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Location: Tallinn, Estonia Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (Applied AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience. Opportunities to learn and grow through our “ Employee Training & Development program”. Stebby Sports Compensation or Confido Health Compensation. Multiple events to bond with the team and the group. Birthday and Loyalty benefits . What to expect from our recruitment process: Interview with HR Assessment task Interview with hiring managers Final interview with top management Make your next Career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Limassol, Cyprus Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: A Unique Opportunity for a career in a global, fast-growing company. Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance). Opportunities to learn and grow through our “ Employee Training & Development program”. Medical Insurance Cover , which includes Outpatient, Inpatient, and Dental Care. Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company. Participation in our welfare investment and savings plan through our Provident Fund Scheme. Birthday and Loyalty benefits . Collaboration with SportBenefit. What to expect from our recruitment process: First interview with hiring managers or an HR call Task Assessment Technical Interview or home assignment Final interview with top management Make your next Career step and apply NOW! * Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

Location: Barcelona, Spain; Madrid, Spain; Tenerife, Spain; Bolzano, Italy; Rome, Italy; Budapest, Hungary; Miskolc, Hungary; Petten, Netherlands; Krakow, Poland; Krosno, Poland; Lublin, Poland; Poland; Poznan, Poland; Warsaw, Poland; Bratislava, Slovakia; Bucharest, Romania; Bucuresti, Romania; Ljubljana, Slovenia; Vilnius, Lithuania; Nicosia, Cyprus; Pilsen, Czechia; Podgorica, Montenegro; Praha, Czechia; Banská Bystrica, Slovakia; Sofia, Bulgaria; Zagreb, Croatia Workplace: remote At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently looking for a dedicated Lead AI Aplication Engineer to join one of our clients' teams . If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you. Key Responsibilities: Build & Run the Shared AI Platform Architect and maintain a multi-tenant AI Platform that supports the full ML lifecycle across cloud and on-premises environments. Ensure high availability, low latency, and cost-efficiency for all shared AI resources. Implement LLMOps/MLOps best practices, including automated deployment pipelines for models. 2. Curate the AI Services Catalogue Develop and expose "as-a-service" capabilities: Inference-as-a-Service, Embeddings-as-a-Service, and RAG-as-a-Service. Standardize how squads interact with LLMs, providing unified APIs and abstraction layers to prevent vendor lock-in. 3. Manage AI Data Infrastructure Own the deployment and scaling of Vector Databases (e.g., Pinecone, Milvus, Weaviate) and Feature Stores (e.g., Feast, Tecton, Hopsworks). Optimize data retrieval patterns to support real-time AI applications and agentic workflows. Oversee Model Hosting environments, utilizing Kubernetes (K8s) and GPU orchestration to manage compute resources efficiently. 4. Enable Developer Self-Service Build and maintain a Self-Service Portal or CLI that allows product squads to provision AI environments, models, and data stores independently. Reduce "Time-to-Inference" for new features by providing pre-configured templates and blueprints. Conduct internal workshops and provide documentation to empower squads to use the platform effectively. Must-Have Technical Skills Infrastructure: Deep experience with Kubernetes (K8s), Docker, and Terraform/Pulumi. Hybrid Cloud: Proven experience managing workloads across AWS/Azure/GCP and On-Premises (NVIDIA AI Enterprise, OpenShift). AI/ML Tooling: Hands-on experience with vLLM, TGI (Text Generation Inference), or NVIDIA Triton for model serving. Databases: Expertise in Vector DBs and traditional SQL/NoSQL databases. Languages: High proficiency in Python and Go or Rust for platform tooling. Experience 8+ years in Platform Engineering, DevOps, or Site Reliability Engineering (SRE). 2+ years specifically focused on building AI/ML infrastructure or platforms. Experience building Internal Developer Platforms (IDP) is a massive plus.

