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Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Director, Analytics Engineering, you'll lead a team of 8 and report to the VP of Data & Insights. You set direction across the data organization, stay close enough to the work to guide technical decisions credibly, and partner with Data Engineering, Data Science, IT, and business leaders. You will have three mandates: Build trusted, AI-ready self-service. Deliver a semantic model that answers business questions correctly, with the telemetry, evals, and model flexibility to prove it and keep costs in check. Set the strategy for how GitLab accesses data. Own the data models, BI tools, and AI access patterns (Claude, MCP servers, Slack agents) that put trusted data in everyone's hands. Build data applications the whole company relies on. Ship production-grade apps that combine trusted data, APIs, and AI to answer questions dashboards can't. What you'll do Build and own a trusted semantic model, with governed metrics and business definitions, that answers business questions consistently across every tool Build evals and ground-truth datasets that measure answer quality, and use them to drive improvements and catch regressions Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they get stuck Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and quality Own data modeling and curated datasets for self-service, with the ownership, data contracts, testing, and documentation that make them AI-ready Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the governance and security to keep access trusted and reliable Own the enterprise BI and self-service tools strategy (e.g., Tableau, Omni), including evaluation, adoption, and cost Build self-service capabilities, such as Claude skills, documentation, and guided workflows, that help people find and use data on their own Build and own company-wide data applications, from Claude-built single-page apps to apps inside BI tools, that combine Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake Set engineering standards for data apps (security, authentication, testing, deployment, and monitoring) so they're reliable at company scale Set a long-range roadmap tied to company strategy, and a lightweight operating model that balances urgent stakeholder needs with investment in reusable data products and tech-debt reduction Hire, coach, and retain a high-performing team of 8: build career paths, develop leaders, distribute ownership, and recognize great work Act as customer zero for GitLab and GitLab Duo in data workflows, sharing feedback with Product and Engineering What you'll bring 12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads Deep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic views, LookML, Cube), and expert dbt, including testing and CI/CD across a multi-team project Hands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including evals and telemetry for answer quality, and advanced use of AI coding agents such as Claude Code Expert SQL and strong Snowflake experience; working knowledge of Python Strong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies) Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scale Systems thinker who sees how models, pipelines, and architecture decisions connect, and designs for second-order effects Exceptional communicator who writes clear technical specs, sets a clear vision, makes trade-offs visible, and influences executives and peers across the company Pragmatic in ambiguity: makes sound decisions on emerging technology and ships the right next version rather than waiting for the ideal end state Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values Nice to Have Experience with LLM routing or gateway tools and managing model costs Experience with Tableau, Omni, or a BI platform migration Experience with web app development (e.g., React, TypeScript) and Postgres Experience owning finance or revenue-critical data (e.g., ARR, consumption) where accuracy and auditability are non-negotiable About the Team Analytics Engineering makes GitLab's data trusted, easy to find, and ready for anyone to use, whether they ask a dashboard, Claude, or a Slack agent. We own the curated data models, the semantic layer, the self-service tools, and the data applications that let teams answer their own questions. AI is changing how people get to data. Questions that once went through an analyst now go straight to AI tools, so the answers are only as good as the data models and business definitions behind them. Our job is to make those answers correct, consistent, and measurable. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $139,200 — $285,600 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Задачи: — Разрабатывать новые backend-сервисы и поддерживать существующие — Проектировать, разрабатывать и интегрировать RESTful API с использованием FastAPI — Проектировать и оптимизировать схемы, индексы и запросы PostgreSQL — Писать unit и интеграционные тесты, участвовать в код-ревью, поддерживать качество кода — Строить и поддерживать CI/CD пайплайны для автоматического тестирования и деплоя — Контейнеризировать и деплоить сервисы с помощью Docker и Kubernetes — Реализовывать аутентификацию, авторизацию и практики безопасного кодирования — Интегрировать AI-возможности с использованием MCP (Model Context Protocol) — Оптимизировать производительность приложения и эффективность базы данных — Сотрудничать с frontend-разработчиками и продуктовыми командами Требования: — Опыт коммерческой backend-разработки от 3 лет — Глубокие знания Python и FastAPI — Практический опыт с PostgreSQL, оптимизацией SQL, индексами и миграциями — Опыт с pytest, unit и интеграционным тестированием, принципами TDD — Опыт работы с CI/CD инструментами (GitHub Actions, GitLab CI или аналогичными) — Практический опыт с Docker и Kubernetes — Понимание принципов проектирования REST API и безопасности приложений — Знание Git и практик совместной разработки — Владение английским языком Будет плюсом: — Опыт с MCP и интеграциями AI-инструментов/агентов — Async Python (asyncio, async SQLAlchemy) — SQLAlchemy и Alembic — Сообщения и очереди (RabbitMQ, Kafka, Redis) — Облачные платформы (AWS, GCP, Azure) — Кэширование (Redis, Memcached) Условия: — Полная занятость, работа в офисе в Ташкенте, Узбекистан — Официальное трудоустройство по законодательству Узбекистана — Бесплатные обеды — Компенсация спортивных и фитнес-активностей — Корпоративные мероприятия и тимбилдинги

Location: Distributed About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location: London, Munich, Amsterdam, Paris, Lisbon About the Department The Specialist Solutions Engineering team at Cloudflare is a group of trusted technical advisors who partner with our customers to solve their most complex security and performance challenges. We work hand-in-hand with the sales organization to navigate the entire customer journey, from initial discovery and solution design to proof-of-concept and implementation. We are passionate about technology and dedicated to helping our customers understand and leverage the full power of Cloudflare's global network to achieve their business critical objectives. About the Role As a Senior Solutions Engineer Specialist, you will be a pivotal technical expert and strategic advisor, focusing on the Cloudflare One product suite. You will partner with our sales team and engage directly with our customers to architect and demonstrate how our SASE platform can solve their unique security, performance, and reliability needs. Your expertise will be crucial in guiding prospects through complex technical evaluations, ensuring they have the confidence to adopt Cloudflare as a core component of their IT and security infrastructure. This role requires a blend of deep technical curiosity, strong communication skills, and a genuine passion for helping customers transform their network and security architecture. Candidates are expected to actively use AI tools in their day-to-day life for research, preparation, automation, or customer engagement. Responsibilities Serve as a trusted technical advisor to our customers, helping them architect the optimal solution for their business needs using the Cloudflare One product suite. Stay at the forefront of AI-era security challenges by developing expertise in how enterprises govern and secure AI tool adoption, including Shadow AI visibility, data loss prevention for AI applications, MCP server access controls and Agentic AI Governance. Guide qualified prospects through the