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Задачи: — Отвечать за всю AI-часть продукта: архитектура AI-системы от выбора LLM-моделей до построения RAG-pipeline и интеграции компьютерного зрения, принимать все ключевые технические решения — Обеспечивать качество рекомендаций, повышая конверсию на каждой итерации — Проводить быстрые итерации с выкатыванием изменений каждую неделю, сбором метрик, анализом и улучшением — Проводить эксперименты: A/B тесты промптов, гибридный поиск (текст + визуал + отзывы), мультимодальные модели, быстро проверять гипотезы на реальных пользователях — Масштабировать систему с 2000 туров на Мальдивы до 50,000+ туров по трём направлениям с тысячами запросов в день — Строить продукт с нуля, быстро экспериментировать и влиять на архитектуру Требования: — Опыт с продакшен LLM-приложениями, построение RAG-систем или чат-ботов на основе GPT/Claude — Экспертный уровень промпт-инжиниринга: правильная структура промптов, few-shot examples, chain-of-thought — Опыт работы с эмбеддингами и векторным поиском, понимание similarity search, hybrid search, reranking — Python на уровне продакшена: чистый, быстрый, поддерживаемый код Будет плюсом: — Опыт с компьютерным зрением и мультимодальными моделями (CLIP, GPT-4o, Claude 4.5 Sonnet) — Опыт с high-load системами и оптимизацией latency — Понимание рекомендательных систем — Понимание MLOps: мониторинг моделей, версионирование, A/B тестирование — Опыт построения recommendation систем и MCP для LLM систем — Личный опыт использования LLM для автоматизации задач Софт-скиллы: — Продуктовое мышление: AI как инструмент решения бизнес-задач — Умение работать с метриками: конверсия, время сессии, escalation rate — Быстрота принятия решений: выкатывать несовершенное решение и тестировать — Умение объяснять сложное простым языком для команды и бизнеса Условия: — Официальное оформление по ТК РФ — График 5/2, офис, сокращённый рабочий день по пятницам до 15:30 — Корпоративные программы обучения и развития — Медицинское обслуживание: ДМС и собственная медсанчасть — Специальные предложения от компаний-партнеров (рестораны, магазины, отдых, мероприятия) — Организация отдыха сотрудников и их детей, оплата детского сада — Аккредитованная IT компания — Офис на станции м. Курская — Корпоративные условия на приобретение туров — Дополнительный оплачиваемый отпуск 3 дня, оплата больничного — ДМС для членов семьи по корпоративным условиям — Корпоративные условия на изучение английского и занятия спортом
Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building high-load products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Lead ML Engineer to own a new ML stream focused on fast delivery of applied machine learning solutions across different product and business domains. The stream will work with a broad range of ML challenges. Some initiatives may be relatively small and delivered within a few weeks, while others may prove their value and grow into larger dedicated projects. This role combines hands-on ML engineering with end-to-end technical delivery ownership. You will receive product problems and expected outcomes from Product or internal stakeholders, clarify the technical requirements and constraints, define the implementation approach, coordinate execution within the stream, and bring solutions to production readiness and launch. This is a highly hands-on role. The stream will not have a dedicated software engineer for every initiative, so we expect Data Scientists and ML Engineers to be comfortable working beyond experimentation and contributing directly to production code. The role is not tied to a single ML domain. We value strong ML fundamentals, engineering skills, pragmatism, and the ability to quickly understand new problem areas more than deep specialization in one particular class of models. Job Responsibilities Technical Delivery Ownership Turn product and business problems into concrete ML implementation plans. Clarify requirements, constraints, available data, integrations, and success criteria together with Product and relevant stakeholders. Define technical scope, milestones, dependencies, risks, and delivery estimates. Select appropriate ML approaches and determine the fastest reliable way to validate and implement them. Drive technical delivery through experimentation, implementation, integration, deployment, and launch readiness. Keep delivery on track, proactively identify blockers, and coordinate dependencies with other teams. Provide Product with clear technical options, trade-offs, estimates, risks, and experiment results required for product decisions. Support production rollout and iteration based on observed results. Hands-on ML & Engineering Design, train, evaluate, and deploy ML models across different domains and problem types. Write production-quality Python and contribute directly to implementation. Build APIs, batch jobs, data-processing pipelines, and ML services required to deliver solutions where appropriate. Work with classical ML, deep learning, and foundation-model-based approaches depending on the problem. Process and transform large production datasets using Python and SQL. Integrate models into existing production systems. Implement appropriate testing, monitoring, logging, and observability for delivered ML solutions. Work within the shared ML infrastructure, architecture, and engineering practices used across the company. Collaborate with Data Science, Backend, Data Engineering, and MLOps specialists when deeper domain expertise or infrastructure changes are required. Stream Execution Break initiatives down into concrete technical tasks and coordinate execution within the stream. Coordinate the work of Data Scientists and ML Engineers contributing to stream initiatives. Review technical approaches, experiments, and implementation. Keep the team focused on the agreed scope, priorities, and delivery timeline. Identify technical risks and dependencies early and drive them to resolution. Escalate architectural, infrastructure, or methodological questions when broader alignment is required. Help prepare successful initiatives for scaling or transition into longer-term ownership if they grow beyond the scope of the stream. Cross-functional Collaboration Work closely with Product throughout the delivery lifecycle. Independently gather the technical details and constraints required to execute on a product request. Communicate estimates, dependencies, technical trade-offs, and delivery status clearly. Work directly with Engineering and other internal teams to unblock implementation. Challenge technically unclear, contradictory, or infeasible requirements and propose practical alternatives. You’ll thrive here if you have 5+ years of commercial experience in Machine Learning, Data Science, or ML Engineering. Strong hands-on Python programming and software engineering skills. Experience taking ML solutions from a product requirement through experimentation, implementation, integration, and production. Strong understanding of machine learning methods, statistics, experimentation, and model evaluation. Experience writing maintainable production code rather than working exclusively in notebooks. Experience building APIs, services, batch processing, or data pipelines. Strong SQL skills and experience working with large production datasets. Practical experience with Docker and production deployment environments. Ability to turn partially defined problems into concrete technical plans. Ability to estimate work, identify dependencies and risks, and drive technical execution against a timeline. Experience owning technical delivery involving several contributors and coordinating work across dependencies. Experience reviewing code and technical approaches. Ability to work effectively within established engineering and ML practices while independently owning delivery within a stream. Strong communication skills and the ability to work directly with Product and technical stakeholders. Ability to balance speed and engineering quality: validate ideas quickly when uncertainty is high and build robust solutions when moving towards production. Nice to Have Previous experience as a Tech Lead, Stream Lead, or technical owner of ML initiatives. Experience with Kubernetes and CI/CD. Experience with Kafka or other streaming platforms. Experience with Airflow, MLflow, experiment tracking, model monitoring, or similar tooling. Experience building real-time or high-load ML services. Experience with FastAPI or similar Python service frameworks. Experience across several ML domains, such as recommendation systems, ranking, NLP/LLMs, Computer Vision, anomaly detection, forecasting, or classification. Experience with LLM inference, fine-tuning or other GenAI systems. Experience in teams where Data Scientists and ML Engineers own a substantial part of production implementation themselves.