Задачи: - Проектировать и согласовывать архитектуру AI-агента, приложений и интеграций. - Развивать и разрабатывать backend-компоненты AI-агента, общие библиотеки и интеграционные взаимодействия. - Реализовывать решения на базе LLM, ReAct и RAG, включая поиск и подбор релевантных «шагов» из существующей библиотеки. - Интегрировать систему с внутренними сервисами, репозиториями, базами знаний и корпоративной инфраструктурой. - Формировать требования для построения CI/CD, мониторинга, логирования, трассировки и контроля качества для AI-агента. - Проводить ревью кода, поддерживать код-стандарт и участвовать в командных коммуникациях. - Взаимодействовать с специалистами по автоматизированному тестированию, QA-инженерами и разработчиками для уточнения требований и сценариев использования. - Участвовать в разработке пользовательской поверхности решения, в формате IDE plugin. Требования: - Опыт работы от 3-4 лет в разработке. - Высшее образование. - Практический опыт построения RAG-систем и работы с векторными хранилищами, желательно PostgreSQL + pgvector. - Опыт работы с LangChain, Python. - Опыт разработки ReAct агентов. - Понимание принципов ООП, SOLID и паттернов проектирования. - Понимание базовых принципов многопоточного и асинхронного программирования, включая GIL и asyncio. - Практические знания и навыки работы с LLM. - Опыт работы с инструментами контейнеризации приложений, включая Docker. - Лидерские качества: умение принимать решения и брать на себя ответственность. Условия: - Возможность участия в интересных проектах. - Возможность профессионального и карьерного роста в компании. - Опыт работы в команде профессионалов. - Специальные тарифы для сотрудников в спортивные клубы и языковые курсы и пр. - Удаленный и гибридные форматы работы.

Требования: - Очное обучение в ВУЗе или ССУЗе по ИТ-специальности - Уверенное знание Python - Понимание ООП и базовых принципов написания чистого кода - Базовый опыт работы с FastAPI или другим backend-фреймворком - Понимание REST API - Базовое знание SQL и PostgreSQL - Понимание Git - Базовое умение работать в Linux / terminal - Знания про асинхронность / многопоточность - Интерес к работе с LLM, AI Agents, RAG и AI-native разработке - Готовность писать тесты, документацию и разбираться в чужом коде - Умение задавать вопросы, быстро и самостоятельно учиться и работать с обратной связью Условия: - Официальное трудоустройство согласно ТК РФ - Оформление по срочному трудовому договору - Современный офис в центре города: ул. Костина, 6 - Возможность выбрать гибкий график работы - Возможность профессионального роста и развития внутри Компании - Обучение в одном из лучших Корпоративных университетов и в Виртуальной школе Сбера - Гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ - ДМС для сотрудников/родственников (с первого дня трудоустройства) - Материальная помощь и социальная поддержка, корпоративная пенсионная программа - Бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров.

Задачи: - Пресейлы с потенциальными клиентами - Подготовка эстимейтов и пропоузалов на скоуп работ - Прохождение клиентских интервью для старта проектов - Ведение технической части в проектах: помощь разработчикам в построении изначального решения - Контроль выполнения работ инженерами и попадание в сроки в соответствии с эстимейтами Требования: - Опыт на позиции AI архитектора или аналогичной роли - Широкий опыт работы с клиентами (преимущественно со стартапами) - Опыт подготовки оценок для проектов, организация работы и контроль попадания в сроки - Важен бекграунд в backend разработке, знание Python на уровне senior, опыт с современными библиотеками и фреймворками (особенно FastAPI), опыт проведения код-ревью - Коммерческий опыт с GenAI, интеграции AI решений в приложения (LLM, RAG, ИИ-агенты и др.) - Знание популярных инструментов для интеграции AI/LLM в приложение (например, Hugging Face Transformers, LangChain, OpenAI Python SDK, PydanticAI, LlamaIndex, Microsoft AutoGen, Ollama и др.) - Знание и опыт с CI/CD, DevOps, MLOps - Если есть экспертиза в конкретном домене в AI (Healthcare, Video, etc.), будет огромным плюсом - Разговорный английский язык на уровне не ниже B2 (Upper-Intermediate) - Локация кандидата должна быть вне РФ и вне РБ Условия: - Удалённый формат работы - Гибкий рабочий график, фулл-тайм - Задачи на стыке бизнеса и современных AI-технологий - Возможность получить широкую экспертизу в разнообразных доменах бизнеса - Влияние на развитие продуктов и на технические решения - Заключаем договор формата b2b (с ИП, валютный расчётный счёт)