solution design and proof-of-value stages, effectively demonstrating the key capabilities and value of the Cloudflare One portfolio. Collaborate with sales partners to consistently achieve pipeline generation and revenue goals. Analyze customer IT landscapes and security requirements to develop robust architectures that support their strategic objectives. Clearly articulate the benefits and technical differentiators of the Cloudflare One product portfolio against competing solutions. Enhance customer retention by identifying, capturing, and communicating product gaps or feature requests to internal product and engineering teams. Collaborate with Product Teams by being the voice of our customers by sharing insights, trends, and product gaps to help shape the product suite and solution roadmap. Qualifications Successful candidates are curious, customer-focused, and have a passion for learning. We are looking for individuals with a strong background in technical sales or systems engineering who can effectively communicate complex concepts to both technical and executive audiences. Key Qualifications: 5+ years of experience in a customer-facing technical role such as Technical Sales, Solutions/Systems Engineering, or a related field. Active adoption of the use of AI tools in professional day to day workflows and knowledge on AI security concepts relevant to enterprise customers:  Securing employee AI tool usage,  Governing AI application access, and understanding the data leakage risks posed by generative AI tools Demonstrated experience presenting technical solutions and communicating the value of network and security transformation to senior-level executives. Deep understanding of the modern cybersecurity landscape, including common threats (e.g., malware, ransomware, phishing, botnets) and mitigation strategies. Fundamental knowledge of customer network and application architectures, including hybrid environments leveraging public clouds (Azure, AWS, GCP). Solid grasp of SASE concepts and Zero Trust networking architectures. Hands-on experience with one or more of the following: Secure Web Gateway (SWG), CASB, DLP, DNS security (including DNS over HTTPS), Identity Provider (IdP) integration (SAML, OTP), and SIEM/log analytics platforms. Desirable Skills, Knowledge, and Experience: Fluent in English (written & spoken), Russian and/or Hebrew Proficiency with networking fundamentals, including routing, subnetting, VPNs, and SD-WAN concepts. Understanding of AI agentic architecture and the security requirements and challenges in implementation at scale. Familiarity with client operating system fundamentals and software distribution methods. Knowledge of the competitive landscape for CDN, WAF, DDoS mitigation, and Zero Trust Network Access (ZTNA) solutions. Direct experience with Cloudflare's Zero Trust solutions (Access, Gateway, Browser Isolation) is a significant plus. Strong project management skills, with the ability to work to deadlines and prioritize effectively among competing goals. Compensation For Spain based hires: Estimated annual salary is between €79,000 - €124,000. For Germany based hires: Estimated annual salary is between €116,000 - €182,000. For Netherlands based hires: Estimated annual salary is between €111,000 - €174,000. For Portugal based hires: Estimated annual salary is between €74,000 - €117,000. For France based hires: Estimated annual salary is between €102,000 - €161,000. This role is labelled CSP Position 3-1 and has a coefficient of 170, as per the SYNTEC Collective Bargaining Agreement. Equity This role is eligible to participate in Cloudflare's equity plan. 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: Berlin Office; Norway; Latvia; Netherlands; Hungary; Portugal; Poland; Serbia; Germany; Austria; Lithuania; Ireland; United Kingdom; Spain Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. 🎯 YOUR MAIN GOAL WILL BE TO BUILD AND OPERATE N8N’S SHARED CONTEXT INFRASTRUCTURE — OUR “COMPANY BRAIN” — SO BOTH PEOPLE AND AI AGENTS CAN RELIABLY ACCESS ACCURATE, WELL-STRUCTURED, AND APPROPRIATELY GOVERNED KNOWLEDGE ACROSS THE COMPANY. To make that happen, you’ll shape how our knowledge is structured, contributed, accessed, and maintained as we build the context layer powering n8n’s agentic future: DESIGN OUR INFORMATION ARCHITECTURE - Define the taxonomy, structure, contributor guidelines, and templates that turn fragmented company knowledge into reliable, reusable context. - Establish standards that make knowledge easy to navigate, maintain, and use without creating duplication or another layer of content sprawl. - Evolve these standards as our functions, knowledge sources, and agentic use cases grow. ONBOARD & ENABLE TEAMS - Onboard functions to the company brain and train designated champions to structure and maintain their own knowledge over time. - Give non-technical contributors the guidance, templates, and support they need to contribute high-quality context independently. - Partner with the Internal AI Enablement Lead to develop a shared network of champions who help scale strong knowledge practices across n8n. OPERATE OUR CONTEXT PLATFORM - Configure and operate ingestion from qualitative sources such as Slack, Gong, Drive, and Notion using our context platform’s tooling. - Own day-to-day platform configuration and basic troubleshooting, escalating genuine engineering challenges to our Automation team or vendor when needed. - Partner with IT, Security, and Legal to define requirements for how people and AI agents access sensitive company knowledge. BUILD FOR LONG-TERM TRUST & REUSE - Keep content structures, contributor guidelines, and knowledge freshness current as n8n and the platform evolve. - Work with functions to ensure the company brain becomes a trusted source of context rather than another parallel knowledge repository. - Provide product feedback to our context platform vendor and anticipate shared context patterns and capabilities that future agents will need. REQUIREMENTS MUST-HAVES - 🗂️ Information architecture: You have proven experience designing structured content or knowledge programs at scale, including taxonomies, style guides, contributor guidelines, templates, or information architecture. - 🧠 Knowledge systems experience: You’ve worked hands-on with knowledge or context systems and understand what it takes to turn fragmented qualitative information into something others can reliably use. - ⚙️ SaaS platform fluency: You’re comfortable configuring and operating SaaS knowledge or context platforms, working with APIs and integrations, and independently troubleshooting basic issues. - 🎓 Stakeholder enablement: You have a track record of training non-technical stakeholders and enabling them to confidently maintain high-quality content themselves over the long term. - 🔐 Governance collaboration: You’re comfortable partnering with IT, Security, and Legal on access requirements and compliance-sensitive data flows without needing to own the underlying technical architecture. - ✍️ Communication: You have strong written and verbal communication skills and can set a clear quality bar for how company knowledge is structured, documented, and shared. NICE-TO-HAVES - 🤖 Context platforms: You’re familiar with Qontext.ai http://Qontext.ai or a comparable agent-context platform. - 🔌 MCP: You have experience with or a strong understanding of Model Context Protocol (MCP). - 🏷️ Knowledge governance: You have a background in knowledge management, metadata, or data governance. Why join us? At n8n, you’ll have the opportunity to shape how an entire company’s knowledge becomes usable — not only by people, but by the AI agents increasingly working alongside them. You’ll build a capability we don’t have today and help establish the context layer that future agentic initiatives across n8n will depend on. You’ll have real ownership over how company knowledge is structured, governed, and maintained, while working closely with teams across IT, Security, Legal, Data, and AI & Automation. You’ll also have the support of a strong technical team and vendor partner, so your focus can stay on creating a trusted, scalable knowledge system rather than building every piece of infrastructure from scratch. As n8n grows, you’ll help turn fragmented knowledge into a shared company brain that teams can contribute to confidently and agents can depend on reliably. Sound like a challenge you’re excited to take on? Apply now — and help us build the context layer for the future of automation. n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.