Задачи: — Создавать персонажей, объекты, окружение и другие игровые арты в cartoon / stylized стилистике — Работать от идеи и референсов до финального арта — Точно попадать в существующий визуальный стиль проекта и поддерживать его консистентность — Прорабатывать композицию, цвет, свет, форму и детали — Дорабатывать арты по обратной связи Art Director — Взаимодействовать с другими художниками и командой проекта — Использовать AI-инструменты для ускорения работы, при этом самостоятельно рисовать и качественно дорабатывать результат руками Требования: — Уровень Senior / Lead — Сильное портфолио с коммерческими cartoon / stylized работами — Умение рисовать с нуля, а не только работать с AI-генерациями — Сильная база: композиция, цвет, свет, перспектива и анатомия — Умение быстро адаптироваться под разные визуальные стили — Уверенное владение Photoshop или аналогичными инструментами — Опыт в GameDev / игровой индустрии будет большим плюсом — Самостоятельность, внимание к деталям и адекватное отношение к обратной связи — Для Lead-позиции важен опыт ведения художественного направления, контроля качества арта и работы с другими художниками.
Location: Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Paphos, Cyprus; Remote, Germany; Warsaw, Poland Founding Tech Lead (GrowthBricks) Are you a hands-on engineer who loves zero-to-one challenges? Do you want to build systems with real context and memory that do more than reason, use tools, and drive actual business outcomes? About JetBrains We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale. GrowthBricks is a new project at JetMinds, backed by JetBrains, designed to give GTM teams and AI agents a shared business brain. Business context usually gets fragmented across CRMs, documents, dashboards, and people's heads. GrowthBricks brings that context together so agents and people can make decisions and execute effectively across the sales, marketing, and product stack. About GrowthBricks GrowthBricks is a shared business brain for GTM teams and AI agents. It brings together the context that usually lives across CRM, docs, dashboards, tools, and people’s heads: who we sell to, why customers buy, what matters now, what we tried, and what worked. Agents and people use that context to decide what to do next and execute across the GTM stack. GrowthBricks is a new project at JetMinds, backed by JetBrains. About the role We’re looking for a hands-on Founding Tech Lead to build GrowthBricks from zero. You’ll work directly with the product founder and own the technical side of the product: architecture, core systems, integrations, and the agent layer. The core challenge is turning fragmented, changing business context into reliable memory and agent actions across tools and measuring whether those actions actually drive business outcomes. You’ll write a lot of the early code yourself, make the key technical decisions, and shape the product as we learn what works. What you’ll work on Design the core architecture: business context, agents, tools, integrations, and feedback loops. Build agentic workflows that can reason over company context and act across CRM, sales, marketing, and product systems. Build context extractors from GTM team artifacts like sales calls, emails, internal documents, CRM state, marketing campaigns, etc. Work on prompting, context management, memory, tool use, and orchestration. Connect GrowthBricks to the existing GTM stack rather than rebuilding everything around it. Decide where to use MCP, APIs, frameworks, or third-party tools and where a custom solution is worth it. Prototype fast, discard weak ideas, and turn the useful ones into product primitives. We expect that you Are a strong hands-on engineer who enjoys zero-to-one work. Have built with LLMs, agents, or agentic workflows used by real people, and improved them based on failures, evaluations, and user feedback. Understand how context, prompting, tools, and agent behavior fit together. Can design backend systems, APIs, data models, and integrations. Are comfortable making decisions before all the answers are known. Prefer simple, pragmatic solutions over unnecessary complexity. We’re especially interested if you Have worked in solution engineering, sales engineering, pre-sales, or built software for GTM teams. Understand the modern GTM stack: CRM, enrichment, outbound, automation, and product signals. Have automated sales or marketing workflows, ideally with agents or LLMs. Have owned a technical product from a blank repo to something people actually used. GTM experience is not mandatory, but if you already understand how sales and marketing teams work, that is a strong advantage. What we offer A competitive salary and strong benefits package. The runway and resources of an established company, with startup-level autonomy. A founding role with direct influence over both product and architecture. Real users and real workflows from day one. Freedom to choose the stack, tools, and technical approach. A chance to help define what an agent-native GTM product should look like. #LI-IM We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Описание проекта: Крупное предприятие переводит финансовый контур c 1С:УПП на 1С:ERP.УХ: регламентированный учёт, МСФО, внутренний контроль для налогового мониторинга — с учётом ФСБУ и актуальных изменений (в т.ч. ФСБУ 9/2025 и IFRS 15). 10 филиалов, полный цикл внедрения, роль функционального архитектора по блоку МСФО — от целевой модели до первого промышленного закрытия. Обязательные требования: — Опыт работы в роли ведущего консультанта 5 и более лет — Экспертное знание функциональных областей «Регламентированный учет» и «Налоговый учет» — Отличное знание конфигурации 1С: ERP УХ или 1С: ERP на уровне ведущего консультанта, с пониманием всех регистров, модели учета, настроек, с опытом закрытия месяца, с уклоном на блок учета затрат и производство: отличное знание документов и аналитик производства (заказ на производство, этапы производства, ДПиМ, статьи калькуляции, МВЗ, статьи расходов, ресурсные спецификации и т.д.) — Участие в проекте по внедрению рег.учета, от переноса остатков до закрытия года. — Опыт написания ТЗ, проектных решений, концептуальный дизайн. — Опыт в проектах полного цикла, включая интеграционные обмены. — От этапа обследования до ввода в ПЭ. — Желателен опыт перехода с 1С:УПП на 1С:ERPУХ Условия: — Командировки: нет — Локация: РФ — Формат работы: Гибрид (2-3 дня в неделю в офисе Заказчика МСК)/ 1 неделю в месяц из других регионов. — График: Full time
Location: Lisbon, Portugal Workplace: remote WELCOME TO OLX We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors. Join OLX and see how far you can go. About the Role We are a large-scale consumer marketplace building AI-native product experiences across multiple markets. Trust and Safety is not a defensive function here - it is a strategic growth lever. A platform users trust converts better, retains longer, and earns stronger word of mouth. Fraud, abuse, and bad actors actively destroy the value we create; eliminating them is product work at its core. We are looking for a Lead Product Manager to own the Trust & Safety product agenda end-to-end. You will define the strategy for how we detect and prevent fraud, protect user integrity, and keep our marketplace safe - while building systems that are intelligent, proportionate, and do not create friction for the millions of legitimate users who rely on us every day. AI is central to how you will do this: not as an add-on, but as the foundation of a new generation of proactive, signal-driven safety infrastructure. This role can be based in Spain, Portugal or Poland. What you will do: Own the Trust & Safety product strategy and roadmap translating business risk and user insight into a clear, prioritised plan. Shift the function from reactive incident response to proactive, intelligence-driven fraud prevention: build the Risk Engine, data signals intelligence, anomaly detection, and investigation tooling that make this possible. Ship AI-native T&S product experiences: partner with Data Science and Engineering to design, prototype, and productionise real-time detection and decisioning systems using ML models, LLMs, and behavioural signals. Balance fraud mitigation with growth protection—ensuring T&S interventions do not unnecessarily create friction for legitimate users or throttle marketplace supply/demand. Make hard, evidence-based trade-off decisions. Define and track the right T&S success metrics: fraud loss rates, false positive/negative rates, time-to-resolution, user trust scores, and financial exposure. Communicate impact in business terms to senior leadership. Partner closely with Engineering leads, Data Science, Legal, Compliance, and Operations—holding shared accountability for outcomes and navigating competing priorities. Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, detection model performance, and contributor/user impact at scale. Establish business cases quantifying fraud losses and ROI of prevention investments; secure resources and drive prioritisation grounded in data. Ensure products and strategies meet local and regional compliance, legal, and security requirements across all markets. Apply AI to how you operate as a PM: faster threat analysis, synthetic user research on abuse patterns, AI-assisted spec writing, automated experimentation pipelines—whatever moves the needle on velocity. Represent Trust & Safety at the leadership level, presenting strategy, risk posture, and results clearly to executive audiences. What we are looking for: Significant product management experience in the digital sector: consumer facing platform, marketplace, mobility, e-commerce, classifieds, fintech, or similar high scale environment. Proven experience owning trust related products or problem spaces such as Trust & Safety, Fraud Prevention, Risk, Identity & Verification, Marketplace Integrity, Account Security, Abuse Prevention, Payments Risk, or Compliance Technology. Track record of building scalable systems that proactively detect, prevent, and mitigate abuse, fraud, risk, or other trust related issues, rather than relying solely on manual or operational processes. Strong analytical and data driven mindset, with experience defining success metrics, evaluating impact, and making prioritization decisions based on evidence and measurable outcomes. Experience partnering closely with Engineering, Data Science, Operations, Legal, Compliance, and other cross-functional stakeholders to deliver complex products in regulated or high-risk environments. Experience in vendor management and collaboration. Experience building, deploying, or working closely with machine learning, AI, risk scoring, decisioning, detection, recommendation, or automation systems. Hands-on experience with AI-powered trust or fraud products is a plus. Demonstrated ability to balance user experience, marketplace growth, operational efficiency, and risk mitigation, making thoughtful trade offs that protect both users and the business. Comfortable operating in ambiguity, taking ownership of complex problem spaces, influencing senior stakeholders, and driving strategy and execution across multiple teams. Strong core product muscle that transfers across fraud domains—you've stepped into unfamiliar threat vectors, oriented fast, and delivered. Domain specificity matters; rigid domain lock-in does not. Well versed in building, iterating core Data (Science) products at scale Nice to Have: Experience building trust, risk, fraud, or safety products across multiple international markets and regulatory environments. Familiarity with emerging regulations and industry trends affecting online platforms, digital marketplaces, payments, AI, and consumer trust. If you're excited by the opportunity to solve complex trust challenges at scale and build products that make a meaningful difference to millions of users, we'd love to hear from you. This is a role for someone who enjoys tackling ambiguous problems, partnering across disciplines, and shaping the future of trust in a modern, AI-powered marketplace. Diversity, Equity and Inclusion at OLX OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us! OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.
Location: Remote Portugal, Portugal Workplace: remote WELCOME TO OLX We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors. Join OLX and see how far you can go. About the Role We are a large-scale consumer marketplace building AI-native product experiences across multiple markets. Trust and Safety is not a defensive function here - it is a strategic growth lever. A platform users trust converts better, retains longer, and earns stronger word of mouth. Fraud, abuse, and bad actors actively destroy the value we create; eliminating them is product work at its core. We are looking for a Lead Product Manager to own the Trust & Safety product agenda end-to-end. You will define the strategy for how we detect and prevent fraud, protect user integrity, and keep our marketplace safe - while building systems that are intelligent, proportionate, and do not create friction for the millions of legitimate users who rely on us every day. AI is central to how you will do this: not as an add-on, but as the foundation of a new generation of proactive, signal-driven safety infrastructure. This role can be based in Spain, Portugal or Poland. What you will do: Own the Trust & Safety product strategy and roadmap translating business risk and user insight into a clear, prioritised plan. Shift the function from reactive incident response to proactive, intelligence-driven fraud prevention: build the Risk Engine, data signals intelligence, anomaly detection, and investigation tooling that make this possible. Ship AI-native T&S product experiences: partner with Data Science and Engineering to design, prototype, and productionise real-time detection and decisioning systems using ML models, LLMs, and behavioural signals. Balance fraud mitigation with growth protection—ensuring T&S interventions do not unnecessarily create friction for legitimate users or throttle marketplace supply/demand. Make hard, evidence-based trade-off decisions. Define and track the right T&S success metrics: fraud loss rates, false positive/negative rates, time-to-resolution, user trust scores, and financial exposure. Communicate impact in business terms to senior leadership. Partner closely with Engineering leads, Data Science, Legal, Compliance, and Operations—holding shared accountability for outcomes and navigating competing priorities. Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, detection model performance, and contributor/user impact at scale. Establish business cases quantifying fraud losses and ROI of prevention investments; secure resources and drive prioritisation grounded in data. Ensure products and strategies meet local and regional compliance, legal, and security requirements across all markets. Apply AI to how you operate as a PM: faster threat analysis, synthetic user research on abuse patterns, AI-assisted spec writing, automated experimentation pipelines—whatever moves the needle on velocity. Represent Trust & Safety at the leadership level, presenting strategy, risk posture, and results clearly to executive audiences. What we are looking for: Significant product management experience in the digital sector: consumer facing platform, marketplace, mobility, e-commerce, classifieds, fintech, or similar high scale environment. Proven experience owning trust related products or problem spaces such as Trust & Safety, Fraud Prevention, Risk, Identity & Verification, Marketplace Integrity, Account Security, Abuse Prevention, Payments Risk, or Compliance Technology. Track record of building scalable systems that proactively detect, prevent, and mitigate abuse, fraud, risk, or other trust related issues, rather than relying solely on manual or operational processes. Strong analytical and data driven mindset, with experience defining success metrics, evaluating impact, and making prioritization decisions based on evidence and measurable outcomes. Experience partnering closely with Engineering, Data Science, Operations, Legal, Compliance, and other cross-functional stakeholders to deliver complex products in regulated or high-risk environments. Experience in vendor management and collaboration. Experience building, deploying, or working closely with machine learning, AI, risk scoring, decisioning, detection, recommendation, or automation systems. Hands-on experience with AI-powered trust or fraud products is a plus. Demonstrated ability to balance user experience, marketplace growth, operational efficiency, and risk mitigation, making thoughtful trade offs that protect both users and the business. Comfortable operating in ambiguity, taking ownership of complex problem spaces, influencing senior stakeholders, and driving strategy and execution across multiple teams. Strong core product muscle that transfers across fraud domains—you've stepped into unfamiliar threat vectors, oriented fast, and delivered. Domain specificity matters; rigid domain lock-in does not. Well versed in building, iterating core Data (Science) products at scale Nice to Have: Experience building trust, risk, fraud, or safety products across multiple international markets and regulatory environments. Familiarity with emerging regulations and industry trends affecting online platforms, digital marketplaces, payments, AI, and consumer trust. If you're excited by the opportunity to solve complex trust challenges at scale and build products that make a meaningful difference to millions of users, we'd love to hear from you. This is a role for someone who enjoys tackling ambiguous problems, partnering across disciplines, and shaping the future of trust in a modern, AI-powered marketplace. Diversity, Equity and Inclusion at OLX OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us! OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.