Задачи: - Пресейлы с потенциальными клиентами - Подготовка эстимейтов и пропоузалов на скоуп работ - Прохождение клиентских интервью для старта проектов - Ведение технической части в проектах: помощь разработчикам в построении изначального решения - Контроль выполнения работ инженерами и попадание в сроки в соответствии с эстимейтами Требования: - Опыт на позиции AI архитектора или аналогичной роли - Широкий опыт работы с клиентами (преимущественно со стартапами) - Опыт подготовки оценок для проектов, организация работы и контроль попадания в сроки - Важен бекграунд в backend разработке, знание Python на уровне senior, опыт с современными библиотеками и фреймворками (особенно FastAPI), опыт проведения код-ревью - Коммерческий опыт с GenAI, интеграции AI решений в приложения (LLM, RAG, ИИ-агенты и др.) - Знание популярных инструментов для интеграции AI/LLM в приложение (например, Hugging Face Transformers, LangChain, OpenAI Python SDK, PydanticAI, LlamaIndex, Microsoft AutoGen, Ollama и др.) - Знание и опыт с CI/CD, DevOps, MLOps - Если есть экспертиза в конкретном домене в AI (Healthcare, Video, etc.), будет огромным плюсом - Разговорный английский язык на уровне не ниже B2 (Upper-Intermediate) - Ваша локация должна быть вне РФ, вне РБ Условия: - Удалённый формат работы - Гибкий рабочий график, фулл-тайм - Задачи на стыке бизнеса и современных AI-технологий - Возможность получить широкую экспертизу в разнообразных доменах бизнеса - Влияние на развитие продуктов и на технические решения - Дружную команду экспертов, обмен знаниями и тех.рост - Заключаем договор формата b2b (с ИП, валютный расчётный счёт)

Задачи: - Интегрировать LLM в продукты и сервисы (API, backend, пайплайны обработки данных); - Разрабатывать и оптимизировать prompt’ы, CoT, системные инструкции; - Оценивать качество ответов (метрики + human eval); - Настраивать guardrails: безопасность, фильтрация, соответствие требованиям; - Строить RAG-системы: индексация данных; работа с векторными БД; оптимизация поиска и генерации; - Оптимизировать инференс (стоимость, latency, batching, caching, квантизация); - Участвовать в архитектурных решениях вместе с продуктовой и ML-командой; - Исследовать и внедрять новые подходы и модели; - При необходимости: работать с мультимодальными моделями (текст, изображения, документы). Требования: - Уверенный Python; - Опыт работы с LLM в проде (не только pet-проекты); - Понимание prompt engineering, RAG-подходов, оценки качества моделей; - Опыт деплоя ML/LLM решений (Docker, Kubernetes, cloud); - Работа с векторными базами данных. Будет плюсом: - Fine-tuning / PEFT (LoRA, adapters); - RLHF или synthetic data generation; - Опыт с LangChain, LlamaIndex, Hugging Face; - Оптимизация инференса (vLLM, TensorRT, ONNX); - Опыт с мультимодальными моделями; - Публикации / open-source / pet-проекты; - Участие в хакатонах; - Понимание продуктовых метрик. Условия: - Полная удалёнка; - Аккредитованная ИТ-компания; - Интересный продукт, современный стек, микросервисная архитектура; - Известные клиенты из ТОП-10 в своих сегментах; - Прокачка скиллов под руководством лидов с 8+ лет опыта; - Достойный оклад по итогам собеседования + ежеквартальный сбор ОС с премированием лучших сотрудников; - Возможность взять на себя дополнительные задачи за соответствующее вознаграждение; - Премии за менторство младших сотрудников; - Ежеквартальные бонусы и подарки лучшим сотрудникам; - Пригласите друга и получите щедрое вознаграждение за рекомендацию.

Location: Hybrid (Berlin, Germany). Must be based in or be able to relocate to Berlin, Germany (attendance at the Berlin campus 2 days a week). Company: A pioneering local delivery platform operating in over 70 countries, focusing on efficient, affordable, and sustainable last-mile delivery. What you will do: — Build and scale AI agents capable of reasoning, tool calling, and interacting with internal services and data systems. — Develop and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic retrieval systems. — Design and implement evaluation frameworks and safety guardrails for agent behavior and model performance. — Implement observability, monitoring, and cost visibility for LLM and agent workloads. — Collaborate with data scientists and platform engineers to integrate AI systems with the broader ML ecosystem. — Optimize systems for performance, reliability, and cost efficiency while operating AI workloads at scale. Requirements: — Proven experience shipping LLM-powered systems or AI agents into production. — 4+ years of experience in production machine learning infrastructure, specifically involving LLMs. — Strong programming skills in Python with experience building scalable backend services. — Experience with Cloud platforms, ideally AWS or GCP. — Strong communication skills and ability to work collaboratively in cross-functional teams. Nice to have: — Experience with Kubernetes, Terraform, Kafka, MLflow, or Kubeflow. — Experience with LLM application frameworks such as LangChain, LangGraph, or LlamaIndex. — Experience with ML frameworks such as Hugging Face or PyTorch. Culture & Benefits: — Hybrid working model with 2 days a week in the Berlin campus. — 27 days of holiday, increasing with years of service. — €1,000 Educational Budget, language courses, and access to Udemy Business. — Health checkups, meditation, and gym/bicycle subsidies. — Employee Share Purchase Plan, corporate pension plan, and life/accident insurance. — Relocation support and dedicated relocation hub for moving to Berlin.