Требуется инженер для разработки обвязки ИИ-агентов с опытом программирования на Python или TypeScript не менее двух лет. Кандидат должен владеть работой с LLM API, такими как Claude и OpenAI, включая использование инструментов, формирование структурированных ответов и стриминг. Важно понимание агентных паттернов, включая цикл агента, вызов инструментов, управление контекстом и памятью. Опыт с MCP, LangGraph, Agent SDK или собственными оркестраторами будет преимуществом. Необходимо писать надёжный код с обработкой ошибок, ретраями и логированием. В обязанности входит проектирование и разработка инструментов, оркестрации, памяти и песочниц для ИИ-агентов, интеграция агентов с клиентскими системами, такими как 1С, CRM и документооборот, а также настройка мониторинга, трассировки и контроля стоимости запросов. Работа предполагает сотрудничество с командой evals для повышения качества агентов. Предлагается участие в проектах по ИИ и корпоративным системам для крупных компаний Казахстана, гибридный формат работы с офисом в Астане, официальное трудоустройство, доступ к современным ИИ-моделям и инструментам, а также возможность влиять на архитектуру и продукт.

Location: SF Bay Area Workplace: Hybrid ABOUT THE ROLE We’re looking for an experienced software engineer to help drive and evolve our data and AI security product. Our technology is new and rapidly evolving: you’ll be an early contributor with a substantial impact on the architecture and be solving multiple exciting technical challenges! WHAT YOU'LL DO - You'll design and implement highly scalable and fault-tolerant solutions to protect enterprise data across public clouds (e.g., AWS, GCP, Azure), SaaS applications, and AI agents. - You'll build security capabilities that provide visibility into and control over how AI agents discover, access, process, and share sensitive enterprise data. - You'll solve real-world scaling problems that require thorough performance analysis and troubleshooting skills. - You'll work with a modern and constantly evolving microservices-based software stack that includes Go, Kubernetes, Bigtable, BigQuery, Spanner, Redis, Docker, and more. - You'll write robust, secure-by-design software that must withstand real-world attacks while processing untrusted data and communicating with hundreds of thousands of endpoints over the internet. WHO YOU ARE - Proven Expertise: You have 5-8 yrs of industry experience in building high-scale security products. Experience in data security is highly preferred. - AI Agents and Agentic Security: You have experience building AI agents, agentic applications, or security solutions for AI agents. Familiarity with agent frameworks, tool calling, MCP, and securing agent access to enterprise data is highly preferred. - Cloud and SaaS Development: You have extensive experience developing distributed application software for public clouds (AWS, GCP, Azure) or SaaS applications. - Data Integration at Scale: You are skilled in integrating and ingesting large-scale data from third-party SaaS, PaaS, or IaaS APIs. - Programming Skills: You have extensive experience developing enterprise-scale applications, preferably in Go. Alternatively, you are proficient in Python, Java, or Rust. - Database Proficiency: Familiarity with GCP Bigtable, BigQuery, or graph databases such as Neo4j or AWS Neptune is a plus. - Performance Optimization: You have expertise in profiling and optimizing distributed code that interacts with large databases and streaming platforms. - API and Microservices Development: You are experienced in designing and implementing RESTful APIs, with hands-on knowledge of microservices and Kubernetes. - Communication Skills: You have excellent verbal and written communication skills in English and are comfortable collaborating frequently with distributed teams across Europe, India, and the US. Joining Cyberhaven means joining the team building Data Security for the Agentic Enterprise. Traditional tools fall short. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context, so protection moves with the way people actually work, not against it. AI Changed Work. We Protect It. Backed by $250M from leading investors like Khosla and Redpoint, our team includes leaders who built industry-defining technologies at CrowdStrike, Palo Alto Networks, Meta, Google, and more. This role lets you shape the future of data security, working alongside people driven to protect workflows, not just data, for customers who cannot afford to slow down to stay safe. AI Tools Disclosure: As part of Cyberhaven's hiring process, we use recruiting tools that include AI-powered features to help with tasks like scheduling, note-taking, workflow automation, and other recruiting activities ("AI Tools"). The AI Tools may process information you provide during the application and interview process. When AI-assisted interview note taking is used, candidates are notified in advance and have the option to opt out of the AI-assisted interview note taking. Cyberhaven is committed to creating a diverse environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Location: Bangalore Workplace: Hybrid ABOUT THE ROLE We’re looking for an experienced Senior Software Engineer with 5+ years of experience to help build and evolve our data and AI security product. You’ll work on scalable backend systems that protect enterprise data across cloud environments, SaaS applications, and AI agents. As an early contributor, you’ll have the opportunity to influence technical decisions and solve complex engineering challenges at scale. WHAT YOU’LL DO - Design and build highly scalable, reliable, and fault-tolerant backend systems to protect enterprise data across public clouds (AWS, GCP, Azure), SaaS applications, and AI agents. - Develop security capabilities that provide visibility and control over how AI agents access, process, and share sensitive enterprise data. - Build and optimize distributed services that process large volumes of data with high performance and reliability. - Work with a modern microservices-based stack including Go, Kubernetes, Bigtable, BigQuery, Spanner, Redis, and Docker. - Write secure, production-ready code and troubleshoot complex performance and scalability challenges. - Collaborate with engineering teams to contribute to technical design and architecture decisions. WHO YOU ARE - You have 5+ years of software engineering experience building scalable backend systems and distributed applications. - You have experience developing cloud-native or SaaS applications, preferably in security or data protection. - You have experience with AI agents, agentic applications, or AI security, including familiarity with agent frameworks, tool calling, or MCP. - You have experience integrating and ingesting large-scale data from third-party SaaS, PaaS, or IaaS APIs. - You have strong programming skills in Go, Python, Java, or Rust, with Go preferred. - You have hands-on experience with microservices, RESTful APIs, Kubernetes, and public cloud platforms. - You are familiar with distributed databases such as Bigtable, BigQuery, Spanner, Redis, or graph databases. - You have strong debugging, performance optimization, and problem-solving skills, with the ability to independently own and deliver technical solutions. - You communicate effectively and collaborate well with distributed teams. Joining Cyberhaven means joining the team building Data Security for the Agentic Enterprise. Traditional tools fall short. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context, so protection moves with the way people actually work, not against it. AI Changed Work. We Protect It. Backed by $250M from leading investors like Khosla and Redpoint, our team includes leaders who built industry-defining technologies at CrowdStrike, Palo Alto Networks, Meta, Google, and more. This role lets you shape the future of data security, working alongside people driven to protect workflows, not just data, for customers who cannot afford to slow down to stay safe. AI Tools Disclosure: As part of Cyberhaven's hiring process, we use recruiting tools that include AI-powered features to help with tasks like scheduling, note-taking, workflow automation, and other recruiting activities ("AI Tools"). The AI Tools may process information you provide during the application and interview process. When AI-assisted interview note taking is used, candidates are notified in advance and have the option to opt out of the AI-assisted interview note taking. Cyberhaven is committed to creating a diverse environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Location: Sunnyvale, CA; United States - Remote Workplace: remote We have an opportunity for an organized undergraduate student to join our IT and Security team as an AI & Operations Intern, and we’re looking for a candidate who is available to start immediately.   Our Intern will have an opportunity to accelerate their personal and professional growth through a professional learning environment.   About You Under the direction of our VP of IT and Security, our Intern will add value and contribute to key IT and Security projects.   Duration:   We anticipate this position will work 40 hours per week and can be based in our Sunnyvale, CA office or remotely in the US. What You'll Do (aka Responsibilities) Claude Skill Development Design, build, and test Claude skills (SKILL.md) for IT and Security workflows, including writing skill descriptions, step-by-step instructions, and prompt logic that integrates with Azul's connected MCP servers. AI Agent Design and Deployment Assist in scoping, building, and iterating on AI agents that automate repetitive IT and Security tasks, including tool selection, prompt engineering, and testing against real-world scenarios. MCP Connector Integration and Testing Configure and validate MCP connector integrations (Slack, Atlassian, Asana, M365, Salesforce) within Claude, documenting tool behavior and flagging gaps or security considerations. Security Operations Support Support the Security team with log review, alert triage, and incident documentation across Okta, Microsoft Purview, and Defender, following established investigation playbooks. IT Operations and Helpdesk Assistance Assist with hardware procurement tracking, onboarding/offboarding tasks, Jamf device management, and SaaS access requests under the direction of the IT Operations team. Documentation and Knowledge Base Maintenance Create and maintain internal documentation for AI tools, security procedures, and IT runbooks in Confluence, ensuring accuracy and accessibility for team members. What You'll Bring (Education, Skills, Qualifications) Education: Currently enrolled in an Undergraduate degree program majoring in Engineering, Information Technology, Physics or appropriate degree with a minimum overall GPA of 3.4 Excellent organizational and time-management skills Able to effectively manage competing priorities Excellent written and verbal communication skills Additional Details Start date: Immediate - available to start right away Duration:  8-12 weeks Weekly hours:  40 Location:  Sunnyvale, CA or Remote, US We offer compensation where you’ll be rewarded based on your performance and recognized for the value you bring to the business.  The hourly pay for this job is $25.00.  Individual hourly pay is determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.

Location: Remote, Worldwide Workplace: remote About Distru Distru is the #1 ERP in the cannabis industry with $15B in sales processed through our platform. We've built a battle-tested ERP and B2B eCommerce platform that powers inventory, manufacturing, sales, and logistics, and we're now building AI infrastructure on top of it to give commercial businesses their all-in-one AI stack. We're growing and profitable, with 5/5 stars on Glassdoor. Our investors include Felicis Ventures, Global Founders Capital, Poseidon Asset Management, and Village Global, who have funded companies such as Shopify, Cruise, HelloFresh, Facebook, Slack, and Opendoor. Get to know the team, our culture and our full benefits at distru.com/careers! The Role AI has hit an inflection point in model capability for enterprise work, and AI assistants like Claude, Codex, and Grok are seeing record adoption in the workplace. We believe the system of record has never been more valuable, because it's where the data AI acts on gets consolidated and organized. So we're building Distru headless-first: unified access to ERP data, deep MCP and embedded AI assistant integrations, agents embedded in Distru, and a seamless experience between the ERP and the AI tools our customers already use. The AI space moves fast and the specifics will change, so this vision is something you'll mold. As our first VP of Product, you'll own: Product direction: strategy across Distru ERP, Distru Commerce, Order Agent, Distru Analytics, and our AI product suite, with accountability to revenue & growth AI product suite: the foundations that make Distru an all-in-one AI stack, including the unified data layer, agent builder, workflow builder, MCP, and the headless experience AI vision and evangelism: keeping Distru ahead of the curve on AI, finding where it creates product-market fit and new market opportunities, and championing that vision with the team, customers, and the market Product org: growing the product team from 4 to 8+, structured to serve existing ERP and Commerce customers while building new AI-first product lines Product timeline: the company's source of truth for what's shipping and when AI-first product process: how the team plans, specs, designs, and ships with AI And more… You'll report to the CEO and work closely with the VP of Engineering, Head of Sales, Head of Go-to-Market, and the product team. You'll have a long-tenured team of craftspeople around the existing product, and a fast-moving AI team experimenting at the frontier. There's a lot of autonomy and room to bring new methods, and we welcome wild AI-forward ideas. What you'll do Product strategy Deliver a quarterly strategy review to the exec team: market landscape, ERP and AI sequencing, a 1-year roadmap, metrics, and resourcing asks Own the product timeline and keep the company and technical teams aligned on it Shape our data infrastructure (StarRocks, BigQuery, Postgres) with engineering so it serves internal and external AI use cases AI vision and evangelism Track new models, AI tools, and competitor moves, and turn them into a point of view on where Distru should play next Find product-market fit for our AI products and size the new markets AI opens up, testing bets with customers before we commit the roadmap Evangelize our AI vision inside and outside the company: rally the team, equip GTM with the story, and show customers and the industry what an AI-first ERP can do Team leadership Own the product hiring pipeline, set the hiring bar, and find creative ways to bring in top talent Manage and coach the product team, including hard feedback, performance plans, and exits when needed Set PRD standards, review PRDs, designs, and mockups, and lead the team's adoption of AI-first product processes Cross-functional leadership Set the operating cadence with engineering: planning, roadmap reviews, and a clear split where product owns the what and engineering owns the how Work with GTM on launches, feature enablement, and AI-forward content, and make sure our MCP and API docs and knowledge base are high quality Run the feedback loop from customers, CS, and Sales, build relationships with key customers, and track feature adoption in a way the whole company can see What success looks like at 6 months You've run your first quarterly strategy review, and the exec team has signed off on a 1-year roadmap tied to revenue targets You've made your first product hires, at a hiring bar you've set and written down You've shipped a core piece of the headless AI suite, and its adoption and revenue impact are tracked in a dashboard the whole company uses What we look for AI fluency For every AI role, we look for three things: Tool fluency: you personally build with AI tools. You go beyond prompting and have built your own skills, agents, workflows, or prototypes. Process fluency: you've set AI-first processes for