Location: Barcelona, Spain Workplace: remote WELCOME TO OLX We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors. Join OLX and see how far you can go. About the Role We are a large-scale consumer marketplace building AI-native product experiences across multiple markets. Trust and Safety is not a defensive function here - it is a strategic growth lever. A platform users trust converts better, retains longer, and earns stronger word of mouth. Fraud, abuse, and bad actors actively destroy the value we create; eliminating them is product work at its core. We are looking for a Lead Product Manager to own the Trust & Safety product agenda end-to-end. You will define the strategy for how we detect and prevent fraud, protect user integrity, and keep our marketplace safe - while building systems that are intelligent, proportionate, and do not create friction for the millions of legitimate users who rely on us every day. AI is central to how you will do this: not as an add-on, but as the foundation of a new generation of proactive, signal-driven safety infrastructure. This role can be based in Spain, Portugal or Poland. What you will do: Own the Trust & Safety product strategy and roadmap translating business risk and user insight into a clear, prioritised plan. Shift the function from reactive incident response to proactive, intelligence-driven fraud prevention: build the Risk Engine, data signals intelligence, anomaly detection, and investigation tooling that make this possible. Ship AI-native T&S product experiences: partner with Data Science and Engineering to design, prototype, and productionise real-time detection and decisioning systems using ML models, LLMs, and behavioural signals. Balance fraud mitigation with growth protection—ensuring T&S interventions do not unnecessarily create friction for legitimate users or throttle marketplace supply/demand. Make hard, evidence-based trade-off decisions. Define and track the right T&S success metrics: fraud loss rates, false positive/negative rates, time-to-resolution, user trust scores, and financial exposure. Communicate impact in business terms to senior leadership. Partner closely with Engineering leads, Data Science, Legal, Compliance, and Operations—holding shared accountability for outcomes and navigating competing priorities. Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, detection model performance, and contributor/user impact at scale. Establish business cases quantifying fraud losses and ROI of prevention investments; secure resources and drive prioritisation grounded in data. Ensure products and strategies meet local and regional compliance, legal, and security requirements across all markets. Apply AI to how you operate as a PM: faster threat analysis, synthetic user research on abuse patterns, AI-assisted spec writing, automated experimentation pipelines—whatever moves the needle on velocity. Represent Trust & Safety at the leadership level, presenting strategy, risk posture, and results clearly to executive audiences. What we are looking for: Significant product management experience in the digital sector: consumer facing platform, marketplace, mobility, e-commerce, classifieds, fintech, or similar high scale environment. Proven experience owning trust related products or problem spaces such as Trust & Safety, Fraud Prevention, Risk, Identity & Verification, Marketplace Integrity, Account Security, Abuse Prevention, Payments Risk, or Compliance Technology. Track record of building scalable systems that proactively detect, prevent, and mitigate abuse, fraud, risk, or other trust related issues, rather than relying solely on manual or operational processes. Strong analytical and data driven mindset, with experience defining success metrics, evaluating impact, and making prioritization decisions based on evidence and measurable outcomes. Experience partnering closely with Engineering, Data Science, Operations, Legal, Compliance, and other cross-functional stakeholders to deliver complex products in regulated or high-risk environments. Experience in vendor management and collaboration. Experience building, deploying, or working closely with machine learning, AI, risk scoring, decisioning, detection, recommendation, or automation systems. Hands-on experience with AI-powered trust or fraud products is a plus. Demonstrated ability to balance user experience, marketplace growth, operational efficiency, and risk mitigation, making thoughtful trade offs that protect both users and the business. Comfortable operating in ambiguity, taking ownership of complex problem spaces, influencing senior stakeholders, and driving strategy and execution across multiple teams. Strong core product muscle that transfers across fraud domains—you've stepped into unfamiliar threat vectors, oriented fast, and delivered. Domain specificity matters; rigid domain lock-in does not. Well versed in building, iterating core Data (Science) products at scale Nice to Have: Experience building trust, risk, fraud, or safety products across multiple international markets and regulatory environments. Familiarity with emerging regulations and industry trends affecting online platforms, digital marketplaces, payments, AI, and consumer trust. If you're excited by the opportunity to solve complex trust challenges at scale and build products that make a meaningful difference to millions of users, we'd love to hear from you. This is a role for someone who enjoys tackling ambiguous problems, partnering across disciplines, and shaping the future of trust in a modern, AI-powered marketplace. Diversity, Equity and Inclusion at OLX OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us! OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.
