Вакансии

Location: Hybrid 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 Location: Kuala Lumpur, Malaysia What you will do as a Customer Engineer 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. Key Responsibilities 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. Minimum Qualifications Language: Mandarin is required to deal with customers in the Greater China region, Cantonese is a plus 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. Strongly Preferred Qualifications (The "Good-to-Haves") 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. Education Undergraduate or graduate degree in Computer Science, Engineering, or a related field. Travel This role may require travel up to 20–50% to attend customer meetings, conferences, industry events, and in-person team collaboration. 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: Athens, Greece We currently have a vacancy for an AI Architect , to be involved in a very important international project offering rapid career evolution. The candidate will join a software development team that uses cutting-edge technology to implement challenging IT software projects for major international public organisations. The candidate will receive adequate training and support to develop their career expectations. What You'll Do: Own the end-to-end technical architecture of GenAI and LLM solutions across multiple enterprise engagements; Translate business and functional requirements into secure, scalable, production-ready AI architecture blueprints; Design advanced GenAI pipelines including RAG architectures, orchestration layers, evaluation frameworks, and model deployment strategies; Drive AI governance, observability, monitoring, and responsible AI practices, ensuring architectural integrity across complex client environments. Requirements Must-Have Qualifications: 3+ years of experience in AI/ML engineering or solution architecture, with a proven track record of enterprise-grade AI delivery from concept to production; Strong hands-on experience architecting GenAI solutions: prompt engineering strategies, RAG architectures, LLM evaluation frameworks, and production deployment patterns; Deep understanding of distributed systems, APIs, microservices, data architectures, and cloud-native design principles; Proven experience designing scalable AI solutions on AWS and/or Azure, including MLOps and CI/CD practices; Demonstrated ability to translate complex business requirements into clear technical blueprints and solution architectures; Fluent in spoken and written English. Nice-to-Have Qualifications: Experience in consulting, systems integration, or public-sector IT environments; Hands-on experience with AIOps practices, LLM monitoring frameworks, and AI governance models; Knowledge of frameworks such as LlamaIndex, LangGraph, and AI evaluation toolkits, and experience with multi-model strategies (open-source and commercial LLMs). Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( AIA/11/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1100 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published at www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

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 - 5–8+ 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 $125,000 to $150,000. 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/.

Задачи: — Проектировать, разрабатывать и внедрять LLM/AI агентов и AI-ассистированные инструменты для процессов команды информационной безопасности (анализ инцидентов, threat intelligence, vulnerability management, автоматизация рутинных операционных задач и др.). — Выстраивать новые рабочие процессы команды на базе AI-решений — от пилотов и MVP до продуктивной эксплуатации. — Оценивать применимость LLM/AI инструментов и агентных архитектур к задачам информационной безопасности, формировать обоснованные рекомендации по внедрению. — Разрабатывать автоматизацию с использованием языков программирования для интеграции AI-решений с существующей инфраструктурой и инструментами (SIEM, тикет-системы, EDR и др.). — Учитывать и минимизировать риски безопасности, связанные с использованием LLM/AI (утечки данных, prompt injection, неконтролируемый доступ агентов к системам и др.). — Документировать архитектуру, процессы и практики использования AI-инструментов, обучать