Вакансии

Задачи: — Разработка AI агентов, которые выполняют рабочие процессы, а не только чат-интерфейсы. — Работа с агентами, которые подключаются к API и внутренним системам, используют инструменты, извлекают контекст, принимают решения на нескольких шагах и восстанавливаются при ошибках. Требования: — Опыт разработки на Python и бекенд инженерия. — Опыт работы с LLM API и агентными системами в продакшене. — Знание LangGraph, LangChain, LlamaIndex или аналогичных технологий. — Опыт работы с вызовом функций/инструментов и структурированными выводами. — Знание RAG, embeddings, векторного поиска и управления контекстом. — Опыт работы с состоянием агента, памятью, маршрутизацией, повторными попытками и логикой резервного копирования. — Интеграция с API и событийно-ориентированные рабочие процессы. — Оценка, трассировка и отладка LLM. — Опыт работы с Docker, Kubernetes, CI/CD и AWS. — Преимуществом является опыт с мультиагентной оркестрацией, MCP, human-in-the-loop рабочими процессами или мониторингом агентов в продакшене. Условия: — Удалённая работа. — Полная занятость или контракт. Это практическая инженерная роль с ответственностью за дизайн агента, реализацию, оценку, деплой и надёжность в продакшене.

Задачи: — разработка multi-agent систем (MAS) для Deep Research задач — создание LLM-агентов с использованием tool calling, planning и reasoning — проектирование и развитие RAG-архитектуры включая поверх коллекции из 850+ млн документов — разработка и поддержка knowledge graph для аналитических и исследовательских сценариев — оптимизация LLM inference (latency, throughput, batching, KV cache) — подготовка и оптимизация моделей для production — разработка воспроизводимых ML pipelines и инфраструктуры экспериментов — внедрение и эксплуатация AI / ML сервисов в production Требования: — 3+ лет опыта реализации проектов в Machine Learning / AI — знание паттерной архитектуры и системного дизайна — уверенное владение Python — опыт разработки систем на базе LLM — опыт построения RAG систем или AI-агентов — опыт вывода ML/AI сервисов в production — понимание архитектуры ML pipelines и инженерного подхода Условия: — участие в развитии одной из крупнейших аналитических платформ научных данных — работа с современными LLM и AI-архитектурами — сильная исследовательская и инженерная команда — гибкий график (начало рабочего дня с 8:00 до 11:00) — гибридный формат работы (возможна удалёнка) — обучение и курсы НИУ ВШЭ, английский язык — доступ к библиотеке НИУ ВШЭ и образовательным ресурсам — софинансирование ДМС — программы лояльности фитнес-клубов и театров — офис на Мясницкой (м. Лубянка / м. Тургеневская)

Задачи: – управлять командой разработчиков: координировать задачи, декомпозировать их, контролировать технические решения и проводить code review; – помогать команде в решении сложных технических задач; – развивать и технологически совершенствовать систему анализа больших данных; – участвовать в архитектурных решениях: проектировать API, разрабатывать сервисы и бизнес-логику; – проектировать и системно внедрять новые решения; – отвечать за производительность, качество и устойчивость решений; – заниматься развитием и ростом команды. Требования: – от 5 лет коммерческой разработки на Python (Backend / Fullstack); – от 3 лет опыта руководства командой; – уверенное знание Python 3.8+, asyncio, FastAPI и инструментов экосистемы (poetry/pdm, nox/tox, blake); – продвинутый уровень Linux; – хороший уровень SQL, опыт работы с PostgreSQL и ClickHouse; – базовое знание ML; – английский на уровне чтения технической и научной литературы; – сильные коммуникационные навыки: умение объяснять сложные технические решения и находить общий язык с командой. Будет плюсом: – опыт работы с системами обработки больших объёмов данных; – опыт внедрения AI-решений в разработку; – знание Go; – глубокое понимание микросервисной архитектуры, REST, observability и масштабирования; – опыт работы с fastMCP и агентными системами; – опыт реализации AI-решений: RAG, агенты и др. Условия: – масштабный проект с реальным применением технологий анализа больших данных; – обучение: семинары, курсы и тренинги от НИУ ВШЭ, английский язык; – гибридный формат работы в Москве или удалённый формат по РФ; – гибкое начало рабочего дня с 8:00 до 11:00; – софинансирование ДМС; – программы лояльности от крупных фитнес-клубов и театров Москвы; – доступ к библиотеке НИУ ВШЭ, электронным и аудиокнигам «МИФ»; – офис на Мясницкой — рядом с метро и любимыми городскими местами; – скидки в «Даблби», «Ska vi fika?» и «Буквышке» для сотрудников НИУ ВШЭ.