Location: Remote Spain, Spain Workplace: remote WELCOME TO OLX We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible. We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust. Our brands – including AutoTrader, OLX, Otomoto Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors. Join OLX and see how far you can go. About the Role We are a large-scale consumer marketplace building AI-native product experiences across multiple markets. Trust and Safety is not a defensive function here - it is a strategic growth lever. A platform users trust converts better, retains longer, and earns stronger word of mouth. Fraud, abuse, and bad actors actively destroy the value we create; eliminating them is product work at its core. We are looking for a Lead Product Manager to own the Trust & Safety product agenda end-to-end. You will define the strategy for how we detect and prevent fraud, protect user integrity, and keep our marketplace safe - while building systems that are intelligent, proportionate, and do not create friction for the millions of legitimate users who rely on us every day. AI is central to how you will do this: not as an add-on, but as the foundation of a new generation of proactive, signal-driven safety infrastructure. This role can be based in Spain, Portugal or Poland. What you will do: Own the Trust & Safety product strategy and roadmap translating business risk and user insight into a clear, prioritised plan. Shift the function from reactive incident response to proactive, intelligence-driven fraud prevention: build the Risk Engine, data signals intelligence, anomaly detection, and investigation tooling that make this possible. Ship AI-native T&S product experiences: partner with Data Science and Engineering to design, prototype, and productionise real-time detection and decisioning systems using ML models, LLMs, and behavioural signals. Balance fraud mitigation with growth protection—ensuring T&S interventions do not unnecessarily create friction for legitimate users or throttle marketplace supply/demand. Make hard, evidence-based trade-off decisions. Define and track the right T&S success metrics: fraud loss rates, false positive/negative rates, time-to-resolution, user trust scores, and financial exposure. Communicate impact in business terms to senior leadership. Partner closely with Engineering leads, Data Science, Legal, Compliance, and Operations—holding shared accountability for outcomes and navigating competing priorities. Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, detection model performance, and contributor/user impact at scale. Establish business cases quantifying fraud losses and ROI of prevention investments; secure resources and drive prioritisation grounded in data. Ensure products and strategies meet local and regional compliance, legal, and security requirements across all markets. Apply AI to how you operate as a PM: faster threat analysis, synthetic user research on abuse patterns, AI-assisted spec writing, automated experimentation pipelines—whatever moves the needle on velocity. Represent Trust & Safety at the leadership level, presenting strategy, risk posture, and results clearly to executive audiences. What we are looking for: Significant product management experience in the digital sector: consumer facing platform, marketplace, mobility, e-commerce, classifieds, fintech, or similar high scale environment. Proven experience owning trust related products or problem spaces such as Trust & Safety, Fraud Prevention, Risk, Identity & Verification, Marketplace Integrity, Account Security, Abuse Prevention, Payments Risk, or Compliance Technology. Track record of building scalable systems that proactively detect, prevent, and mitigate abuse, fraud, risk, or other trust related issues, rather than relying solely on manual or operational processes. Strong analytical and data driven mindset, with experience defining success metrics, evaluating impact, and making prioritization decisions based on evidence and measurable outcomes. Experience partnering closely with Engineering, Data Science, Operations, Legal, Compliance, and other cross-functional stakeholders to deliver complex products in regulated or high-risk environments. Experience in vendor management and collaboration. Experience building, deploying, or working closely with machine learning, AI, risk scoring, decisioning, detection, recommendation, or automation systems. Hands-on experience with AI-powered trust or fraud products is a plus. Demonstrated ability to balance user experience, marketplace growth, operational efficiency, and risk mitigation, making thoughtful trade offs that protect both users and the business. Comfortable operating in ambiguity, taking ownership of complex problem spaces, influencing senior stakeholders, and driving strategy and execution across multiple teams. Strong core product muscle that transfers across fraud domains—you've stepped into unfamiliar threat vectors, oriented fast, and delivered. Domain specificity matters; rigid domain lock-in does not. Well versed in building, iterating core Data (Science) products at scale Nice to Have: Experience building trust, risk, fraud, or safety products across multiple international markets and regulatory environments. Familiarity with emerging regulations and industry trends affecting online platforms, digital marketplaces, payments, AI, and consumer trust. If you're excited by the opportunity to solve complex trust challenges at scale and build products that make a meaningful difference to millions of users, we'd love to hear from you. This is a role for someone who enjoys tackling ambiguous problems, partnering across disciplines, and shaping the future of trust in a modern, AI-powered marketplace. Diversity, Equity and Inclusion at OLX OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us! OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.
Joi Lab (joilab.ai) is an open research arm building open-source generative models, agent architectures, and training infrastructure. All code, weights, and data are public. The focus is on true AI agency with persistent memory, self-modification, and self-authored capabilities, not just ChatGPT wrappers. The role involves working with huge models up to 1 trillion+ parameters, ensuring fast and cheap production inference, and technologies like SGLang, caching, distributed inference, and post-training. The candidate will also set the technical direction for NLP and CV engineers. Требования к кандидату: — 5+ years of experience in ML engineering — Deep hands-on experience optimizing LLM inference — Proficiency with PyTorch and related libraries — Experience with distributed inference/training of large models — Strong understanding of inference optimization techniques — Proven technical leadership in guiding engineers — Backend engineering experience (Python, Go, C#) — Advanced English or Russian language skills
Location: Paris; New York; London Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The role Mistral is building a sovereign AI cloud. Our inference platform already serves production traffic at scale. We are hiring a Lead Product Manager to own the inference portfolio within our Cloud & Inference organization. You'll set strategy, write specs, sit with customers running production traffic, and work across our inference, infrastructure, and go-to-market teams to deliver real customer impact. Example problems you may work on include figuring out the next inference product we should launch to help our customers scale their AI workloads or how we cut fraudulent free-tier usage without adding friction for legitimate users. You will work on state of the art infrastructure, in close collaboration with our science and research engineering teams. Your job is to turn that infrastructure into products that AI-native startups and enterprises pay for, integrated with our developer platform Studio. You will operate as an individual contributor first — taking end-to-end ownership of complex and significant product lines — while building the foundation for the inference PM team as the portfolio grows. The size and shape of the team reporting into the role will be defined together with the VP Product once you're in place; from day one the expectation is hands-on product leadership, not people management. You will be the first PM fully dedicated to inference and the most senior product hire in the space. You will report to the VP Product - Cloud & Inference, and work day-to-day with our inference engineering teams in the US and Europe. What you'll do - Strategy and vision: define the vision, strategy, and annual goals for the inference portfolio, aligned with customer needs and company objectives. Benchmark the managed-inference field and pick where we win. - Roadmap and execution: own the full lifecycle for serverless inference, dedicated endpoints, and adjacent services. Prioritize, ship, measure, iterate. Economics: own adoption, revenue contribution, and gross margin for your products. Treat cost-per-token, unit economics, and capacity tradeoffs as product decisions, and partner with GTM, Finance and Marketing on pricing, packaging, and launches. - Customers: spend real time with AI-native startups and enterprises running advanced production workloads. Turn their constraints, like latency, throughput, compliance, and cost, into roadmap choices. - Engineering partnership: work daily with inference engineering and the cloud infrastructure teams behind our data centers on capacity planning, scheduling, routing, and reliability. - Research and open source: track open-source inference advances and emerging model architectures, and turn them into performance and efficiency gains for the product. - Team building: as the portfolio scales, help shape and grow the inference PM team — hiring, mentoring, and setting the product bar. What we're looking for - Deep product experience in tech and infrastructure with a track record of bringing inference, cloud infrastructure, or large-scale distributed systems to market. You have built robust, at-scale AI infrastructure first-hand. - An engineering background before moving into product management. - You have taken an infra or inference product from early stage to material revenue and adoption, owning complex and significant product lines end to end. - Player-coach disposition: you lead from the front — hands-on product work now, with the range and appetite to build and coach a team as we scale. - Fluency in the economics of the business: gross margin, unit economics, and the tradeoffs behind token pricing and GPU capacity. - High ownership and a strong bias for action. You prototype with AI coding tools, write your own specs, and unblock yourself without waiting for engineers or designers. - Low ego, comfort in ambiguity, and credibility with executives, engineers, and customers alike. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.