команду работе с ними. — Участвовать (около 20% времени) в проектах Infrasec Core Team по повышению защищённости сетевой и серверной инфраструктуры. — Работать в тесном контакте с командами CSIRT, VM, Endpoint/Server Security и Network Security для выявления точек, где AI-агенты дадут наибольший эффект. Требования: — Опыт работы в информационной безопасности или смежной инженерной области от 4+ лет. — Сильные навыки программирования и автоматизации (Python или Go предпочтителен). — Самостоятельное написание production-ready кода, а не только прототипов. — Практический опыт работы с LLM/AI: использование API моделей, построение агентных пайплайнов, работа с RAG, промпт-инжиниринг, понимание ограничений и рисков. — Понимание применения LLM/AI именно в контексте информационной безопасности. — Опыт проектирования архитектуры (для новых процессов/сервисов), умение самостоятельно принимать и обосновывать технические решения. — Базовое инженерное понимание операционных систем (Windows/Linux), сетевой инфраструктуры и типовых механизмов защиты — достаточное, чтобы проектировать AI-решения для реальных задач информационной безопасности. — Понимание принципов кибербезопасности, векторов атак. — Способность работать на стыке нескольких команд, выступать драйвером изменений и обучать коллег новым инструментам. — Инициативность, самостоятельность и готовность строить процессы «с нуля» в быстро меняющейся области. Условия: — Формат работы на выбор: гибрид, удалёнка, офисы в Москве, Санкт-Петербурге, Иннополисе, Новосибирске и ещё более чем в 8 городах России, а также в Казахстане и Беларуси. — Участие в конференциях, митапах, техтолках, хакатонах и конкурсах. — Билеты, дорога и проживание за счёт компании. — ДМС со стоматологией и льготная медицинская страховка для близких, страхование от несчастных случаев, полис выезжающего за рубеж, онлайн-поддержка психолога. — Курсы по запросу и поддержка в карьерном развитии. — Бесплатные курсы программирования, математики и английского языка для детей сотрудников. — Партнёрские скидочные программы, спортивные клубы, йога в офисе. — Оплачиваемая стажировка Route Start для начинающих специалистов. — Зарплатные проекты от Ozon Банка и других банков. — Льготная жилищная программа для сотрудников. — Реферальный бонус за рекомендацию друга.

Задачи: — самостоятельно находить клиентов на разработку и IT-консалтинг; — находить потенциального клиента и помогать довести его до конкретного запроса; — передавать техническую часть автору услуг, который общается с клиентом, оценивает задачу, предлагает решение и стоимость, выполняет работу и отвечает за результат. Требования: — умение находить клиентов и продавать услуги; — опыт в B2B-продажах, IT-продажах, лидогенерации, работе с предпринимателями и компаниями, продаже разработки и digital-услуг; — желательно иметь собственную клиентскую базу или опыт продаж IT-услуг. Условия: — формат работы полностью удалённый; — фиксированной оплаты нет, оплата только в виде 20% от фактически оплаченных заказов; — комиссия выплачивается после получения оплаты от клиента; — повторные заказы от привлечённого клиента также учитываются в партнёрской модели (условия обсуждаются отдельно); — не требуется разбираться в Python или архитектуре, главное — находить бизнес-задачи и заинтересованных клиентов; — предоставляется сайт с описанием услуг, информация о техническом опыте, возможность быстро получить техническую оценку проекта, помощь с подготовкой предложения клиенту и возможность подключить технического специалиста к разговору. Примеры услуг: — разработка backend на Python с использованием FastAPI и Django; — разработка API и интеграций; — автоматизация бизнес-процессов; — создание Telegram-ботов и веб-приложений; — доработка существующих проектов; — микросервисная архитектура; — базы данных и backend-инфраструктура; — интеграция AI/LLM в существующие продукты, включая RAG и AI-агентов; — технический аудит и консультации. Где искать клиентов: — биржи фриланса (например, FL.ru), Avito, Telegram, профильные и предпринимательские сообщества, прямой поиск компаний, партнёрства с агентствами и другими специалистами, собственная база контактов. Пример расчёта комиссии: — заказ 50 000 ₽ → комиссия 10 000 ₽; — заказ 100 000 ₽ → комиссия 20 000 ₽; — заказ 200 000 ₽ → комиссия 40 000 ₽; — заказ 500 000 ₽ → комиссия 100 000 ₽.