a product team, and you have a point of view on how to evaluate AI fluency when hiring a PM. Build fluency: you know how to evaluate an AI workflow in production, with evals, observability, and feedback loops that make agents better over time. You use AI tools daily and can tell us specifically where your fluency is strong and where you're still building it. Must have 10+ years in product management, including 4+ leading product teams Product leadership: you've built and run a product org, including hiring, coaching, and making hard people calls, and you've led a product into new markets or major new product directions AI products in production: you've built and shipped AI product lines such as MCPs, Agent Builders, Workflows, Copilots, etc… that are used in production Technical depth: you know the modern SaaS and AI stack, including infrastructure, data, AI models, and full-stack development, and the production concerns that come with it: reliability, observability, permissions, and durable workflow execution Outcome orientation: you measure the impact of product decisions by their revenue impact Hands-on: you still do the work: PRDs, tools, details. You can sit with engineers without translating through a layer Strong signal Experience in ERP, accounting, cannabis, or supply chain software You've taken an AI product from zero to revenue You've led product at a B2B SaaS company at a similar stage You've been a founder How we work We love building with AI. Trying new models the week they drop, building agents for fun, and forming strong opinions on what works. We invest in it with company-wide AI growth with classes and workshops, AI demo days, AI hackathons, and access to best-in-class models and tools. Product owns outcomes, not output. You measure product by adoption and revenue, and you hold the team to the same bar. Taste and conviction beat consensus. You make opinionated calls on what we build, and you grow that taste across the product team. Product owns the what, engineering owns the how. You hold a high technical bar without doing engineering's job. You'll build on what we've learned. You'll have access to the team's combined AI knowledge and the processes and skills we've built. For the full picture of our culture and who thrives here, see distru.com/careers . Benefits Our careers page is the best way to get to know us: the full benefits, our yearly offsites, who thrives here, and what the team says about working at Distru. Here are a few highlights (exact benefits vary by country and employment type): Fully remote across 4 continents Employee-friendly option terms: after 2 years, a 10-year window to exercise if you leave 18 days PTO + 11 holidays (sick days don't count toward PTO) Medical, dental, vision + 401(k) for US employees The best AI tools available and a generous AI stipend for everything else Yearly in-person team offsites Interview process Application questions: three short questions on something you've built with AI, an AI capability you've shipped, and the product teams you've led Leadership interview (60 min): your background, how you lead, hire, and manage product teams, and a briefing on the role AI product-market fit (60 min): your view of AI product-market fit for Distru, plus a show and tell of products and mockups you've built Co-building session (90 min): build a working prototype of a feature live with AI, alongside our design and product team Technical leadership (60 min): how you work with engineering, what makes an MCP and headless suite defensible, and how product improves agents over time Take-home: Headless AI Product Suite (4–8 hours, then a 60 min presentation): define Distru's headless AI product suite and present it live Meet the team (four 45 min calls): calls with both co-founders, a reverse AMA with GTM, and an AMA with the product team References and offer Distru was formed by an environment of mutual respect and trust made up by people working together without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by law. We believe that diversity and inclusion among our team members is critical to our success and we proactively strive to recruit, develop and retain the best and brightest people from the most diverse candidate pools we can find all over the world. Where you land in the range depends on your experience and skills. The role also includes equity.

Задачи: — Владение поддержкой QuickMail и Mailflow, включая работу с help desk, проверку состояния системы, тестирование новых релизов и проведение еженедельных командных встреч. — Обработка и приоритизация запросов в Help Scout, диагностика и решение проблем клиентов. — Мониторинг и анализ состояния системы через Support Dashboard, расследование и устранение проблем. — Обработка предупреждений о мошенничестве и отключение аккаунтов злоумышленников. — Проведение звонков с клиентами, установление контакта и помощь в успешном использовании продукта. — Обновление changelog и справочных материалов на основе новых релизов и запросов клиентов. — Сбор и передача обратной связи от клиентов команде, работа с отзывами и кейс-стади. — Улучшение AI-агента поддержки: проверка ответов, исправление документации, взаимодействие с клиентами при ошибках. — Написание и поддержка автоматизированных тестов для проверки стабильности продукта. — Использование интеграций (Helpscout, GitHub, Postmark и др.) для анализа поддержки и выявления направлений улучшения. — Контроль релизов: тестирование новых функций на staging, оценка влияния на пользователей, оформление баг-репортов. — Управление критическими инцидентами: подтверждение проблем, оповещение команды и клиентов, обновление статуса, проведение ретроспектив. — Ведение еженедельных командных встреч, обновление статусов и KPI. Требования: — Отличные коммуникативные навыки, умение быстро устанавливать контакт с клиентами. — Способность ясно и кратко излагать информацию как внешне, так и внутри команды. — Умение работать с минимальными инструкциями, приоритизировать задачи и самостоятельно доводить их до конца. — Комфортное владение видеоинструментами (Zoom, Meet, Loom). — Надежность, ответственность, умение работать в условиях давления и быстро адаптироваться к изменениям. — Высокий эмоциональный интеллект, умение не принимать критику на личный счет и эффективно общаться. — Готовность работать с графиком, пересекающимся с часовыми поясами Восточного побережья США и Великобритании. Будет плюсом: — Опыт работы с клиентами или объяснение, почему вы подходите на эту роль. — Знания в области deliverability и LinkedIn outreach, включая Warmup, DNS, inbox rotation, DKIM, SPF, настройку Outlook и Gmail. — Опыт работы с агентскими настройками, рабочими пространствами, гостевыми аккаунтами и покупками почтовых ящиков. — Навыки работы с данными, умение извлекать статистику из Help Scout и MCP. — Умение замечать довольных клиентов и вовремя запрашивать отзывы и кейс-стади. Условия: — Полная или частичная занятость. — Зарплата от 2500 до 4000 долларов США в месяц в зависимости от опыта и местоположения. — Для сотрудников из США работа по контракту независимого подрядчика (1099). — Гибкий график с возможностью компенсировать личные занятия. — Удаленная работа в распределенной команде. Контакт для отклика и подача заявки по ссылке: https://remoteOK.com/remote-jobs/remote-technical-customer-support-quickmail-1137506