Location: Singapore Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences - Proficiency in Mandarin is required to support interactions with Mandarin speaking clients. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.

Задачи: — создание цифровых помощников для управления рисками инвестиционных портфелей в мультиагентной системе, анализирующей отчетность эмитентов, новостную повестку, судебные производства, котировки, кредитные рейтинги. Требования: — глубокое понимание архитектуры и принципов работы больших языковых моделей (LLM); — опыт разработки и интеграции AI-агентов и multi-agent систем; — понимание методов и алгоритмов машинного обучения и обработки естественного языка (NLP); — опыт с RAG (retrieval-augmented generation) и Knowledge Graph; — навыки prompt engineering; — опыт с инструментами и фреймворками: LangChain, GigaChain, LangGraph, LangFlow, n8n, Flowise, OpenRouter, NeuroAPI, GigaChat, ChatGPT, DeepSeek, Qwen, Mistral; — программирование на Python (приоритет); Java/Go/JavaScript — будет плюсом; — разработка и интеграция backend-сервисов и WebUI для AI-решений; — протоколы обмена данными: REST, WebSocket, JSON-RPC, gRPC; — системы логирования, мониторинга и диагностики для AI-приложений; — базовые DevOps и CI/CD практики; — опыт реализации и сопровождения AI-агентов в production-средах; — разработка приложений на базе LLM с использованием популярных open-source и коммерческих моделей; — интеграция внешних данных (базы знаний, API) для расширения возможностей AI-агентов; — построение кастомных пайплайнов обработки запросов и ответов; — участие в проектах по оптимизации производительности и масштабируемости LLM-систем; — командная разработка и взаимодействие с продуктовой и DevOps-командами. Условия: — удаленная работа; — полная занятость; — грейд middle+/senior; — зарплата от 260 000 до 350 000 ₽ в месяц.

Location: Distributed About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations Switzerland Responsibilities The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey. Technical Validation: Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. . Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals. Customer Adoption & Value Realization: Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices.  Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk. Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes. AI Orchestration & Workflow Automation: Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory. Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization. This role may require travel up to 20–50% to attend customer meetings, conferences, industry events, and in-person team collaboration. Desirable Skills, Knowledge, and Experience Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services,  Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly. Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives. Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles. Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below: Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS. Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts. Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3. AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows. Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments. Business Fluency in German Bonus Points Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms. Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls. Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2. Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth. Compensation This role features a competitive base salary and a variable compensation structure tied directly to the successful execution of full-lifecycle commercial targets, including new business acquisition, ongoing adoption milestones, and overall account expansion. What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: Remote Workplace: remote About Distru Distru is the #1 ERP in the cannabis industry with $15B in sales processed through our platform. We've built a battle-tested ERP and B2B eCommerce platform that powers inventory, manufacturing, sales, and logistics, and we're now building AI infrastructure on top of it to give commercial businesses their all-in-one AI stack. We're growing and profitable, with 5/5 stars on Glassdoor. Our investors include Felicis Ventures, Global Founders Capital, Poseidon Asset Management, and Village Global, who have funded companies such as Shopify, Cruise, HelloFresh, Facebook, Slack, and Opendoor. Get to know the team, our culture and our full benefits at distru.com/careers! The Role AI assistants like Claude and ChatGPT are seeing record adoption at work, and they're only as useful as the data they can reach. For our customers, that data lives in Distru. We believe the system of record has never been more valuable, so we're building Distru headless-first: unified access to ERP data, deep MCP and AI assistant integrations, agents embedded in Distru, and a seamless experience between the ERP and the AI tools our customers already use. You'll own and evolve Distru's AI product suite, including: MCP: connect AI assistants like Claude and ChatGPT directly to Distru data Agent Builder: build agents that run inside Distru, with workflow support for multi-step processes Unified Data Engine: unify ERP and business data into one layer that AI can query and act on And more… We're in the early stages, so you'll define the product from the ground up and make strong, opinionated calls on what we build and where