Задачи: — Разработка и развитие production LLM/AI-систем и AI-агентов. — Построение многошаговых agentic workflows: routing, tool calling, state management. — Работа с prompt- и context-engineering, управление памятью и состоянием диалога. — Реализация structured output и function/tool calling. — Создание RAG-пайплайнов: chunking, embeddings, retrieval, reranking. — Интеграция LLM с API, базами данных и внутренними сервисами. — Разработка backend на Go и AI-компонентов на Python. Требования: — Умение собирать LLM-систему целиком — от prompt/context logic и агентов до backend, интеграций и запуска в production. — Основной стек — Go для production-backend и высоконагруженной логики, Python для AI-инфраструктуры и прототипирования. — Опыт построения agentic workflows, управления состоянием диалога и памяти. — Понимание RAG, embeddings, retrieval и reranking. — Навыки тестирования и оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge. — Умение выбирать модели с учётом качества, latency и стоимости. — Анализ логов и трасс для повышения стабильности.

Требования: — Отличные знания и опыт разработки на Python — Хорошие знания и практический опыт с одним из фреймворков (FastAPI / Django / Flask) — Умение эффективно работать с AI-инструментами (Claude Code / Cursor / Codex / OpenCode): формулировать чёткие задачи, итеративно уточнять промпты и проверять результат — Понимание принципов построения RAG-систем: chunking, embedding, retrieval, ранжирование результатов — Опыт работы с LLM API — Понимание принципов разработки, алгоритмов и структур данных Будет плюсом: — Опыт построения или поддержки ETL-пайплайнов — Опыт с AWS (S3, Lambda, S3Vectors)

Location: Hybrid 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 Location:  Austin, Dallas or Houston TX Senior Customer Engineer SLED *This is a work-from-home 100% remote role, but you should reside in Texas." What you’ll do as a Senior Customer Engineer SLED About the Role At Cloudflare , we are on a mission to help build a better Internet. As the architectural complexity of enterprise solutions scales, we are evolving how we partner with our customers. The Customer Engineer (CE) represents the core driver of our technical go-to-market strategy: a trusted advisor who owns the technical relationship from the initial discovery phase through to long-term adoption and ongoing account expansion. Sitting within the GTM organization and reporting to the Regional Customer Engineering Leader, this specialized role will focus heavily on our SLED (State, Local, and Education) and Local Government sectors. You will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, utilizing AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire public sector customer journey. Key Responsibilities Technical Validation : Partner closely with Account Executives to lead technical discovery, build bespoke architectures, and deliver compelling product demonstrations and Proof of Concepts (PoCs) across Cloudflare’s portfolio (Security, Networking, and Developer Platforms) tailored to public sector procurement and compliance standards . Customer Adoption & Value Realization : Lead and/or provide oversight to technical onboarding and implementation, serving as the primary executive and engineering contact for the customer. You will partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. You will proactively monitor dynamic customer health scores and telemetry to ensure rapid time-to-value and resolve integration bottlenecks common in municipal and educational IT infrastructures . Commercial Accountability & Expansion : Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. You will 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. AI Orchestration & Workflow Automation : Act as an "AI-Augmented" engineer. Leverage AI agents and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, and basic telemetry monitoring, reclaiming your time for strategic customer advisory. Minimum Qualifications Public Sector Expertise : Proven experience working with or selling into SLED, Local Government, State or Municipal agencies , with a deep understanding of public sector buying cycles, compliance requirements, and unique government IT constraints. Experience : Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Sales Engineering, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Technical Acumen : Broad technical expertise spanning web security, networking (routing, DNS, DDoS mitigation), cloud infrastructure, and enterprise architecture. 