This role goes beyond engineering leadership. Together with your team, you’ll help shape how new products and teams will integrate and deploy their applications in ClickHouse Cloud. What You’ll Do - Lead, coach, and grow a high-performing team - recruit to a high bar, set crisp expectations, give direct feedback and career development, and manage performance — while fostering a healthy, inclusive environment built on empathy, psychological safety, trust, and a high technical bar. - Own outcomes across the platform surface: API gateways and API standards, shared platform services (event bus, notifications, feature flags, websockets, audit records), deployment and infrastructure patterns, CI and testing, local developer experience, disaster recovery, and Control Plane observability. - Treat the integrating teams as your customers and measure success by their delivery velocity and adoption of the platform, not only by what your team ships. - Guide architecture and help senior engineers make explicit, sound tradeoffs. land cross-cutting migrations, deprecations, and contract changes across teams without stalling product delivery. - Jump into designs and code for complex areas - gateway routing and auth/RBAC enforcement, spec-driven code generation, event delivery semantics and idempotency, multi-region rollout safety. - Build the culture of operational excellence: Own SLOs, reliability, on-call quality, and cost-efficiency for k8s-hosted, multi-tenant services across cloud regions. - Systematize support, reduce toil, and build self-serve/auto-healing capabilities - golden-path templates and generators, auto-healing, and documentation that gets a new team integrated in days rather than weeks. - Shape the platform vision, turn it into a roadmap, sequence bets for business impact, and ship fast with tight feedback loops — including writing the RFCs that build cross-org consensus before big changes land What you bring - 8+ years in software engineering and 3+ years managing software engineers with a track record of hiring, developing, and retaining strong talent. - Experience leading a platform or infrastructure team whose customers are other engineering teams — you've driven adoption and cross-org migrations through influence and good tooling rather than mandate. - Experience leading distributed global teams, fostering an inclusive and autonomous culture, and creating clarity across time zones. - Experience building scalable, highly available, and secure cloud-based infrastructure in AWS (EKS, SQS, DocumentDB, Redis, PostgreSQL, Lambdas) with infrastructure as code (Terraform, Helm) and progressive delivery (Argo Rollouts or similar). - Experience with containerization and orchestration (Docker, Kubernetes), including patterns for hosting many independently deployed applications in a shared cluster. - Familiarity with API platform work: OpenAPI-driven contracts, API gateways, and the shared concerns they centralize — authentication, RBAC, rate limiting, versioning, and deprecation. - A track record of decomposing a monolith into independently deployable services without stalling product delivery. - Technical credibility to engage deeply in architecture and incidents without owning daily implementation. - Hands-on: you still enjoy diving into code/designs for complex or critical areas, reviewing code, and guiding via feedback. - Strong execution judgment across ambiguity, parallel workstreams, risk, and long-term system health. Nice to have - Experience with large TypeScript/Node monorepos and the developer-experience problems that come with them: CI scale and flakiness, build and test times, local development environments, and code generation from specs. - Designed and implemented strategies for load balancing, auto-scaling, disaster recovery, and failover for cloud environments. - Experience building CI/CD at scale - Experience with internal developer platforms: service catalogs, golden-path templates, and self-service app scaffolding. - Proficiency with frontend frameworks (React). - Experience making APIs consumable by AI agents — MCP servers, CLIs, or skills generated from API specs. - Experience with ClickHouse - Previous experience in developing analytics or data-intensive applications. Why This Role - Shape how all feature teams in ClickHouse Cloud develop and integrate with each other - Operate with ownership, autonomy, and speed while keeping the company lean. - Lead a technical team where correctness, performance, reliability, and developer experience all matter. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.