it goes next. The AI space moves fast and the specifics will change, so this vision is something you'll mold. You'll report to the executive team and work closely with engineering, design, GTM, and customer success. What you'll do Product execution Gather customer feedback directly and through CS and sales, then deconstruct it into system-level AI features that benefit the wider user base and scale with future additions Prioritize the roadmap and timeline around the work with the most revenue impact Write PRDs with thoughtful UX designs, ready for the engineering team to execute on Product ownership Own features from inception to release, iteration, and continued maintenance Define and measure the success of every feature you're responsible for. You are the CEO of every feature you touch. Own the knowledge base, MCP docs, and go-to-market content for your features, and enable marketing and sales on everything you ship Cross-functional leadership Work closely with engineering, GTM, sales, and CS. You're the bridge that pulls insights from every department together and keeps the product moving. What success looks like at 6 months You've shipped at least one AI-native feature to production with measurable user adoption The product team and engineers trust you to write well-thought-through PRDs You own a part of the Distru product and are the go-to person for it across the company What we look for AI fluency For every AI role, we look for three things: Tool fluency: your setup is AI-forward and you have opinions on which tools to use (and not use). You go beyond prompting ChatGPT or Claude and have built your own skills, agents, or workflows. Workflow fluency: you can break a PM process into human steps, AI steps, and hybrid steps, and explain what you chose to automate, what you kept human, and why. Build fluency: you've shipped AI features that hold up in the real world, with nuanced workflows, different user personas, and users who aren't AI fluent. You know when AI feels natural versus forced, and you can defend the calls you made. You use AI tools daily and can tell us specifically where your fluency is strong and where you're still building it. Must have 3+ years in product management Product ownership: you've owned at least one significant AI feature or product end to end, from an ambiguous problem statement through launch and iteration, with measurable outcomes UX proficiency: you've created intuitive products that abstract away complexity for the user, without the need for a designer Technical fluency: you're comfortable with engineering concepts such as SQL, telemetry, agentic harnesses, subagents, and RAG Clear communication: you convey your thinking briefly and clearly Tooling: experience with product management tooling (Notion, Miro, Claude, Hotjar, LangSmith, etc.) Strong signal Background in supply chain, ERP, CRM, B2B marketplaces, or accounting Experience using Claude Code (or similar coding tools) to build products on your own Familiarity with agentic systems and multi-agent orchestration Experience in early-stage startups (0–50 headcount) How we work We love building with AI. Trying new models the week they drop, building agents for fun, and forming strong opinions on what works. We invest in it with company-wide AI growth with classes and workshops, AI demo days, AI hackathons, and access to best-in-class models and tools. We ship fast. We expect PMs to be comfortable with the pace of a startup. We care about edge cases and details. Our customers' SOPs are nuanced, and details matter when you're handling their inventory and finances. You'll build on what we've learned. You'll have access to the team's combined AI knowledge and the processes and skills we've built. For the full picture of our culture and who thrives here, see distru.com/careers . Benefits Our careers page is the best way to get to know us: the full benefits, our yearly offsites, who thrives here, and what the team says about working at Distru. Here are a few highlights (exact benefits vary by country and employment type): Fully remote across 4 continents Employee-friendly option terms: after 2 years, a 10-year window to exercise if you leave 18 days PTO + 11 holidays (sick days don't count toward PTO) Medical, dental, vision + 401(k) for US employees The best AI tools available and a generous AI stipend for everything else Yearly in-person team offsites Interview process Intro call (30 min): your background, what you've owned, and the most challenging AI product you've worked on Product experience (45 min): a deep dive into a complex product you've owned and a PRD you're proud of AI fluency (30 min): a screen-share show and tell of something you've recently built with AI, and a look at your AI workflow Product exercise (take-home, 2–4 hours over 2–3 days): turn a set of user requests into a single PRD, working with the team in a shared Slack channel Exercise review (60 min): walk the team through your decisions, trade-offs, and what comes after the PRD References and offer   Distru was formed by an environment of mutual respect and trust made up by people working together without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by law. We believe that diversity and inclusion among our team members is critical to our success and we proactively strive to recruit, develop and retain the best and brightest people from the most diverse candidate pools we can find all over the world.   #LI-RC1 Where you land in the range depends on your experience and skills.