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 public sector/enterprise sales cycles. Communication : Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level government C-suite/elected official business strategy. Strongly Preferred Qualifications (The "Good-to-Haves") Cloudflare AI Stack Experience : Hands-on experience building, deploying, or architecting solutions using Cloudflare's developer platform and AI ecosystem, specifically Workers AI, AI Gateway, and Vectorize. Applied AI Knowledge : Experience with prompt engineering, Large Language Model (LLM) orchestration, or Retrieval-Augmented Generation (RAG) architectures. Coding/Scripting : Proficiency in Python, JavaScript, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Compensation Compensation may be adjusted depending on work location. For Texas based hires: Estimated annual salary of $231,000-$275,000+ OTE, Base + Commissions Equity This role is eligible to participate in Cloudflare’s equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave 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: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. About the Role We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a hybrid product builder who truly understands AI capabilities and can translate technical potential into real user value. You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders. If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together. Key Responsibilities End-to-End AI Product Lifecycle Management Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently. LLM / Agent Capability Productization Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value. AI Evaluation Framework & Quality Standards Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement. Conversational Product Design & Knowledge Engineering Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates. Personalization Engines & Generative UI Products Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness. AI Capability Integration with Business Scenarios Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value. Cross-Functional Collaboration & AI-Native Product Culture Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities. Requirements Product Experience : 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product. AI Technical Understanding : Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals. Evaluation & Data Capabilities : Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset. Documentation & Communication Skills : Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps. User Insight & Product Thinking : Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities. Learning Agility & Ownership Mindset : Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments. Nice to Have Familiarity with cutting-edge AI engineering practices including MCP ( Model Context Protocol ), Function Calling, and multi-agent orchestration frameworks (e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams. Experience with AI Harness / Eval / Benchmark platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems. Background in Fintech / e-commerce / SaaS industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments. Bilingual fluency in Chinese and English (spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: Москва Команда юридических ИИ-систем и автоматизации правового анализа. Основной стек: Python 3.10+, FastAPI, LangChain / LangGraph, OpenSearch, Redis, Kafka Обязанности * разработка и поддержка промышленных пайплайнов вокруг больших языковых моделей (LLM) — интеграция агентов, RAG-модулей, кэширования и асинхронных очередей * реализация многоагентных систем на базе LangGraph / LangChain — orchestration, routing, memory-модули, логика принятия решений * интеграция LLM API (GigaChat, OpenAI, Gemini, Qwen) и разработка внутренних сервисов общения между агентами * подключение векторных и поисковых движков (OpenSearch, Qdrant) для семантического поиска в юридических документах * разработка внутренних REST/gRPC-API для взаимодействия с фронтом, хранилищем и внешними LegalTech-системами * настройка пайплайнов логирования, трейсинга и мониторинга (Prometheus, Grafana, Loki) * совместная работа с Data Science-командой — внедрение моделей, дообучение и эксперименты в продакшне. Требования * опыт коммерческой разработки на Python 3+ от 3 лет * глубокое понимание асинхронного программирования, многопоточности и очередей сообщений * опыт построения микросервисной архитектуры и REST/gRPC-API * навыки работы с векторными базами данных или поисковыми движками * базовое понимание принципов работы LLM, RAG, агентов и промтинг-пайплайнов. Будет плюсом: * опыт с GraphRAG / LangGraph * знание DevOps-практик (CI/CD, контейнеризация, мониторинг) * опыт интеграции с LegalTech-системами, ML-API или хранилищами нормативных актов * навыки работы с генеративными AI-моделями * опыт создания AI-агентов и использования их в работе будет преимуществом * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов. Условия * офисный формат работы, после испытательного гибрид обсуждаем * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Проектировать и развивать LLM/AI-системы и AI-агентов; — Строить многошаговые agentic workflows: routing, tool calling, state management; — Работать с Prompt Engineering и Context Engineering; — Управлять контекстом, памятью и состоянием диалога; — Реализовывать structured output и function/tool calling; — Строить RAG-пайплайны: chunking, embeddings, retrieval, reranking; — Интегрировать LLM с API, базами данных и внутренними сервисами; — Разрабатывать backend-сервисы на Go и AI-компоненты на Python; — Исследовать новые модели и подходы, быстро проверять гипотезы; — Выбирать модели с учетом качества, latency и стоимости; — Строить систему оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge; — Анализировать логи и traces, улучшать качество и стабильность агентов; — Реализовывать retries, fallbacks, timeouts и обработку ошибок; — Доводить решения от прототипа до стабильного production. Требования: Go: — production-сервисы; — REST/gRPC API; — concurrency; — работа с БД; — микросервисная архитектура. Python: — AI-сервисы и backend; — async; — API; — обработка данных; — быстрое прототипирование. Также важно: — Практический опыт разработки production-приложений с LLM; — Понимание архитектуры современных AI-систем: prompt → context → tools → agent → state → evaluation; — Опыт Prompt Engineering: system prompts, few-shot, prompt chaining, structured output; — Опыт Context Engineering: memory, summarization, динамическая сборка контекста; — Опыт создания AI-агентов и agentic workflows; — Работа с LLM API и понимание особенностей разных моделей; — Понимание RAG: embeddings, vector search, retrieval, reranking, hybrid search; — Понимание evals, regression testing и анализа production-логов; — Опыт с PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD; — Понимание production-подходов: observability, scalability, latency, retries, fallbacks и контроль стоимости. Будет плюсом: — Multi-agent системы; — LangGraph; — MCP; — Langfuse / LangSmith; — Elasticsearch / OpenSearch; — Open-source LLM: Qwen, Llama, DeepSeek и др.; — vLLM / Ollama; — Kafka / RabbitMQ; — Kubernetes; — Оптимизация token usage, latency и стоимости LLM; — Guardrails и защита от prompt injection; — Highload-системы. Ищем инженера, который воспринимает LLM не как простой API, а как компонент большой production-системы. Важно уметь проектировать всю логику вокруг модели: какие данные передать в контекст, какого агента или инструмент вызвать, как проверить результат, обработать ошибку и определить следующий шаг. Ищем software engineer с сильной AI/LLM-экспертизой, который умеет не только написать хороший промпт, но и довести всю систему до стабильного production-решения.

Задачи: — Проектировать и развивать LLM/AI-системы и AI-агентов; — Строить многошаговые agentic workflows: routing, tool calling, state management; — Работать с Prompt Engineering и Context Engineering; — Управлять контекстом, памятью и состоянием диалога; — Реализовывать structured output и function/tool calling; — Строить RAG-пайплайны: chunking, embeddings, retrieval, reranking; — Интегрировать LLM с API, базами данных и внутренними сервисами; — Разрабатывать backend-сервисы на Go и AI-компоненты на Python; — Исследовать новые модели и подходы, быстро проверять гипотезы; — Выбирать модели с учетом качества, latency и стоимости; — Строить систему оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge; — Анализировать логи и traces, улучшать качество и стабильность агентов; — Реализовывать retries, fallbacks, timeouts и обработку ошибок; — Доводить решения от прототипа до стабильного production. Требования: Go: — production-сервисы; — REST/gRPC API; — concurrency; — работа с БД; — микросервисная архитектура. Python: — AI-сервисы и backend; — async; — API; — обработка данных; — быстрое прототипирование. Также важно: — Практический опыт разработки production-приложений с LLM; — Понимание архитектуры современных AI-систем: prompt → context → tools → agent → state → evaluation; — Опыт Prompt Engineering: system prompts, few-shot, prompt chaining, structured output; — Опыт Context Engineering: memory, summarization, динамическая сборка контекста; — Опыт создания AI-агентов и agentic workflows; — Работа с LLM API и понимание особенностей разных моделей; — Понимание RAG: embeddings, vector search, retrieval, reranking, hybrid search; — Понимание evals, regression testing и анализа production-логов; — Опыт с PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD; — Понимание production-подходов: observability, scalability, latency, retries, fallbacks и контроль стоимости.