Проект: Ритейл. Задачи: — Описание текущего процесса AS IS и целевого процесса TO BE для каждой инициативы; — Сбор, структурирование и согласование бизнес- и пользовательских требований с заказчиками из бизнес-подразделений; — Определение и фиксация scope инициативы, границ PoC и промышленного внедрения; — Выявление исключений, пограничных сценариев и зависимостей от смежных систем и команд; — Формирование функциональных и нефункциональных требований к ИИ-решению (качество ответов, точность, время отклика, ограничения по данным и безопасности); — Декомпозиция инициативы на этапы совместно с ML-инженерами и продакт-менеджером; — Формирование и согласование критериев приемки, в том числе метрик качества модели/агента; — Помощь бизнесу в определении бизнес-эффекта и метрик успеха инициативы, подготовка обоснования эффекта; — Контроль изменений требований в процессе реализации, ведение документации по инициативе. Требования: — Общий опыт работы: от 4 лет в роли бизнес-/системного аналитика; — Опыт по требуемому стеку/направлению: от 1,5 лет участия в проектах внедрения ML/ИИ или продуктов на основе LLM (сбор требований к моделям, метрики качества, критерии приемки); — Релевантный проектный опыт: не менее 2–3 завершённых проектов внедрения аналитических / ИИ-решений в бизнес-процессы крупной компании: от описания процесса до приемки; — Опыт работы с несколькими бизнес-заказчиками параллельно; — Отраслевой опыт: желательно e-commerce, ритейл, B2B-дистрибуция, логистика, клиентский сервис / контакт-центр; — Обязательные технологии/инструменты: нотации описания процессов и требований BPMN, UML/use case, user story, критерии приемки; Confluence / вики-системы, Jira или аналоги; SQL на уровне выборок для проверки данных и гипотез; понимание принципов работы LLM, RAG, промптинга и метрик качества ИИ-решений (precision/recall, точность извлечения, оценка ответов); — Желательные технологии/инструменты: опыт работы с платформами оркестрации LLM (Dify, LangChain, n8n и т.п.); Python на базовом уровне (чтение кода, простые скрипты для проверки данных); опыт расчёта бизнес-эффекта и ROI инициатив, подготовки материалов для руководства; Google Sheets / Excel на продвинутом уровне; — Системы учета задач и документации: Jira / Yandex Tracker, Confluence / Yandex Wiki, реестр ИИ-инициатив в Google Sheets, Битрикс24. Условия: — Занятость: проектная, долгосрочный проект (фултайм); — Формат: удаленно; — Локация: строго Москва, Саранск; — Оформление: ГПХ, ИП; — Вилка оплаты: до 1500 рублей в час гросс; — Важно: не рассматриваются кандидаты с проектами Лимана, Петрович Тех, ВБ, Озон, Лента Тех, Яндекс маркет, М.