Задачи: — Вести задачи полностью — от идеи до продакшна — Разрабатывать и развивать компоненты платформы — Проектировать архитектуру и интеграции — Работать с требованиями, моделями данных и алгоритмами расчётов — Общаться напрямую с конечными пользователями — Проводить code review и участвовать в технических обсуждениях — Использовать AI-инструменты на всех этапах разработки Требования: — От 8 лет коммерческой разработки сложных систем — C#, .NET, ASP.NET, Angular — Уверенное использование AI-инструментов — Понимание архитектуры информационных систем и интеграций — Реальный опыт с Claude Code: CLAUDE.md, структурированные промпты, анализ кодовой базы, генерация production-ready кода, рефакторинг, тесты, PR и аудит безопасности — Понимание ограничений LLM и построение безопасного HITL-процесса — Опыт работы с DWH/BI
Location: Remote-Friendly, United States About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for a State and Local Affairs Lead to engage with state and local governments in the Western United States, advancing AI policy, legislation, and regulation that supports Anthropic's mission of ensuring that the world safely makes the transition through transformative AI. In this role, you will report to Anthropic's Head of Western State and Local Affairs and coordinate with our Policy leadership, Communications, and Legal teams. You will own Anthropic's relationships and legislative and regulatory work across many Western states, including a support role in California —engagement with state legislatures, governors' offices, attorneys general, state agencies, and local governments. You will travel regularly across the region. Successful candidates will demonstrate a track record of political strategy and execution—with specific examples of how you have contributed to complex policy campaigns, built durable relationships with elected officials and community leaders, supported legislative and regulatory outcomes, and executed with accountability and focus in fast-moving environments. Anthropic is equal parts research lab, policy think-tank, and technology startup. We care deeply about safe development of AI systems, and build partnership with governments through proactive, opinionated, substantive policy conversations. We recognize that our approach to AI policy is distinctive—grounded in honest assessment of technological trajectories and authentic concern for safe scaling—and we need a regional lead who can bring that positioning to life at the state and local level. This role offers an opportunity to be part of building a high-impact state affairs operation at a critical moment for AI policy. You will be responsible for executing on strategic priorities across your region, building relationships with government stakeholders, and contributing to the broader state affairs function. Key responsibilities Serve as Anthropic's lead for state and local government affairs across many Western states, working in close coordination with the Head of Western States and other Regional State and Local Affairs Leads Build and maintain relationships with state legislators, legislative staff, governors' offices, attorneys general, and state agency leaders across your region Engage directly with local officials whose decisions affect Anthropic's work—mayors, city councils, county commissions, and economic development boards Track state and local legislation and regulatory proceedings affecting AI and the technology sector, provide analysis and intelligence to inform company strategy, and represent Anthropic's positions Build durable partnerships with local and regional organizations, including chambers of commerce, economic development groups, labor organizations, universities, and school districts Represent Anthropic at legislative hearings, regional events, and public forums, including with audiences who are skeptical of AI Work with the Communications team to develop clear, accurate messaging for regional policy campaigns Translate Anthropic's technical research and policy positions into engagement strategies tailored to Western state political environments Manage the outside advisors and registered lobbyists who support Anthropic's work in your region Coordinate with Anthropic's policy, communications, legal, and executive teams to ensure that regional activity aligns with company-wide positioning Minimum qualifications Align with our mission and embrace the imperative of policy impact and change Have experience in state and local government affairs, political strategy, or legislative roles, with demonstrated success contributing to legislative and regulatory outcomes Have existing relationships with state and local leaders in the West, including legislators, governors' offices, attorneys general, or county and municipal officials Understand how state legislatures and executive branches work—committee processes, legislative and regulatory procedures, and how to move policy forward—and understand where local authority begins and ends Have a track record of executing on strategic objectives and delivering measurable outcomes in government affairs roles Are prepared to travel regularly across the region Preferred qualifications Have 8+ years of experience in state and local government affairs, political strategy, or legislative roles Have experience building partnerships with external organizations including chambers of commerce, economic development groups, labor organizations, and universities Have exposure to technology policy or emerging technology regulation; you understand the unique challenges of navigating policy for rapidly evolving technologies Demonstrate understanding of how to build coalitions and identify aligned constituencies to advance shared objectives Can manage multiple priorities and stakeholder relationships across different states and adapt to different political environments Can work well under time pressure and manage competing demands Can translate complex technical topics into clear, accessible language for policymakers and residents alike Have experience working with communications teams to develop effective messaging for policy campaigns Are comfortable being honest about tradeoffs, including in rooms where people disagree with us Are drawn to working with an organization that approaches AI policy with intensity and intellectual honesty The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
Location: Bengaluru, India We are looking for a lead-level Accessibility QA Engineer who still tests hands-on. You will guide engineering on accessible implementation, run knowledge sessions for engineering and product, and write an accessibility plan for a platform. The plan states the testing the platform needs and the support and budget it does not yet have. Quality engineering uses that plan to request both. You will audit against WCAG 2.2, targeting AA, with awareness of AAA where relevant, and you need working knowledge of WCAG 2.1 and 2.2 at A and AA. Audits use screen readers, keyboard-only navigation, and automated scanners. You will own the accessibility testing process, from test plans, severity, regression, and sign-off through CI gates, remediation guidance, and stakeholder reporting. An accessibility certification is not required. You will manage and mentor the accessibility QA team, and report conformance and regulatory risk in writing that both engineers and legal or compliance staff can use. This position is intended for Hyderabad-based candidates who are available to work from the office. Our client delivers web and mobile products that must meet US and European accessibility requirements. Accessibility is managed continuously through early acceptance criteria, automated checks, hands-on testing with assistive technology, remediation, and conformance reporting. Conduct accessibility audits and risk assessments against WCAG 2.2 Level A and AA, with awareness of relevant Level AAA criteria. Test semantic HTML, WAI-ARIA, keyboard interaction, screen-reader behavior, native mobile applications, the DOM, and the accessibility tree. Create and review test plans, test cases, and automated accessibility tests using axe-core with Playwright, Cypress, Selenium, or comparable frameworks. Write platform accessibility plans and maintain the testing process, including priorities, definition of done, regression, release-readiness, approved exceptions, risk acceptance, and remediation tracking. Shift accessibility left with product, design, and engineering through accessible components, early acceptance criteria, pull-request checks, automated scanners, and CI/CD gates. Track conformance, maintain Accessibility Conformance Reports using the appropriate VPAT template, evaluate vendor accessibility claims, and communicate regulatory risk. Establish accessibility quality metrics, dashboards, and stakeholder reporting. Apply AI-assisted testing and reporting tools with human verification of generated results. Lead, mentor, and develop the accessibility QA team through planning, coaching, review, and calibration. Train product, design, engineering, and QA teams, and provide actionable remediation guidance through validation. Produce technical findings, defect reports, and stakeholder communications for engineering, business, and Legal and Compliance audiences. Lead-level accessibility experience, including hands-on testing and building or operating an accessibility testing process. Deep knowledge of WCAG 2.2 testing and conformance, plus US and European requirements including the ADA, Section 508, EN 301 549, and the EAA. Practical fluency in WAI-ARIA 1.2, ARIA Authoring Practices, semantic HTML, CSS, accessible names, and expected keyboard interactions. Proficiency with NVDA, JAWS, VoiceOver, TalkBack, keyboard-only testing, native mobile accessibility, and DOM and accessibility-tree inspection. Experience conducting accessibility audits and risk assessments for web and mobile products. Experience creating test assets and automated accessibility tests using axe-core with Playwright, Cypress, Selenium, or comparable frameworks. Experience selecting automated scanners and integrating accessibility into design reviews, pull requests, and CI/CD. Experience writing accessibility plans and defining testing scope, priorities, quality gates, exceptions, and remediation tracking. Experience authoring and reviewing Accessibility Conformance Reports, selecting the appropriate VPAT template, and evaluating vendor accessibility claims. Experience defining accessibility metrics and using AI-assisted tools with appropriate human verification. Experience leading and training QA or accessibility teams and working with product, design, and engineering. Ability to explain user impact and provide actionable remediation guidance through implementation and validation. Strong written communication for engineering, business, and Legal and Compliance audiences. IAAP certification such as CPACC, WAS, or CPWA, or Section 508 Trusted Tester certification. PDF and document accessibility experience, including tagged PDF structure and the PAC tool. Knowledge of cognitive and low-vision accessibility. Experience contributing to or auditing an accessible design system. Experience with accessibility maturity models.