Задачи: — Участие в сложных AI-проектах — Разработка AI-решений в офлайн, безопасной среде — Работа с современными серверными инфраструктурами Требования: — Высшее образование в области AI — Минимум 2 года опыта в ML/DL — Опыт работы с Python, Pytorch/Tensorflow и Hugging Face — Навыки fine-tuning моделей Llama, Qwen, Bert через Lora/Qlora — Работа с Rag и Vector DB (Qdrant, Chromadb, Pgvector) — Подготовка датасетов, очистка данных, скрапинг — Опыт работы с Fastapi, Docker и Git Условия: — Работа в профессиональной команде — Возможности для профессионального развития

Location: Bengaluru, India We are looking for a Senior AI Quality Engineer (L3+) with strong Python skills and hands-on experience testing AI and ML systems. You will analyze requirements, define evaluation strategies, build automated checks, validate models and outputs, test APIs and data pipelines, verify defects through resolution, and contribute to release readiness for your assigned product area. You will both evaluate AI systems and design, build, and operate QE agents for the software testing life cycle. AI-assisted work is part of everyday QE practice on this engagement, with Ragas, DeepEval, promptfoo, Cursor, and other AI and ML tools used for evaluation, scripting, test generation, analysis, and maintenance. You will also build golden datasets, calibrate LLM-as-judge methods, test agentic workflows and RAG systems, implement self-healing and intelligent test approaches, and diagnose quality, safety, performance, and cost failures across distributed AI services. This position is intended for Hyderabad-based candidates who are available to work from the office. The client delivers AI agents, retrieval systems, models, and data pipelines across a broad technology landscape. Quality is part of delivery through evaluation gates, automated regression, model and data validation, security and privacy checks, and evidence that a release is ready. Python is the primary language for AI evaluation, model validation, API testing, data-pipeline quality, and QE agent design. The role combines deterministic automation with probabilistic evaluation to assess AI behavior across models, data, retrieval, tools, and integration surfaces, and designs and operates agents that support the software testing life cycle. Analyze requirements and define evaluation strategies, golden datasets, regression benchmarks, baselines, thresholds, and blocking metrics with domain-expert review. Design, build, and orchestrate AI agents, persona-based workflows, and reusable skills for the STLC using LangChain, LangGraph, or Semantic Kernel. Build automated evaluations and benchmarks for LLMs, agents, RAG, retrieval, tool trajectories, and contracts using Ragas, DeepEval, and promptfoo. Calibrate LLM-as-judge against human grading, manage non-determinism through repeated runs, and detect regression and drift. Write and maintain Python and pytest automation for AI, ML, API, data, and integration workflows. Use Cursor and agentic tools to analyze requirements, generate and review tests, and maintain evaluation suites. Validate deep-learning, reinforcement-learning, and predictive models using LangChain. Build AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, and defect triage, plus intelligent test selection and defect prediction. Integrate LLMs, APIs, embeddings, vector databases, retrieval pipelines, and enterprise data sources into QE frameworks using Python. Test REST and streaming APIs, agent tools, and RAG and MCP integrations, including authentication, errors, retries, and recovery. Test data and retrieval pipelines for schema integrity, lineage, idempotency, fallback, promotion gates, and rollback. Integrate evaluations, benchmarks, and agent workflows into QE frameworks and CI/CD on GitHub Actions, review Allure results, and keep TestRail aligned with automated coverage. Test prompt injection, jailbreaks, unsafe tool use, data exfiltration, access control, PII controls, and guardrails. Measure accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnose distributed failures. Implement tracing, monitoring, and production evaluation using Langfuse, LangSmith, or a comparable AI observability platform. Deploy and operate QE agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Deploy and validate AI and ML solutions on AWS or Azure, including secrets, database services, and cloud-native test infrastructure. Report, track, and verify defects in Jira, and work with domain experts, product, and engineering on traceable coverage and untested scope. Contribute to release readiness for the assigned product area without owning sign-off for the whole team. Strong Python proficiency with pytest for test and evaluation automation. Hands-on experience building and orchestrating AI agents and agentic workflows with LangChain, LangGraph, Semantic Kernel, or