Location: Remote - Global Workplace: Remote About the company Trust Wallet is the secure, self-custody Web3 wallet that empowers people to own and control their digital assets. Whether you're new to crypto or an experienced user, Trust Wallet makes it easier, safer, and more convenient to explore Web3, securely access dApps, manage your crypto, and buy and sell digital assets, all in one place. About the Role We're looking for a Lead AI Engineer to own the backend and Agent systems behind our LLM-powered products. The role is end to end: you'll build the Agent workflows, define how we measure quality, keep them reliable in production, and shape where the product goes next. This role is for someone who has shipped LLM features to real users, stayed with them after launch, and can prove with data that their changes made things better. Job Scope: Build and own AI backend and Agent workflows - Design, build, and maintain multi-turn conversation systems, including context management, tool calling, knowledge retrieval (RAG), state management, and human handoff. Drive evaluation and continuous improvement - Define success criteria with Product, Design, and QA leads. - Turn production failures into evaluation samples and regression tests. - Measure the impact and side effects of every change before and after release. Diagnose problems across the stack - Isolate the root cause of failures: model judgment, knowledge gaps, abnormal tool responses, backend instability, or conflicting rules. - Apply the right fix for each cause rather than defaulting to prompt tweaks. Own production reliability - Handle timeouts, retries, graceful degradation, async jobs, and third-party dependency failures. - Make sure every issue is traceable through logs, every change is versioned, and every failure has a recovery path. Shape product and technical decisions - Give clear, reasoned positions on requirements, covering feasibility, cost, risk, and alternatives. - Propose better approaches and break work into phased, shippable deliverables. Communicate proactively and follow through - Share progress, blockers, ETAs, and next checkpoints without needing to be chased. - After launch, track real-world impact and leave clear documentation and handover materials. Requirements: - Production LLM/Agent experience at scale. You've built LLM or Agent features used by 10,000+ active users, and you've maintained and improved them after launch. - Strong backend engineering fundamentals. You're comfortable owning production code, APIs, data flows, and incident troubleshooting. Experience designing and implement backend services in Golang and integrate with LLMs and AI systems. - Real evaluation discipline. You've built evaluation sets, regression suites, and production monitoring, and you can explain how you confirmed an improvement was real rather than random fluctuation. - Ownership mindset. You make decisions, surface risks early, and don't consider a feature done until it's verified in production. - Web3 experience. Preferably 1 year of experience in a crypto, DeFi, or Web3 company (wallet, exchange, L1/L2 protocol, or DeFi platform strongly preferred) ADDITIONAL INFORMATION This is a global and fully remote role. You must have the right to work for the country you are based. WHY WORK AT TRUST WALLET? - Be a part of the world’s leading blockchain ecosystem that continues to grow. - Excellent learning and career development opportunities. - Work alongside diverse, world-class talent, in an environment where learning and growth opportunities are endless. - Tackle fast-paced, challenging and unique projects. - Work in a truly global organization, with international teams and a flat organizational structure. - Work fully remotely with flexible working hours. - Enjoy competitive salary and benefits. Apply today to join our team in building the world’s most trusted and secure crypto wallet and enable a decentralized future for everyone. Trust Wallet is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. *Due to the large amount of the applications, please consider your application as unsuccessful should you not be contacted within 4 weeks from your application date.

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: New York City 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 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. 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. Compensation may be adjusted depending on work location. For New York City, New Jersey based hires: Estimated annual salary of $204,000.00 - $321,000.00 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.

Задачи: — Разработка AI агентов, которые выполняют рабочие процессы, а не только чат-интерфейсы. — Работа с агентами, которые подключаются к API и внутренним системам, используют инструменты, извлекают контекст, принимают решения на нескольких шагах и восстанавливаются при ошибках. Требования: — Опыт разработки на Python и бекенд инженерия. — Опыт работы с LLM API и агентными системами в продакшене. — Знание LangGraph, LangChain, LlamaIndex или аналогичных технологий. — Опыт работы с вызовом функций/инструментов и структурированными выводами. — Знание RAG, embeddings, векторного поиска и управления контекстом. — Опыт работы с состоянием агента, памятью, маршрутизацией, повторными попытками и логикой резервного копирования. — Интеграция с API и событийно-ориентированные рабочие процессы. — Оценка, трассировка и отладка LLM. — Опыт работы с Docker, Kubernetes, CI/CD и AWS. — Преимуществом является опыт с мультиагентной оркестрацией, MCP, human-in-the-loop рабочими процессами или мониторингом агентов в продакшене. Условия: — Удалённая работа. — Полная занятость или контракт. Это практическая инженерная роль с ответственностью за дизайн агента, реализацию, оценку, деплой и надёжность в продакшене.