Location: Lisbon, Portugal Joom is a global cross-border marketplace where millions can find anything they want at fair prices. Joom helps consumers to make shopping easy and entertaining and provides access to interesting and unique goods from around the world. Joom is one of the key businesses of Joom Group, an international group of tech-centric group of e-commerce companies founded in 2016 in Latvia. Joom Group also includes other businesses: JoomPro, the first and only end-to-end cross-border B2B marketplace; JoomPulse, an AI analytics tool for Mercado Livre sellers; and Onfy, a pharmaceutical marketplace in Germany. Joom Group has offices in Latvia, China, Germany, and Brazil, with its headquarters in Lisbon, Portugal. We work as one international team, sharing knowledge and collaborating across countries, businesses and products. We’re looking for an analyst for Order Experience – the area responsible for the user experience from the moment an order is placed: payment and the user’s journey in the app after purchase. Here, analytics directly affects both the user experience and the business economics: how easy it is to pay for a purchase, how quickly a customer’s issue gets resolved, and how much that resolution costs the company. You’ll work with the Product, Payments, Billing, and Support teams: together with managers, engineers, support specialists, and the finance team, you’ll identify opportunities for improvement, test hypotheses, and see them through to implementation. To do this, we have a mature internal A/B testing platform, a set of MCP tools and AI agents for analytical tasks, high-quality data in BigQuery and Spark, and transparent data preparation processes built on Airflow and dbt. This role is a great fit for someone who enjoys proactively proposing changes, taking part in setting priorities, and seeing the results of their work in the product and in business metrics. Responsibilities Improving checkout and the post-purchase experience. Identifying the reasons that prevent users from completing payment, and testing hypotheses that make this journey simpler Developing AI support. Working with the team to improve AI Chat: finding scenarios for automation, and assessing the quality of user problem resolution and the impact on the business Improving the support contact experience. Researching the user journey from ticket creation to problem resolution, agent performance, and refund decision-making Increasing operational efficiency. Forecasting support workload, improving the automatic refund model, and finding opportunities to reduce costs while maintaining service quality Designing and analyzing A/B tests. Helping teams choose metrics and experiment designs, interpret results, and automate analysis. Developing the metrics system. Making payments, billing, and support metrics clear and useful for decision-making, and investigating changes and anomalies Influencing team priorities. Identifying growth opportunities, estimating the potential impact of initiatives, and helping decide where it’s worth investing time Enabling teams to work with data independently. Preparing data for AI tools and automating repetitive analysis so that colleagues can answer basic questions on their own Requirements Strong SQL and Python skills for data analysis and automation A solid understanding of mathematical statistics and hands-on experience with A/B testing – from forming a hypothesis to drawing conclusions and making recommendations Experience applying AI in analytical work: the ability to integrate it into everyday tasks, verify its outputs, and find new opportunities for automation Independence and an interest in the business: the ability to dig into a problem, propose hypotheses, and connect analysis results to a specific decision The ability to explain complex topics clearly to colleagues with different backgrounds — from engineers to support, finance, and legal specialists The ability to manage work for multiple stakeholders: making priorities transparent, agreeing on scope and timelines, and justifiably deprioritizing less important tasks Preferred Experience in e-commerce, payments, support, or operations automation Building your own AI tools and agents for data analysis We offer Compensation package: base salary and performance-based bonuses Office-first: flexible hours with a possibility to work remotely 52 days per year Care & Wellbeing: health insurance (including dental care) for employees and their children, daily meal allowance, and 100% paid sick leave Relocation Support: full assistance for a smooth relocation for the employees and their family AI-first approach: licenses and access to a wide range of AI tools Team & Growth: collaboration with colleagues across Portugal, Brazil, Latvia and China, with opportunities for promotions, professional trainings, and English & Portuguese courses Community & Engagement: annual team building activities, knowledge-sharing workshops, and a strong sense of team work Before applying for the above position please review our Candidate Privacy Notice here . By responding to the vacancy, you acknowledge that you have read our Privacy notice.

Location: Kuala Lumpur, Malaysia; Indonesia; Singapore Workplace: fully We're Osome - an international fintech startup making the lives of entrepreneurs easier. We help thousands of businesses kick admin, accounting and bookkeeping out of their day-to-day, so they can spend more time on what's important to them. We've developed a unique solution that combines SaaS with a human-in-the-loop approach to provide full-fledged services in real-time. We’re experiencing rapid growth in both client base and team, which now comprises around 500 people across our offices worldwide. As we continue to scale, we’re looking for more bright minds who are excited to make a real impact by solving complex problems. What to expect: Intelligence builds the AI capabilities no single team at Osome should carry alone, and helps every other team ship AI well. It works in three modes. It owns cross-cutting capability. It enables product teams by pairing with their engineers, so the pattern transfers and the team runs it afterwards. It incubates only by exception: building inside another team's area when that team has no capacity, always with a written hand-back plan. This is a hands-on PM role. You'll find problems by talking to end users, dig into the data in BigQuery and Postgres to prioritise, prototype cheaply before committing engineering effort, and ship small fixes yourself. You'll also be the team's main liaison with Operations. At a glance You'd own: client and agent assistants (e.g. Maria, our client-facing bot, and the workflows it runs), document and accounting intelligence (e.g. document recognition, AI accounts review, our XBRL agent), and the shared AI foundation (evaluation and safety, memory, Osome MCP and model choices). You'd work with: five engineers, plus shared design and an analyst. Product teams across Osome and our operations teams are your customers. The problem to solve: AI is spreading across our teams faster than shared standards are. Your job is to stop every team reinventing evaluation, safety and memory, while our core AI products keep improving quarter on quarter. What you'll do: Own the Intelligence roadmap, OKRs and delivery, with two or three big bets each quarter. You make the prioritisation calls, own the business outcome behind the backlog, and write the release notes when things ship. Set the evaluation bar for AI across Osome: eval datasets, confidence thresholds, human-review sampling and go/no-go gates. With our Security team, set the safety and data-handling bar for AI across Osome: escalation rules, pre-action checks on agents, fail-open vs fail-closed behaviour, privacy and retention, client data isolation, and provider governance (e.g. zero data retention agreements). Define the success metrics for each AI product before it ships, then keep checking the data yourself after launch to see whether it's working. Brief the analyst on what to build, and review the result. Use that evidence to make model and provider calls, e.g. benchmark a new model against our own labelled documents before switching. Break epics into clear stories and tasks that engineers can pick up without a meeting. Pair with product teams' engineers to build AI features, and define what "successfully handed over" means. Be the team's liaison with Operations: run training and feedback rounds, collect baseline data, and drive adoption until the AI version beats the manual process. Run a small research track: test new techniques and approaches (e.g. retrieval, memory or agent patterns) on our own problems, and write up what we should adopt and what we should skip. Represent this team's priorities to senior stakeholders. As the team grows, mentor other PMs and help manage them. Who you are: Evaluated against our PM capability