comparable frameworks. Hands-on experience building AI evaluations and benchmarks with Ragas, DeepEval, promptfoo, or equivalent tools. Hands-on use of Cursor or agentic development tools for test generation and maintenance. Experience defining AI evaluation strategies, golden datasets, regression benchmarks, and LLM-as-judge calibration, including non-determinism and drift. Experience validating deep-learning, reinforcement-learning, and predictive models with LangChain. Experience building AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, defect triage, intelligent test selection, and defect prediction. Experience integrating LLMs, APIs, embeddings, vector databases, and retrieval pipelines with automation frameworks in Python. Experience testing REST and streaming APIs, agent tools, RAG workflows, and MCP integrations. Experience testing data and retrieval pipelines for correctness, lineage, and safe promotion. Experience integrating AI evaluation and agent workflows with automation frameworks and CI/CD using GitHub Actions, Allure, TestRail, or equivalent tools. Experience testing AI security, privacy, access control, and guardrails. Experience measuring accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnosing distributed failures. Experience with AI tracing, monitoring, and production evaluation using Langfuse, LangSmith, or comparable tools. Familiarity with AWS, Azure, or GCP cloud AI services and agent platforms for deploying and validating AI and ML solutions. Experience deploying and operating agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Experience managing defects through resolution in Jira or an equivalent tool. Ability to work with domain experts, product, and engineering on ground truth and coverage gaps. Experience contributing to release readiness for an assigned product area. Playwright and TypeScript experience for UI and API automation. Real-device and cross-browser execution using LambdaTest, Sauce Labs, or an equivalent platform. Knowledge of AI-driven test optimization and coverage analytics using SeaLights or an equivalent platform. Experience contributing reusable components to shared automation frameworks and reviewing automation code through Git and GitHub workflows. Experience managing test data and troubleshooting test environments needed for reliable execution. Experience triaging security findings and validating operational readiness, monitoring, rollback, and recovery controls. Experience producing audit-ready evaluation reports and improving shared evaluation patterns, automation libraries, and datasets.

Задачи: — Участие в операционной деятельности команды: дейли-митинги, спринт-планирования, ретроспективы, проведение демо для заказчика; — Контроль соблюдения сроков и качества результатов по всем активным проектам; — Проектирование и внедрение LLM решений: NER/классификация/обогащение, semantic search и RAG пайплайны, подготовка датасетов, fine tuning, улучшение метрик; — Ведение проектной документации в соответствии с принятыми стандартами и регламентами компании. Требования: — Опыт DS/ML (3+ лет) и общий опыт в IT около 6 лет, с фокусом на end-to-end внедрения AI/ML решений; — Опыт оценки трудозатрат для комплексных AI-проектов; — Инструменты управления: Jira, Confluence или аналоги для трекинга задач, ведения документации и управления бэклогом; — Понимание полного жизненного цикла ML-проекта: сбор данных, разметка, обучение, валидация, деплой, мониторинг; — Понимание принципов работы LLM, GenAI, RAG и агентных систем — на уровне, достаточном для оценки рисков; — Понимание принципов MLOps: CI/CD для моделей, версионирование данных, автоматизация пайплайнов; — Высокий уровень владения языком Python и опыт разработки production решений и интеграций с корпоративными системами; — Практика работы с корпоративными базами данных (PostgreSQL, ClickHouse, Vertica или аналогичными) и построением витрин/ETL (Airflow, Kafka и т.п.). Условия: — работа в аккредитованной IT-компании (льготная ипотека и проч.); — оформление по ТК РФ и его полное соблюдение (оплачиваемые отпуска, больничные); — ДМС со стоматологией с первых недель работы (а не после испытательного срока).

Requirements: — 4–5+ years of AI/ML or Data Science experience — Advanced Python, SQL, and ML experience — Hands-on experience with LLMs, RAG, embeddings, and transformers — Experience with PyTorch/TensorFlow, Hugging Face, LangChain or LlamaIndex — Experience with vector databases such as Pinecone, FAISS, Milvus, or OpenSearch — MLOps experience with Docker, Kubernetes, MLflow, and CI/CD — AWS and production AI/ML deployment experience The role involves building production GenAI systems, RAG pipelines, recommendation/personalization models, and scalable ML infrastructure from development through deployment. The position is fully remote, with full-time or contract options.