Location: Egypt Workplace: Remote Specright is the first purpose-built, patented platform for Specification Management. Whether it's packaging, raw materials, formulas, products, or machines, Specright helps companies digitize, map, and take action across their supply chain to reduce costs, increase profitability, and drive sustainability. Specright serves customers across industries, including packaging, food and beverage, consumer packaged goods, pharmaceutical, retail, industrials, and more. We're looking for an Agentic Software Engineer (Full-Stack) to help us ship reliable, user-facing AI agent products to production — fast. You'll work at the intersection of modern AI tooling and strong software engineering discipline, building agentic experiences that our customers and internal teams rely on every day.This is not a research role. You will own production systems end-to-end: designing agent architectures, writing and reviewing code (often with agentic coding assistants), setting up rigorous evals, and operating what you build. If you care about making AI agents that actually work — not just demo well — this roleis for you. What You'll Do - Build and Ship Agentic Applications Design, develop, and deliver agentic products end-to-end — including chat-based interfaces, AI workflow tools, and internal copilots — that serve real users in production. - Leverage Agentic Coding Workflows Use modern agentic coding tools daily (e.g., Claude Code, Codex, Cursor, and similar assistants) to accelerate delivery while maintaining high code quality and engineering standards. - Design Agent Systems Architect agent internals: tool calling, multi-step orchestration, memory and state management, retrieval pipelines, permissions models, and failure recovery strategies. - Own Evals and Quality Build and maintain agent evaluation infrastructure — regression suites, scenario-based tests, golden traces, and both offline and online metrics — so you always know whether your agent got better or worse. - Implement Observability Instrument agents with production-grade observability: distributed tracing, prompt and version tracking, tool-call telemetry, and cost/latency monitoring. - Own Production Readiness Take responsibility for the full lifecycle: rollout plans, QA, guardrails, incident response, and continuous improvement of deployed agents. What You Bring (Must-Haves) - Proven full-stack engineering ability. You've shipped production software end-to-end — not justprototypes or demos. - Hands-on experience building LLM-powered agents that work in production. You've owned at least 1–2 agentic features or products through deployment and operation. - Deep familiarity with agentic coding best practices. You understand task decomposition, agent delegation, prompt hygiene, iterative loops, and how to review and steer agentic outputs effectively. - Practical experience with agent evals and tracing. You've gone beyond model benchmarking to build evaluation systems specifically for agent behavior — including trace-based debugging and regression detection. - Solid engineering fundamentals. Testing, debugging, security basics, performance optimization, and reliability are second nature to you. Nice-to-Haves - Proficiency in TypeScript/Node.js and/or Python, with experience in modern web stacks and startup-pace delivery. - Familiarity with agent tooling ecosystems: prompt/version stores, eval harnesses, tracing and telemetry platforms (OpenTelemetry, LangSmith, Datadog, Honeycomb, or similar). - Experience with RAG architectures: vector databases, indexing strategies, chunking approaches, and retrieval evaluation. - Experience designing tool APIs for agents: structured output schemas, idempotency, rate limiting, and error handling patterns that make agents more reliable. We are an energetic company with an entrepreneurial, informal, versatile, intelligent, and fast-paced culture. We are a 100% remote company and promote an open and relatively flat organization with an emphasis on collaboration, sharing ideas, and information. It's more important to innovate than to worry about making mistakes. Specright is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Задачи: — Разработка и внедрение AI/ML решений с использованием LLM, Python и связанных технологий — Работа с production-grade LLM, RAG, NLP, embeddings и векторными базами данных — Парсинг документов, извлечение информации и обработка больших объемов текста — Использование LangChain, LangGraph, CrewAI, Claude Code — Работа с облачными сервисами AWS SageMaker, Bedrock, EC2, Lambda, Azure AI, OpenAI — Использование MLflow, W&B, CI/CD, Docker, Kubernetes для управления ML-процессами — Оценка AI моделей, улучшение и обеспечение наблюдаемости — Руководство командой, наставничество и коммуникация Требования: — Опыт работы в AI/ML инженерии от 3 лет — Знание Python, SQL, NumPy, Pandas, Scikit-learn, PyTorch или TensorFlow — Опыт работы с LLM, NLP, embeddings, векторными базами данных — Знание LangChain, LangGraph, CrewAI, Claude Code — Опыт работы с AWS и Azure AI сервисами — Навыки работы с MLflow, W&B, CI/CD, Docker, Kubernetes — Высшее образование в технической области Условия: — Работа в офисе, 5-дневная рабочая неделя — Локации: Hyderabad, Ahmedabad, Indore — Максимальный срок уведомления о выходе на работу: 15 дней — Процесс интервью: 3 технических/менеджерских раунда + обсуждение CTC Для отклика необходимо предоставить: — Имя кандидата, обновленное резюме, общий опыт, релевантный опыт AI/ML — Количество реализованных production AI/ML систем — Текущая компания и должность, текущее и ожидаемое вознаграждение — Местоположение и предпочтительное место работы — Наличие офферов, причина смены работы, готовность к немедленному выходу — Контактный номер, профиль LinkedIn, релевантные навыки AI/ML и LLM