Location: Toronto, Ontario, Canada Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE ROLE At Sentry, Support is an engineering discipline. Our customers are the greatest technical minds in the world—developers at elite enterprises building the future of software—and they deserve answers that go deeper than a knowledge base link. We are architecting the Technical Support engine. We’re looking for a veteran engineer to help us redefine the standard of technical support by combining deep human expertise with autonomous agentic systems. You are a debugger of both code and systems. You will treat support volume as a data signal to build automated resolution paths, ensuring our human engineers only touch the most complex, high-impact architectural puzzles. Sentry Support Engineers aren't just clearing queues; they are Orchestrators. You will engage with our users across GitHub, Discord, and our internal systems, while acting as the Technical Lead for our Agentic Ops. You ensure that when a developer asks a complex question, our systems have the right context and a seamless "Human-in-the-Loop" path to you when deep, nuanced expertise is required. IN THIS ROLE YOU WILL Master the Sentry Ecosystem & Support Elite Developers - Deep-Dive Debugging: Perform root-cause analysis on complex issues and distributed tracing gaps across polyglot environments. - Support the Great Minds: Act as a strategic consultant for senior engineers at our largest enterprise customers, solving high-stakes architectural challenges that push the boundaries of observability. - Troubleshoot SDK Implementations: Go deep into the source code of Sentry’s SDKs to help developers instrument complex frameworks and custom environments. - Engineering Feedback Loop: Serve as the bridge between the world's best developers and our product teams, using data from your systems to prioritize high-impact platform fixes. Engineer Agentic Operations (The Scaling Engine) - Deterministic Support Paths: Engineer the logic that powers our support agents, moving beyond probabilistic guesses to high-fidelity, autonomous resolutions. - Knowledge Engineering: Build the right context into our systems so they can resolve issues consistently and indefinitely. - Agentic Tooling Development: Use MCP (Model Context Protocol) and Sentry’s internal APIs to build "skills" for our agents, allowing them to perform complex lookups or state-checks autonomously. - The Seer Philosophy: We’ve already proven AI can handle autonomous production fixes with Seer. You will apply that same philosophy to the support lifecycle—moving us from a "Help Desk" to an "Autonomous Resolution Engine." YOU’LL LOVE THIS JOB IF - You love eliminating Non-scalable effort: you enjoy automating repetitive work and take pride in building systems that save time and effort. - You’re a Full-Stack Troubleshooter: You enjoy jumping from a React frontend issue to a Python backend trace to a CI/CD pipeline failure in a single afternoon - You Value Evidence-Based Support: You prefer looking at data trends over anecdotal evidence to decide where to build automation next. - You’re a Developer Advocate: You want to guide the industry on how elite engineers and AI co-exist in a high-density technical ecosystem. QUALIFICATIONS - 4+ years of experience in technical support engineering, systems engineering, or software development, with a track record of solving high-complexity SaaS problems. - Strong Coding Foundations: Mastery of Python, JavaScript, Java, or Ruby. You are comfortable reading SDK source code and identifying bugs in production-level repositories. - Systems Depth: Deep understanding of distributed systems, microservices, APIs, and the "path of a pixel" from frontend to database. - AI & Automation Literacy: Practical familiarity with LLM orchestration (RAG, context windows, system prompts) and a critical eye for where AI succeeds versus where it requires human intervention. - Exceptional Communication: The ability to explain complex architectural concepts to a human and write precise "system instructions" for an AI. BONUS QUALIFICATIONS - Open Source Contributor: An active presence on GitHub or experience maintaining open-source libraries. - Former Software Developer: You’ve spent time in the trenches as a full-time dev and know exactly what keeps our customers up at night. The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $100,000 to $125,000 CAD. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs. EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.