framework. At the Senior PM level, that means: Strategic impact: you can define and drive a strategy spanning 12 months or more for a platform-style team whose customers are other teams, tied to a company-level goal such as gross margin. Domain ownership: you own the OKRs, roadmap and business outcome of a complex, ambiguous, cross-functional area. You understand applied LLM/ML products deeply (evaluation, retrieval, memory, agent safety), and can become credible in our accounting and operations domain within two quarters. Collaboration: you drive high adoption of new tools with operations teams, including the processes needed to run them. You build consensus among senior leaders with conflicting goals, and you can say no while leaving the stakeholder feeling heard. Problem-solving: you map ambiguous, system-level problems, and know when a rule, a classifier or an LLM is the right tool. Execution: you reliably ship complex, cross-functional launches involving Operations and other product teams. You prototype to de-risk before committing engineering time, and you spot risks early. AI-literacy: hands-on well beyond prompting. You build prototypes and ship small PRs with AI coding tools, build eval datasets and run model experiments, read traces, and judge where models fail. Leadership: you shape direction across teams you don't manage, improve how the team works, and are ready to mentor at least one other PM as a player-coach. What you bring AI/ML features shipped to production, with quality measured after launch (accuracy, coverage, deflection). Experience building evaluation datasets and running model experiments: thresholds, go/no-go gates, human-in-the-loop decisions, and reading traces in an observability tool (we use Langfuse) to see where models fail. Experience shipping AI features that handle sensitive or financial data, and deciding when they should escalate to a human or stop. Daily use of AI coding tools (e.g. Claude Code, Codex, Cursor) to read code and ship small changes. Strong SQL. You can pick the right metrics for a product and explain what you need to an analyst. Data modelling is not required. Experience working directly with operations teams: running training, collecting feedback, and proving time saved against a manual baseline. A track record of good calls under ambiguity, and of checking afterwards whether they were right. (Nice to have) Setting company-wide safety and data-handling rules for AI: fail-open vs fail-closed policies, privacy and retention, and client data isolation, including knowing when a new AI vendor needs a security review before it sees any data. (Nice to have) Bookkeeping or accounting literacy: enough double-entry, chart-of-accounts and GST/VAT knowledge to judge whether an AI accounts review or document check is right. Either a qualification or hands-on bookkeeping experience counts. (Nice to have) Document AI/OCR in production: classifying or extracting invoices, bank statements and receipts, and the trade-offs between coverage, accuracy, confidence thresholds and cost. (Nice to have) Agentic systems or MCP in production: agents or tools that take real actions, with permissions, human approval steps and multi-step evaluation. Our Benefits Multi-cultural environment to enhance your global perspective. Learning opportunities and mentorship from peers and leaders. Flexible working arrangement; Hybrid working arrangement An agile working model focused on goals and performance. Equal Opportunity Statement At OSOME, creating a culture where individuals of all backgrounds feel comfortable really matters. Everyone who applies will receive fair consideration for employment. We do not discriminate based upon race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying. We want to ensure that we represent the diversity of talent in the society we live in today. If you have any accessibility requirements that would make you more comfortable during the application and interview process, please let us know so that we can support you.

Требования: — Коммерческий опыт Java + Spring Boot и Python + FastAPI. — Опыт разработки REST API. — Практический опыт с LLM-приложениями: RAG, embeddings, поиск, контекст, интеграция моделей. — Понимание MCP и опыт интеграции инструментов/сервисов в AI-сценарии. — PostgreSQL. — Важно: нужен не просто опыт вызова API модели или учебный проект, а практический опыт проектирования и разработки AI/LLM-сервисов. — Будет плюсом: LangChain, Pydantic. — Семантический или гибридный поиск. — MCP-сервисы / агентные LLM-системы, оценка качества ответов LLM. — Работа с DOCX, PDF, Excel / OOXML / Apache POI. — Опыт с корпоративными или локально развернутыми LLM. — Подойдет инженер, который одинаково уверенно чувствует себя в Java/Spring Boot и Python/FastAPI, а AI/LLM-задачи делал руками, не только на уровне экспериментов.

Кто мы и что строим: Flowwow — международный маркетплейс подарков. Под ним работает Data Platform, построенная с нуля: lakehouse на Apache Iceberg + Trino, Spark для тяжёлых вычислений, CDC-пайплайны на Kafka/Debezium, всё в Kubernetes. Собственный код: Data Vault — моделирование хранилища как код, обвязка Airflow с собственными операторами и хуками, lineage и инструменты наблюдаемости, AI-слой с агентами на LangGraph + MCP для расследования инцидентов и анализа качества данных. Почему эта роль интересная: Позиция Senior Data Engineer с уклоном в платформенную разработку. Проектирование инструментов для ускорения написания пайплайнов, работа с lakehouse-стеком на глубоком уровне: оптимизация Trino-запросов, maintenance Iceberg-таблиц, эволюция схем, REST-каталог. AI-native команда, ежедневное использование Claude Code и аналогичных инструментов, построение harness-систем вокруг LLM. Задачи: — Развивать ядро платформы: Data Vault, обвязка Airflow, lineage-инструменты, проектировать API и нести за них ответственность. — Писать библиотеки и фреймворки на Python: клиенты к источникам, инструменты тестирования пайплайнов, обёртки над инфраструктурой. — Работать с lakehouse: Iceberg maintenance, оптимизация layout таблиц, тюнинг Trino, Spark-джобы. — Строить интеграции с источниками: OLTP-базы, REST/gRPC API, Kafka, файловые хранилища, SaaS-системы, проектировать унифицированные интерфейсы. — Внедрять AI в инженерные процессы: агенты для расследования инцидентов, ассистенты для DAG'ов и code review. — Развивать агентную инфраструктуру (LangGraph, MCP). — Участвовать в архитектурных решениях: выбор технологий, дизайн интерфейсов, best practices. — Делать code review и менторить коллег. Требования: — Опыт от 5 лет в data engineering или backend-разработке с сильным дата-уклоном, опыт эксплуатации production-систем. — Python — главное требование. — Уровень senior: ООП, проектирование API, типизация, тесты, переиспользуемые компоненты. — Практический опыт с lakehouse-стеком: Apache Iceberg (или Delta/Hudi), понимание отличий lakehouse от классического DWH. — Опыт с Trino или другим MPP-движком: архитектура, оптимизация, коннекторы. — Глубокие знания Apache Airflow: внутреннее устройство, собственные операторы и хуки. — Опыт с Apache Spark: PySpark, Spark SQL. — Продвинутый SQL: оконные функции, CTE, оптимизация, работа с большими объёмами. — Уверенное владение Git, CI/CD. — Будет плюсом: опыт разработки внутренних платформенных инструментов, AI-native подход, Kubernetes, Helm, CDC (Debezium, Kafka Connect), знание форматов хранения Parquet, опыт с системами контроля доступа к данным (OPA, row-level security, маскирование). Условия: — Полная занятость. — Трудовой договор. — График 5/2. — Удалённый формат работы. — Уровень дохода обсуждается на этапах найма. Дополнительно: — ДМС со стоматологией или компенсация на медобслуживание, сервис психологической поддержки. — Компенсация расходов на спорт и спортивное оборудование. — Компенсация стоимости техники для работы. — Оплата обучения, конференций, митапов. — Корпоративная программа лояльности с персональными скидками и предложениями от партнёров. Наши ценности: — Забота и любовь к продукту. — Развитие и рост. — Культура взаимопомощи. — Открытость к изменениям. — Благотворительность и социальная ответственность.