Задачи: — Участие в проектной деятельности по созданию, развитию, тиражированию и внедрению государственных информационных систем; — Моделирование бизнес-процессов и систем с использованием BPMN и UML; — Формирование сценариев использования системы для задач разработки; — Участие в проработке решений совместно с командами разработки, тестирования и смежными подразделениями; — Извлечение, сбор, анализ, разработка и документирование требований; — Описание интеграционных взаимодействий, требований к API и обмену данными между системами; — Написание ТЗ и ЧТЗ; — Подготовка и актуализация эксплуатационной и пользовательской документации; — Документирование ранее разработанных подсистем. Будет плюсом: — Опыт работы на проектах ДИТ Москвы; — Опыт составления расчетов НМЦК с использованием методики 3-р; — Опыт сопровождения генеральных подрядных контрактов и организации работы с субподрядчиками (подготовка контрактов, отчетная документация). Требования: — Опыт подготовки технических заданий и частных технических заданий; — Навык работы с наследуемой аналитикой: умение погружаться в модуль, где часть требований уже описана, выявлять пробелы и продолжать работу на основе чужой документации; — Понимание форматов обмена данными: JSON, XML, табличные и файловые форматы; — Знание SQL на уровне простых запросов, методологии проектирования реляционных баз данных; — Умение моделировать процессы, сущности, связи, статусы, переходы и правила обработки в нотации BPMN 2.0; — Знание нотаций: BPMN 2.0, UML, EPC, С4, ER-диаграммы; — Уверенное владение современными технологиями интеграции (SOAP, REST, Web- и http-сервисы, XML и Json, Kafka и RabbitMQ); — Уверенное чтение и редактирование спецификаций API (OpenAPI/Swagger), умение обсуждать технические детали с разработчиками. Условия: — Компенсация (фикс) обсуждается по результатам собеседования в зависимости от профессионального опыта; — График работы 5/2; — Гибкость рабочего времени (по приходу на работу до 11.00); — Оформление в соответствии с ТК РФ (оплата отпусков и больничных); — Соцпакет (ДМС после испытательного срока); — Офис м. Добрынинская, Павелецкая (7 мин пешком от метро).
Задачи: — Развивать архитектуру модульного backend-приложения, REST API и бизнес-логику, включая валидацию, обработку ошибок и документацию; — Проектировать модели данных и миграции, оптимизировать запросы и кеширование; — Развивать аутентификацию, авторизацию и ролевую модель; — Контролировать доступ к внешним данным и управлять подключениями; — Программно управлять контейнерными средами: от создания и ожидания готовности до обработки сбоев и освобождения ресурсов; — Развивать AI-функции: потоковые диалоги, хранение истории, сокращение контекста, агентные инструменты и RAG — от подготовки данных до использования найденного контекста в ответах; — Обеспечивать проверку прав, согласованность состояния и обработку ошибок при выполнении удалённых операций и вызовах инструментов; — Писать тесты, диагностировать production-проблемы, развивать наблюдаемость, согласовывать API с frontend-разработчиками. Требования: — Уверенное владение Java, опыт production-разработки на Spring Boot и готовность работать с Java 21 и Spring Boot 3.5; — Опыт проектирования архитектуры и REST API, самостоятельного принятия технических решений и развития существующей кодовой базы; — Знание Spring MVC, Spring Security, Spring Data JPA/Hibernate, валидации запросов и документирования API через OpenAPI; — Практический опыт PostgreSQL, SQL и Liquibase; — Понимание транзакций, индексов, оптимизации запросов, кеширования и пулов подключений; — Опыт подключения внешних реляционных источников, включая MS SQL Server, и разграничения доступа к данным; — Опыт реализации аутентификации и авторизации с JWT, OAuth2 и OIDC/SSO; — Владение Maven и Git; — Опыт OpenFeign для HTTP-интеграций, JGit для работы с репозиториями, MapStruct для преобразования объектов и Ehcache для кеширования; — Практический опыт Docker и программного управления контейнерами через docker-java; — Знание Docker Compose, Docker Swarm, Traefik и GitLab CI на уровне настройки окружения, понимания сборки и развёртывания, диагностики проблем; — Практический опыт LLM API и LangChain4j: потоковые ответы через SSE, история диалогов и управление контекстом; — Опыт построения RAG, работы с эмбеддингами и векторным поиском в Qdrant; — Опыт агентных сценариев, вызова инструментов и MCP-интеграций с проверкой прав и обработкой ошибок; — Опыт модульного и интеграционного тестирования с JUnit и Testcontainers, включая проверки с базами данных; — Навыки диагностики по логам, метрикам и трассировкам с использованием Actuator, Micrometer, OpenTelemetry и OTLP; — Понимание трассировки AI-вызовов; — Понимание React и TypeScript на уровне согласования API-контрактов и совместной диагностики frontend/backend; — Понимание специфики корпоративного ПО для внешних заказчиков: ролевой модели и безопасности, интеграций с их ИТ-ландшафтом, требований к надёжности и влияния изменений на процессы пользователей. Что важно: — Уметь общаться с бизнес-заказчиками, выявлять реальную потребность за первоначальным запросом, уточнять требования, объяснять варианты решения и переводить бизнес-задачи в техническую реализацию; — Готовность работать итерационно: сформулировать гипотезу, обсудить ее, проверить, скорректировать и двигаться дальше; — Самостоятельно прорабатывать задачи, проверять гипотезы и учитывать обратную связь; — Декомпозировать работу, оценивать сроки, согласовывать приоритеты и своевременно сообщать о рисках и необходимости помощи; — Отвечать за результат до эксплуатации, учитывать пограничные сценарии и последствия изменений; — Аргументировать решения, слышать коллег, конструктивно давать и принимать обратную связь; — Проводить code review, делиться знаниями и помогать другим разработчикам; — Находить баланс между пользой для пользователя, качеством, сложностью реализации, техническим долгом и сроками. Условия: — Работа над корпоративным продуктом, объединяющим backend, интеграции, контейнерные среды и AI; — Развитие экспертизы в AI-инженерии и агентных системах; — Оформление по ТК РФ, после испытательного срока подключение к ДМС, компенсация спортивных программ; — Работа в аккредитованной IT-компании (льготы IT ипотеки, отсрочки); — Возможность работы в одном из офисов или удаленно, преимущественно по желанию сотрудника; — График работы 5/2, гибкое начало рабочего дня, отсутствие дресс-кодов и только полезная бюрократия; — Интересные корпоративные мероприятия, клубы по интересам; — Система профессионального, карьерного и финансового развития.