Задачи: — Разрабатывать и развивать высоконагруженные сервисы и платформенные решения на Python — Проектировать и улучшать архитектуру продуктов вместе с командой — Оптимизировать производительность сервисов и автоматизировать процессы разработки — Работать с базами данных, распределёнными системами и современными инструментами разработки — Участвовать в code review, обсуждении технических решений и развитии инженерных практик — Влиять на развитие продуктов на всех этапах — от проектирования до сопровождения Требования: — Знание Python и понимание принципов его работы — Опыт участия в code review — Понимание многопоточности и асинхронного программирования — Умение писать читаемый и поддерживаемый код — Опыт работы с базами данных и понимание принципов их работы — Знакомство с инструментами наблюдаемости: логирование, метрики, трасировка — Понимание принципов ООП, SOLID и основы функционального программирования Преимущества: — Опыт проектирования распределённых систем и работы с Kubernetes — Опыт внедрения AI-решений в продукты или интерес к AI, LLM и RAG — Участие в улучшении процессов разработки и развитии продуктовых решений

Проект: Мы разрабатываем и поддерживаем продукт ERA - систему комплексной диагностики продуктов и услуг. Наше решение позволяет производить диагностику, анализ и аудит продукта для получения комплексного решения развития, снятия барьеров роста. Цель проекта — построить полностью автономную экспертную систему, где ключевую роль играют смарт-агенты, выполняющие комплексный анализ без участия человека. Технологический стек: Язык программирования: Python 3.12+ Фреймворки: FastAPI, LangChain / LangGraph, FastStream Базы данных: PostgreSQL, Redis Очереди: Kafka, RabbitMQ Поиск и аналитика: Opensearch, Elasticsearch CI/CD: Jenkins, Nexus, BitBucket, SonarQube Инфраструктура: OpenShift (Kubernetes), DropApp, Docker Управление: Jira, Confluence Требования: Высшее профильное образование Опыт коммерческой разработки на Python от 4 лет (по ТК РФ) Уверенное знание Python 3.7+ (в проекте используется 3.12+) Понимание и успешный опыт применения паттернов проектирования (GoF, SOLID, GRASP) Опыт проведения код-ревью и работы по GitFlow Опыт разработки агентных систем с помощью langchain, langgraph и успешное внедрение в промышленную среду Опыт разработки приложений, основанных на микросервисной архитектуре Уверенное знание SQL и понимание принципов работы реляционных СУБД (PostgreSQL) Опыт написания unit-тестов Опыт разработки асинхронных приложений на Python Понимание жизненного цикла разработки приложений в контексте Agile Важно: Опыт и желание работать в команде, умение аргументировать свои решения и договариваться Задачи: Разработка co-pilot решения на базе данных RAG и применении LLM Разработка и интеграция AI-агентов, исследование новых поверхностей взаимодействия с AI Разработка микросервисов на Python в качестве MCP инструментов Анализ требований, формализация функционала, проектирование архитектуры взаимодействия агентов и сервисов Участие в планировании, декомпозиции задач и оценке сложностей, планировании спринтов на основе SCRUM церемоний Проведение код-ревью, поддержание высокого стандарта качества и чистоты кода Тесное взаимодействие с командой на всех этапах разработки Участие в подготовке и выпуске релизов, взаимодействие со смежными подразделениями Документирование своей работы и менторство джуниор-разработчиков Условия: Возможность участия в интересном проекте Возможность профессионального и карьерного роста в компании Опыт работы в команде профессионалов Уровень заработной платы обсуждается индивидуально Формат работы - офисный формат в Москве на период ИС, далее возможен гибрид