Location: San Francisco, CA; New York, NY 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. ABOUT THE TRAVEL, TRANSPORTATION AND HOSPITALITY TEAM - The Travel, Transportation and Hospitality (TTH) supports some of the largest airlines, hotel chains, rental car brands, cruise lines and travel tech companies in the world. Our customers are pioneers in the travel space and are true thought partners in shaping our platform, helping reinvent what hospitality looks like in this new era. Our customers rely on us not only to deliver exceptional customer experiences, but also to drive meaningful growth for their businesses. - Our TTH team is constantly pushing the bounds of what is possible within this industry and beyond. We help support our customers in the moments that matter — whether that’s proactively encouraging new bookings to prepare for exciting events, or helping guests rebook their flights or stays during times of distress. We help our customers maximize the lifetime value of their guests and build products to delight guests at every touchpoint. - We’re a small and scrappy team, and we support each other with any deliverables we have to meet. Every engineer on TTH is also a product-led thinker; every PM on TTH is tinkering and developing tangible prototypes; and every strategist on TTH is capable of owning an agent end to end. As a part of this team, you’ll set the standard for what it means to go beyond your role, and help build the travel industry of the future. 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.

Задачи: — Разработка production-ready AI, LLM и agent-based решений. — Управление полным циклом разработки AI: архитектура, реализация, тестирование, деплой и эксплуатация. — Интеграция компонентов на базе LLM с детерминированной логикой, Context Engineering и Harness Engineering. — Разработка Tool Calling Loops и подключение API, backend-сервисов и корпоративного ПО. Требования: — Минимум 3 года опыта создания и поддержки production AI приложений на базе LLM. — Не менее 3 лет практического опыта в Agentic Engineering, включая дизайн, реализацию, интеграцию, деплой и поддержку AI агентов. — Опыт разработки Tool Calling Loops и интеграции с API и backend. — Опыт интеграции LLM-компонентов с Context Engineering и Harness Engineering (минимум 1 год). — Знание MCP и корпоративных AI интеграций. — Опыт с RAG-решениями и разработкой LLM приложений. — Умение управлять полным циклом AI разработки. — Отличные коммуникативные навыки для взаимодействия с командами и бизнес-стейкхолдерами. — Наличие минимум 2 проектов с подтверждённым опытом коммуникации со стейкхолдерами. Дополнительные преимущества: — Знания в области AI governance, безопасности, комплаенса и защиты данных. — Опыт работы с инструментами мониторинга AI, такими как Langfuse, Arize и аналогичными. — Опыт с корпоративными AI экосистемами, AI шлюзами, управлением жизненным циклом prompt и governance моделей. — Понимание дизайна мультиагентных систем и оркестрации агентов. — Более 2 лет опыта с RAG и MCP серверами. — Знакомство с AWS и AWS Kiro. — Опыт внедрения AI guardrails и мер безопасности. — Знание CI/CD и практик автоматизированного тестирования. Условия: — Контракт до 31 декабря 2029 года с возможностью продления. — Полная занятость. — Полностью удалённая работа в пределах ЕС. — Требуемый уровень английского C1. — Старт как можно скорее.