Location: London Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. WHAT YOU'LL DO As an Agent Strategist https://sierra.ai/blog/agent-strategist-your-phd-in-applied-ai, you own how Sierra's AI agents come to life for our customers — from first pilot to a production agent handling thousands of conversations a day. You sit at the intersection of product, building agents and customer-facing work, and stay just as close to the technology as you are to the people you build for. You transform a customer's thorniest, highest-stakes problems into agents that measurably move their business. - Own the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle. Take agents from initial scope through conversation design, tooling, and evaluation, to launch and continuous iteration in production — translating business goals into an agent that outperforms, and tuning relentlessly until it's the best version of itself in the real world. You'll have real ownership and autonomy over the outcome. - Be the trusted strategic advisor to enterprise leaders. Sit shoulder-to-shoulder with our customers' executives, understand what success actually means to their business, and shape the AI strategy that gets them there. - Partner with the customer's working teams day to day. Run working sessions, troubleshoot the agent as issues come up, and make the calls that keep the build on track for launch. - Directly impact product. Surface unmet needs from your customer work, and feed them back to research and platform to shape where Sierra goes next. EXAMPLE PROJECTS These are the kinds of projects that strategists on our team have worked on recently: - Scope and launch a subscription-retention agent for a large telecommunications or media company that consistently outperforms human agents at saving at-risk customers. - Stand up an agent for a commerce customer that troubleshoots a broken device end-to-end and personalizes product recommendations in the same conversation. - Redesign the conversation flows for a financial services agent so it can handle complex, regulated interactions — and convert a pilot into a multi-team production deployment. See our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services for examples. - Partner with product on a net-new capability — a new agent architecture or self-service tooling — using a live customer as the design partner. - Define the evaluation and quality bar for a new agent, then use those metrics to drive a measurable lift in outcome https://sierra.ai/blog/outcome-based-pricing-for-ai-agents week over week. WHAT YOU'LL BRING - Customer obsession. Genuine energy being in front of customers — understanding their business and needs, thriving in complex organizations, and building trusted relationships. - Communication. Clear, direct, and persuasive across technical and non-technical audiences. - Strategic problem-solving in ambiguity. Strong analytical and critical-thinking skills to break down complex problems, spot risks early, and adapt as things change fast. - Technical aptitude. Comfortable engaging directly with technical concepts - reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in a design discussion. - Ownership and delivery. A track record of running multiple complex, high-visibility projects at once and driving them to outcomes. EVEN BETTER... - Experience building or deploying AI/LLM agents in production — hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) — working closely with technical counterparts. - You've been a founder, founding team member, or operator — you know how to balance craft, ownership, and speed. - A degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience — and/or an MBA or comparable experience at the intersection of technology and business. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.

Location: London Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in London, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn - Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations - Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services! - Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development - Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments - A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship - Comfort working directly with customers to understand their needs and solve real-world problems - Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.

Location: CH - Zurich, Switzerland The Security Team of Scopely Explore (formerly known as Niantic) seeks a Senior Security Engineer to improve the security posture of our software development lifecycle, applications, and build infrastructure. Scopely Explore, known for global hits like Pokémon GO, Monster Hunter Now, and Pikmin Bloom is now part of Scopely, home to games like Monopoly GO!, Stumble Guys, and Star Trek Fleet Command. Together, we engage billions of players worldwide, and we need your expertise to keep them safe! Do you want to help secure one of the most widely used gaming platforms on the planet? We seek creative and dedicated engineers with excellent technical judgment, strong interpersonal skills, and an eagerness to embrace new technologies. What You’ll Do Implement and maintain agentic or AI-enabled workflows to speed-up common security tasks. Perform security reviews and audits of platform and application software throughout design and launch. Provide guidance and expertise to product and operations teams across Scopely. Design, build and maintain automation and tooling that amplify the Security Team’s impact and improve the developer experience. Drive initiatives in security architecture, application scanning, fuzzing, and other proactive defenses. Contribute to hardening efforts across in-house libraries, CI/CD systems, and cloud/container environments. Be responsible for third-party library reviews and manage vulnerability remediation. Educate engineers on secure coding practices and help standardize security across teams. Engage in red-team exercises and coordinate with internal teams and external pentesting partners. Qualifications Bachelors in Computer Science or related field 5+ years of experience in a global company with cloud-centric infrastructure (preferably GCP). You have implemented services and applications with the help of AI tools like Claude, Codex, OpenCode or Gemini and are adept in the use of these tools and adjacent technologies (RAG, MCP, etc). You are capable of creating automation, agentic workflows and tooling to reliably solve problems that scale to the whole enterprise. You have in-depth experience in hardening distributed web services, cloud services and platform architectures. You can demonstrate strong programming skills (preferably Go or Java) and a deep understanding of common vulnerability classes and exploitation patterns across modern stacks. Excellent communication skills and experience collaborating across distributed teams. Bonus Points... Have participated in red-team operations or managed mitigation tracking. Possess deep familiarity with build systems, artifact repositories, or large-scale infrastructure. Have delivered privacy-focused solutions for user-facing services. Have experience in code quality management or security champion programs. Have worked in a customer-centric engineering culture and value pragmatic, scalable solutions. Can demonstrate hands-on experience or research in the area of AI security and safety. About Scopely Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play. Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come. Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play. Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit: https://www.scopely.com/ . Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official website and verify that all Talent Partner communications come from an email address ending in @ scopely.com . Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice . Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Location: Ukraine Workplace: remote Creatio is an AI CRM and workflow platform where people and AI agents work together — with no limits on users, agents, or scale. We help midsize and large organizations run customer workflows in the AI era. With a global team and a large ecosystem of partners, Creatio serves thousands of customers in over 100 countries and automates tens of millions of workflows daily. Genuine care for our clients and partners is at the heart of our DNA. We’re proud to be recognized by top industry analysts as a Leader and Strong Performer in multiple Gartner and Forrester reports.   In 2025, Creatio was named to Inc.’s Best Workplaces list, recognizing our commitment to employee wellbeing and a strong workplace culture. Who We’re Looking For: We are looking for an AI Software Engineer to design, build, evaluate, and operate AI-powered capabilities within the Creatio platform. This is an AI-first engineering role: you will spend most of your time designing agents, engineering prompts and context, building retrieval and evaluation pipelines, and directing AI coding agents - with solid .NET engineering as the foundation rather than the whole job. You will join the AI teams building the agent platform that enables AI agents to safely perform real work in the product: call tools and APIs, read and write data, maintain context and memory, follow permissions, and escalate to humans when needed. The team also owns the core infrastructure for evaluation, monitoring, logging, observability, and cost/performance control, ensuring AI agents are reliable, scalable, secure, and production-ready. This role combines strong software engineering expertise with hands-on AI engineering experience. You will work on enterprise-grade AI solutions, including assistants, copilots, knowledge systems, semantic search, RAG-based capabilities, and agentic workflows - and you will use AI coding agents as your primary daily development workflow. Responsibilities: Design and implement AI-powered product features within the Creatio platform: assistants, copilots, agentic workflows, knowledge systems, RAG, and semantic search. Design agent architectures - tools, memory and context strategy, orchestration, permissions, guardrails, and human-in-the-loop escalation - and choose the right pattern for each problem (single LLM call vs. tool-using agent vs. multi-agent). Engineer prompts, system instructions, and agent context as first-class artifacts: versioned, reviewed, and covered by evaluations. Integrate LLM providers, MCP servers and tools, enterprise data sources, embedding pipelines, and vector/hybrid search into the platform. Build evaluation datasets, offline and online evals, quality gates, and observability (tracing, logging, drift detection) for AI capabilities. Monitor and improve the quality, latency, cost, reliability, and security of AI capabilities in production, including prompt and model updates. Identify and mitigate AI-specific risks: prompt injection, data exfiltration through tools, hallucinations, over-permissioned agents, and sensitive-data leakage. Develop and maintain backend services using C# and .NET. Use AI coding assistants and engineering agents as the default development workflow; critically review and verify agent output; contribute reusable rules, skills, and prompts to the team. Follow the AI landscape closely and bring new models, tools, and patterns to the team. Requirements: Must have: Hands-on experience shipping LLM-based features to production: prompt engineering, function/tool calling, structured outputs, context-window and cost management. Practical understanding of agent architectures (tool loops, planner/executor, multi-agent, human-in-the-loop), MCP, and at least one agent framework or SDK. Working knowledge of RAG: chunking, embeddings, vector and hybrid search, re-ranking, grounding and citations, and common failure modes. Experience with AI evaluation (datasets, offline evals, LLM-as-judge), LLM observability and tracing, and AI security (prompt injection, OWASP Top 10 for LLM Applications, Responsible AI practices). Daily proficiency with AI coding agents: the ability to direct, review, and verify agent output rather than only write code by hand. Solid experience with C# and .NET, API design, distributed systems, and software architecture. Experience with SQL databases, automated testing, CI/CD, and cloud-native development; Docker and basic Kubernetes. Strong knowledge of engineering best practices and production-grade software development. Nice to have: Python for prototyping, data work, and evaluation scripting. Hands-on experience with a major AI platform (Anthropic API, Azure OpenAI, AWS Bedrock, Google Vertex AI). Experience building agent-facing tools or MCP servers. LLMOps practices: prompt and model versioning, evaluation gates in CI/CD, canary rollouts of prompt changes. Fine-tuning, distillation, or adapter-based model customization. Experience with Creatio or other low-code CRM platforms. What to expect from us: Growth & Development: Clear career paths, mentorship opportunities, and access to continuous learning to help you reach your full potential. Flexibility & Well-Being: We provide flexible work arrangements and initiatives that empower you to manage your schedule effectively, stay productive, and thrive both personally and professionally. Recognition & Impact: A culture that celebrates achievements, values your ideas, and empowers you to make real contributions from day one. Innovative Culture: Be part of a company that embraces new ideas, modern technologies, and bold thinking to stay ahead of the curve. Benefits & Rewards Package: We provide competitive compensation and benefits designed to support you and your family. Our rewards approach goes beyond salary, recognizing your contributions and commitment. The exact package may vary depending on your country of residence and employment type.