Location: New York, NY (HQ); San Francisco, CA; Remote (US) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT PRODUCTION ENGINEERING Production Engineering is Ramp's infrastructure ownership layer. We exist to make Ramp faster, more reliable, and more scalable — and we do that by being embedded in the problems, not adjacent to them. A few things that define how we operate: - One team, one company, one objective. There is no "infra team" and "product team" — there is Ramp. We share the company's goals as our own. When a product team struggles with reliability or scalability, that is our struggle. - If reliability or scalability is at risk, we own it. We don't wait to be invited, and we don't ask whose code it is. If a system is slow, if it breaks, if it won't scale — that's ours to lead, regardless of where it lives in the stack. - We go first, and we go fast. When the path isn't obvious, we don't wait for someone else to find it. We move with urgency, propose the solution, align the stakeholders, and stay in until it's done — not until our ticket is closed. - We lead the way. We find the next problem before it finds us. And when we solve it, we don't just fix it for ourselves — the patterns and standards we establish become the foundation the rest of Ramp builds on. That's not a side effect of the job; it's the job. - We stay calibrated. Speed means nothing if we're moving in the wrong direction. We regularly stop and ask honestly whether what we're working on is still the highest-leverage thing we could be doing — the discipline that makes sure our effort compounds toward what actually matters. You cannot build the future of finance on shaky infrastructure. OUR TEAMS Production Engineering is organized into teams — but we think about teams differently. Teams are mutable. We build them around what needs to be done, not around what we need to do given the teams we already have. The structure below reflects our current priorities; it will evolve as Ramp does. Right now, we operate across four areas: - Compute — the foundation everything runs on: container orchestration, networking, load balancing, edge infrastructure, and the deployment systems that get code from engineers' laptops to production reliably and at scale - Storage — databases, caching, object storage, and the data infrastructure that underpins everything - Workflows & Messaging — the systems that power Ramp's financial workflows and event-driven architecture - Developer Infrastructure — the platform that makes every builder at Ramp faster and more autonomous: observability, cost attribution, and CI/CD systems that give teams visibility into what they build and what it costs WHAT YOU'LL DO Production Engineers at Ramp are full software engineers who happen to specialize in infrastructure. You write production code, you own systems end-to-end, and you drive technical outcomes across the organization — not just within your team. As a Tech Lead & Manager, you are a hands-on player-coach: you will lead and grow a team while remaining directly engaged in the technical work. Management at Ramp does not mean stepping away from the technology or the code. You will help set direction, develop engineers, and work alongside the team to deliver consequential infrastructure outcomes. Day to day, you will: - Build, coach, and grow a high-performing team. Create clarity, give direct feedback, mentor engineers, and help each person expand their technical judgment, ownership, and leadership. - Set technical direction for your team’s domain. Identify the highest-leverage problems, define a path forward, bring the right people along, and stay engaged with the team until the work is delivered. - Build and operate critical infrastructure across Ramp's compute, storage, messaging, and observability stack — owning the systems that handle real financial transactions at scale. - Drive architectural change — not just flag problems. When you surface a reliability or scalability issue, you own the path forward: you propose the solution, find the owners across engineering, and stay in until it's resolved. - Partner with product teams at the design phase — reviewing architectures, embedding golden paths, and making it easy to build correctly the first time. - Build Ramp's next level of scale — you'll be a hands-on contributor to the most consequential infrastructure shift happening right now: our move to a cellular architecture, enabling Ramp to scale, reach international markets, operate in highly regulated and constrained environments (e.g. FedRAMP), and deliver on enterprise-grade SLAs. - Enable AI-native engineering — as Ramp builds increasingly AI-powered products, PE is the team that makes sure the platform can support them. You'll proactively partner with product teams on AI infrastructure patterns, define the golden paths that turn one-off solutions into reusable foundations, and stay ahead of emerging challenges before they become blockers. - Build developer tooling and self-service infrastructure — so that other teams can answer their own questions (cost, performance, reliability) without involving PE. - Participate in on-call rotation — and more importantly, use every incident as a signal to eliminate the root cause, not just resolve the symptom. - Lead across the company — PE doesn't just review designs or show up when called. We proactively initiate cross-team architectural reviews, and we take full ownership of company-wide reliability and scalability initiatives: identifying the problem, proposing the solution, aligning the stakeholders, and staying in until it's done. WHAT WE LOOK FOR We don't hire for a checklist. We hire for the instincts that make someone exceptional on this team. The mindset we're looking for: - You love building teams, mentoring engineers, and helping people grow—and you are equally energized by writing code, reviewing designs, and digging into complex distributed systems. - You are a true player-coach. You know when to coach, delegate, and create space for others to lead; you also know when your direct technical involvement will create the most leverage. - You can set a technical direction, bring people along, and then lock in with the team to make it happen. - You do not believe managing engineers means stepping away from the technology or the code. - You can't walk past something broken without wanting to fix it — and you don't stop at the workaround. You find the root cause and eliminate the class of problem. - You think in systems, not tasks. You understand that "fixing the bug" is step one; making it so the bug can't happen again is the job. - You move with urgency but without chaos. You know when to go fast and when to slow down and do it right. - You treat product teams as your users. You build for them, communicate with them proactively, and measure success by how much faster they can ship. But you're also an owner — when something is broken or blocking, you don't wait to be asked. We win when our customers win. - You leave things better than you found them. Every system you touch, every process you encounter — you move it forward. Not always dramatically, but always directionally. You picked it up in a certain state; you leave it in a better one. - You are equally comfortable reading a database query plan, reviewing a system design doc, writing a Terraform module, and jumping into an incident at 2am. Experience profile: - 8+ years of software engineering experience, including a track record of shipping high-quality architectures for critical systems. - Staff+-level technical leadership: experience setting technical direction and leading complex, multi-quarter technical initiatives from ambiguous problems through durable production outcomes. - Experience managing, mentoring, and developing engineers. You create clarity, give direct feedback, and help people grow in technical judgment, scope, and leadership. - A sustained hands-on engineering track record. You are comfortable writing and reviewing production code, evaluating system designs, debugging incidents, and making difficult technical tradeoffs. - Hands-on experience building and operating distributed systems at production scale. - Strong software engineering fundamentals — you write clean, well-tested, production-ready code and set that standard for the team. - Experience with at least one major cloud provider (AWS preferred). - Familiarity with observability and reliability practices, including SLOs, error budgets, alerting, dashboards, and incident response. - Track record of delivering through cross-functional coordination: aligning stakeholders, unblocking teams, and staying accountable for the outcome. - Comfortable using AI tooling and coding agents as part of your everyday engineering workflow — and helping a team use them to move faster and think bigger. Bonus (not required): - Experience with cellular or multi-tenant architecture patterns - Prior work on workflow orchestration systems (Temporal) - Contributions to developer experience or internal platform tooling - Experience in fintech, payments, or regulated industries (FedRAMP, SOC 2) BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf. OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process. Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice
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