Location: Москва В кластере несколько продуктов для расчетов результативности сотрудников банка:  * Сервисы расчета результативности (от расчета показателей в КПЭ до учета этих данных в премии сотрудника) * AI-Ассистент для консультации сотрудников продающих ролей по статусу учета продаж сотрудника в результативности * Сервисы ведения и рекомендаций финансовых целей для руководителей ТОП-600 * Расчета стоимости встреч в Jazz * Сервисы ведения продуктовых атрибутов B2C, B2B для ведения расчетов финансовых показателей на единой модели данных платформы FinAl **По тех теку решения делятся на:** * Greenplum, Hadoop - ежедневный учет продаж физической сети банка (соблюдений критериев мотивации) * PHP и Java - расчет сводных коэффициентов результативности для целей премирования * собственная платформа ЕРМ - конструктор методик премирования, связи с моделями планирования (бизнеса, численности). Команда кластера 50 человек, распределена на 3 города: Москва, Нижний Новгород и Воронеж. Обязанности ### **Задачи ИТ Лидера:** * определение целевой архитектуры решений кластера, как части ЕРМ платформы, обеспечивающей автономные бизнес процессы на базе AI * контроль соответствия, разрабатываемого ПО архитектурным требованиям, технический и архитектурный контроль процессов разработки систем * разработка и исполнение ИТ стратегии развития продукта * формирование дорожных карт инициатив * подбор, развитие компетенции сотрудников, управление их мотивацией и карьерными треками; * выстраивание взаимодействия с кросс-командами, выявление и устранение проектных и кросс-проектных ИТ рисков * управление бюджетами проектов. Требования ### **Мы ожидаем:** * опыт разработки ПО от 5 лет в роли архитектора или руководителя команды разработки * опыт подбора, управления, развития и удержания IT-команд от 30 человек * опыт управления сложными высоконагруженными или критичными для бизнеса информационными системами, желательно в банковском или финансовом секторе * опыт формирования целевой архитектуры продукта и управления ее реализацией практический опыт построения AI-native решений: понимание того, как перестраивать архитектуру и процессы разработки с учетом применения AI, а не просто добавлять AI-функциональность в существующий продукт * понимание современных подходов к использованию генеративного AI, LLM, AI-агентов, RAG, ML/AI-пайплайнов, MLOps/LLMOps и принципов интеграции AI в корпоративные системы. **Будет плюсом** * опыт работы с классическими BI-системами (Tableau, QlikView, SAP BW) или open-source решениями (Superset) или российскими BI-решениями * опыт проектирования, построения и внедрения информационно-аналитических систем, ETL, DWH и BI решений * опыт разработки систем бюджетирования, планирования или бизнес-анализа. Условия ### Мы предлагаем: * конкурентная заработная плата: оклад + бонусы * масштабные и интересные задачи в agile команде * комфортный офис на м. Кутузовская, Сбербанк Agile Home * ДМС для сотрудников и скидки на медицинскую страховку для родственников * бесплатный тренажерный зал и спортивные групповые занятия * обучение и тренинги · Профессиональный и позитивный коллектив.