Location: Paris; Amsterdam; Munich; London; Berlin Workplace: Remote ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it. You will lead the team building our serverless containers product: the way developers run AI apps, MCP servers, APIs, and managed workers on our cloud without thinking about servers. Push a container, get an endpoint, scale from zero to thousands of instances and back down — across CPU and GPU. On a hyperscaler, the serverless layer is a product someone else built. Here you own it end to end: the scheduler that decides where a container lands, the routing path a request takes, the machinery that turns a scaled-to-zero service into a warm instance before a customer notices. All of it runs on metal, network, and datacenters we own. That tension is the product: scale-to-zero economics with cold starts in milliseconds, autoscaling that absorbs a launch spike without a config change, GPUs scheduled onto containers the way other platforms schedule CPU. The customers betting on this layer are the developers building the next generation of AI software on European infrastructure. WHAT YOU WILL DO - Own the container platform end to end: image delivery, placement, request routing, scale-up, scale-to-zero — across CPU and GPU. - Make cold starts a solved problem: snapshotting, prewarming, image-layer caching, whatever it takes for scale-from-zero to feel instant. - Treat AI workloads as the normal case: GPU-backed containers, streaming responses, long-lived connections, MCP servers that cost almost nothing while idle. - Write Go alongside your team and own the architecture and the hardest implementation decisions. - Grow the engineers, not just the software — set the standard for ownership and coach people past their comfort zone. - Own people management for the team: hiring, performance, growth paths, and honest feedback. - Partner with Product Managers to turn platform decisions into a product developers want to deploy on. WHAT WE'RE LOOKING FOR - 3+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - You have shipped production systems in Go. Not dabbled. Shipped. - You have built container or workload platforms — orchestration, scheduling, isolation, request routing — not just deployed onto someone else's serverless platform. - Deep Linux: namespaces, cgroups, image layers, page cache — comfortable well below the application layer. - Multi-tenancy instincts: density, isolation, and fairness when hundreds of customers share one fleet. - Significant experience building complex backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Задачи: — Разработка и развитие микросервисов, их взаимодействия по REST и через Kafka; — участие в проектировании решений вместе с командой; — рефакторинг, повышение производительности и отказоустойчивости сервиса рассылок; — разработка логики конструктора писем и персонализированных коммуникаций, включая AI-функции формирования персонализированных писем; — разработка асинхронных микросервисов на FastAPI и обработка событий Kafka: гарантии доставки, идемпотентность и повторная обработка; — использование кодовых агентов, проверка и доработка сгенерированного кода; — написание unit- и интеграционных тестов, code review, документирование решений; — работа с логами и метриками и диагностика ошибок; — декомпозиция и оценка задач, сопровождение до внедрения и взаимодействие с аналитиками, QA и frontend-разработчиками. Требования: — От 3 лет коммерческой разработки на Python и профильное IT-образование; — уверенное знание Python и asyncio, опыт с FastAPI, REST API и микросервисной архитектурой; — уверенный SQL и PostgreSQL, включая транзакции, индексы и планы запросов; — опыт работы с ORM; — практический опыт с Redis, Docker и Apache Kafka в production, а также с логами, метриками и диагностикой production-инцидентов; — ежедневная работа с AI-кодовым агентом; — умение декомпозировать задачи, управлять контекстом, использовать AGENTS.md, rules, скиллы и MCP-инструменты; — умение объяснять и проверять сгенерированный код, исправлять ошибки и доводить решение до production. Условия: — формат работы: офис или гибрид, Москва.

Задачи: — Вести проекты в Jira + Confluence — Составлять и актуализировать роадмапы и спринты — Ежедневно распределять задачи и отслеживать сроки их выполнения — Поддерживать эффективную коммуникацию внутри команды — Своевременно информировать руководство о возникающих трудностях — Вести записи созвонов и составлять follow-up'ы — Следить за корректностью отчётности — Контролировать соблюдение сотрудниками внутренних правил при работе с сервисами и мессенджерами — Быть полностью вовлечённым в проект Требования: — Опыт автоматизации задач и процессов (боты, n8n и т.д.) — Опыт работы с современными ИИ-инструментами (CLI-агенты, MCP и т.д.) — Навык настройки Jira + Confluence — Опыт составления роадмапов и спринтов — Опыт работы с трудными заказчиками, умение находить компромиссы — Умение аргументированно доносить свою позицию — Знание игровой индустрии и понимание процессов создания игр — Опыт работы в Slack, Notion, Miro, Google Docs — Стабильный быстрый интернет Условия: — Доход: от 35 000 до 45 000 ₽ — Занятость: парт-тайм, 4 часа в день — Формат: удалённая работа — График: гибкий — Рост: возможность профессионального роста

Ищем Senior GenAI-разработчика на проект крупной компании из сферы добывающей промышленности. Основная задача - разработка и внедрение корпоративных GenAI-решений: AI-агентов, мультиагентных систем, RAG-конвейеров и автоматизаций в закрытом защищённом контуре. Задачи: — Разработка AI-агентов и субагентов с использованием tool-calling — Построение мультиагентных систем и управление цепочками вызовов — Создание автоматизаций и workflow в n8n, Flowise, Dify, Langflow или аналогичных платформах — Разработка бизнес-логики и кастомных функций на JavaScript, TypeScript и Python — Построение RAG-конвейеров: подготовка данных, embeddings, поиск и работа с векторными базами — Интеграция с внутренними сервисами и витринами данных через REST API и OAuth2 — Парсинг, сбор, нормализация и трансформация данных из внешних источников — Проектирование промптов для суммаризации и генерации структурированных отчётов — Развёртывание и эксплуатация open-source и on-prem LLM в закрытом корпоративном контуре — Работа со структурированными данными, PostgreSQL и JSON — Участие в анализе и формализации бизнес-требований Требования: — Опыт коммерческой разработки GenAI-решений на уровне Senior — Уверенное владение JavaScript, TypeScript и Python — Практический опыт создания AI-агентов и мультиагентных систем — Опыт хотя бы с одним из стеков: LangChain / LangGraph, LlamaIndex, Semantic Kernel, CrewAI / AutoGen, n8n / Flowise / Dify / Langflow — Опыт разработки RAG-решений и работы с векторными хранилищами: PGVector, Qdrant, Milvus или аналогами — Уверенная работа с PostgreSQL, JSON, REST API и OAuth2 — Опыт работы с LLM и prompt engineering — Опыт развёртывания локальных моделей в закрытом контуре — Готовность вести разработку и эксплуатацию решения в ОС Windows — Понимание принципов защиты чувствительных и корпоративных данных Будет преимуществом: — Опыт работы с MCP — Model Context Protocol — Разработка кастомных нод и sub-workflows в n8n — React — GraphQL — FastAPI — Опыт работы с веб-поиском, парсингом и внешними API — Опыт участия в корпоративных или промышленных проектах