О компании и команде Мы вошли в топ лучших it-работодателей России 2025 на Хабр Карьере. В Strikt мы превращаем хаотичные бизнес-процессы наших заказчиков в четкие, самообучающиеся алгоритмы с использованием ИИ. Ищем к нам в команду опытного Data Scientist для работы над интересными проектами в областях AdTech, Machine Learning! Требования: — Высшее техническое или математическое образование; — От 3–4 лет коммерческого опыта в Data Science / ML; — Сильная база в статистике, классическом ML и анализе данных; — Опыт работы с Time Series: прогнозирование, скользящее окно, тренды, сезонность, оценка качества моделей; — Опыт участия в проектах с LLM / NLP / GenAI: промпты, embeddings, RAG или интеграция LLM в продуктовые сценарии; — Уверенный Python: pandas, numpy, scikit-learn, matplotlib, Jupyter Notebook; — Знание SQL и понимание работы с реляционными БД; — Умение самостоятельно разбираться в задаче, выбирать подход и объяснять решение команде; — Готовность помогать junior/middle DS-специалистам; — Будет плюсом: Английский язык на уровне чтения технической документации PyTorch / TensorFlow / Hugging Face, CatBoost / LightGBM / XGBoost, LangChain / LlamaIndex / vector databases, понимание MLOps, мониторинга качества моделей и CI/CD. Задачи: — Работать с задачами Time Series, классического ML и LLM/NLP; — Развивать и улучшать существующие ML-модели в проектах; — Помогать выбирать подходы, метрики и критерии качества; — Анализировать данные, строить гипотезы и проводить эксперименты; — Работать с SQL и Python для извлечения, очистки и анализа данных; — Ревьюить решения менее опытных DS-специалистов и помогать команде расти. Условия: — Полностью удалённая работа; — Part-time занятость; — Оформление по договору с самозанятым или ИП с первого дня; — Проекты на стыке Data Science, Time Series, LLM/NLP и прикладного AI; — Сильная команда, возможность влиять на технические решения.

Задачи: — Разрабатывать Python / SQL-пайплайны загрузки и обработки данных из файлов, API и информационных систем. — Проектировать таблицы хранилища: сущности, связи, правила преобразования. — Встраивать псевдоанонимизацию и проверки качества в потоки данных. — Готовить признаки и версионируемые train/validation/test-выборки. — Обеспечивать прослеживаемость и воспроизводимость ML / LLM-экспериментов. — Вместе с ML-командой развивать оценку моделей, подготовку данных для RAG и дообучения. Требования: — Уверенные Python и SQL, поддерживаемый код за пределами ноутбуков. — Практический опыт ETL / ELT: оркестрация, инкрементальная обработка, повторные запуски. — Опыт с S3, Parquet, pandas / Polars / PyArrow. — Понимание жизненного цикла ML: выборки, baseline, метрики, проверка утечек. — Опыт с MLflow, ClearML или аналогами. — Linux, Git, Docker, CI/CD. — Умение работать с чувствительными данными. Будет плюсом: — Опыт с медицинскими данными, МИС и клиническими справочниками. — Практический NLP / LLM: извлечение данных из текста, embeddings, RAG. — PyTorch / Hugging Face, дообучение и inference на GPU. — Опыт превращения исследовательского прототипа в регулярный пайплайн. Условия: — Гибридный / удаленный по РФ формат работы. Дополнительно: — Проект в HealthTech, поддержка врачебных решений. — Возможность строить платформу с нуля и влиять на архитектуру. — Работа на стыке Data Engineering, MLOps и LLM с современным стеком.

Задачи: — Разрабатывать и улучшать RAG-приложения: chunking, embeddings, retrieval и reranking. — Создавать LLM-воркфлоу и агентов с использованием LangChain, LangGraph, LlamaIndex, CrewAI или аналогичных. — Разрабатывать переписывание запросов, классификацию намерений, маршрутизацию и структурированное извлечение. — Интегрировать LLM API/модели в производственные системы. — Работать с OpenAI, Gemini, Hugging Face и PyTorch. — Вносить вклад в SFT, LoRA, QLoRA, PEFT и оценку LLM. — Работать с OCR, PDF/DOCX, STT и памятью для диалогов. — Создавать API с Python/FastAPI и работать с Docker, Git, тестированием и CI/CD. — Мониторить и улучшать качество моделей, задержки и стоимость. — Брать ответственность за отдельные функции/компоненты под наставничеством старшего инженера. Требования: — 2–4 года опыта в NLP, ML, информационном поиске или прикладном ИИ. — Сильные навыки Python. — Практический опыт с LLM, RAG и AI-агентами. — Понимание трансформеров, embeddings, prompting, retrieval, chunking и reranking. — Опыт работы с LangChain, LangGraph, LlamaIndex, CrewAI. — Опыт с Qdrant, Pinecone, Milvus, Weaviate, Elasticsearch. — Опыт с OpenAI, Gemini, Hugging Face и знание PyTorch. — Понимание оценки LLM и снижения галлюцинаций. — Навыки работы с FastAPI, REST, Docker, Git. — Знание многоязычного NLP будет плюсом. — Профессиональный английский. Желательно: — Знания SFT, LoRA, QLoRA, PEFT. — Знания BM25, RRF. — Опыт с RAGAS, DeepEval, LangSmith, LangFuse. — Опыт с OCR, STT. — Опыт с Graph RAG. — Опыт с vLLM, TGI, Triton. — Оптимизация под GPU. — Знание корейского языка будет плюсом. Условия: — Возможна поддержка визы и релокации в Южную Корею.

Задачи: — Построить внутреннюю AI-платформу знаний, интегрирующую локальные LLM, Box и внешние AI-сервисы. — Обеспечить интерфейс для 10–20 сотрудников для поиска и использования корпоративных знаний, взаимодействия с AI-моделями и генерации ответов и документов с указанием источников. Требования: — Развертывание локальных LLM на Mac Studio (Ollama или аналог). — Интеграция с Box API и поиск по крупномасштабным данным компании по запросу. — Реализация RAG, извлечение документов и их повторная ранжировка. — Интеграция с внешними AI API, такими как OpenAI/GPT, Gemini, Grok и др. — Создание AI Router/Orchestrator для выбора или комбинирования нескольких моделей. — Аутентификация пользователей и доступ к документам с учётом прав. — Ведение истории разговоров, управление знаниями и аудит логов. — Отслеживание использования API, затрат и обеспечение безопасности. — Архитектура backend/API, пригодная для дальнейшего расширения. Условия: — Начать с небольшого PoC и расширить до продакшена после проверки точности поиска, качества ответов, производительности, безопасности и затрат на эксплуатацию. Особенности: — Не планируется скачивать или встраивать весь набор данных Box, предпочтение отдаётся поиску по запросу с выборкой релевантных документов и передачей контекста выбранной LLM. При отклике необходимо кратко описать опыт с локальными LLM, RAG, Box или аналогичными API корпоративного хранилища, мульти-LLM интеграцией и рекомендуемым стеком технологий для проекта.

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. Job Location: Singapore What you will do as a Senior Customer Engineer The Senior 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 Experience: 7+ years of 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 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. This role requires frequent travel to Indonesia and work directly with clients communicate in Bahasa Indonesia. Fluency in Bahasa Indonesia is preferred. 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.

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.