Вакансии

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We are seeking a Software Engineer to help us build the next version of media web experience. In this role, you will define the work on the technical components of how we deliver video and audio content at Reddit. Specifically, you will focus on our web media player and the APIs that power it, drawing on industry patterns from top streaming platforms to build seamless, low-latency playback experiences and interactive tools for creators and users alike. Key Responsibilities Work cross-functionally with product, design, and other engineering counterparts to execute on product and business strategy and build novel products and features that our users will love. Contribute to the full development cycle: technical design, development, test, experimentation, analysis, and launch. Design and implement end-to-end fullstack solutions, optimizing web UI components for our media player (React, TypeScript) and the backend APIs (Go, Python) that power them. Move fast while balancing quality. We can’t afford extensive processes, and we also can’t afford show-stopping bugs. You’ll be reviewing code and design docs, giving feedback on product specs and mocks. Collaborate with client engineers and platform engineers to improve performance of media across Reddit to serve better content globally. Contribute to standards that improve developer workflows, recommend best practices, and help mentor junior engineers on the team to grow their technical expertise. Qualifications BS degree in Computer Science, a similar technical field of study or equivalent practical experience. 3+ years of software development experience in one or more general-purpose programming languages; Go, Python, Rust, Ruby. Proficiency in modern web development technologies (JavaScript, React, Next.js, TypeScript) and experience translating complex UI/UX designs into scalable web applications. Experienced with GraphQL, REST, HTTP, gRPC, Thrift basics, and the ability to design and implement maintainable APIs. Strong organizational skills, the ability to prioritize tasks and to deliver projects on schedule. Excellent communication skills. You collaborate effectively with teams in a fully remote environment and discuss complex topics with technical and non-technical audiences. Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $165,000 — $229,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Paris ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As an Applied AI Engineer, your mission is to make Mistral AI-native from the inside. You lead the design and delivery of production-grade AI systems in rapid cycles, building the iconic use case for multiple department (eg: GTM, HR, Engineering, Finance, ect) in your portfolio. You sit where product, engineering and the business overlap, turning advanced technology into real-world solutions that move a metric. You translate complex, often ambiguous business requirements into engineered solutions that work at scale. You act as the technical lead for your departments and contribute as an Individual contributor you guide the technical choices, build the solution end to end, drive adoption, and keep improving it. Your goal is to build clients trust, and deliver high ROI solutions, not a hit-and-run POC. WHAT YOU WILL DO - Run discovery with department heads and key users, map their workflows, and turn ambiguous needs into a prioritized use-case backlog with clear expected value. - Deliver end to end: design and ship production-grade full-stack apps (Python/FastAPI, React) and AI systems, from scoping through deployment and adoption. - Encode business rules, KPIs and ROI metrics as durable datalake assets and app logic, so your departments run on trustworthy, observable data. - Dogfood the latest Mistral products as a first internal user, and turn what you learn into credible product feedback that shapes the roadmap. - Own architecture for your surface: keep it scalable, secure and observable, with a high bar on clean code. - Spot patterns across departments and lift one-off solutions into reusable building blocks. WHAT WE'RE LOOKING FOR - At least 3 years building and deploying production AI software. - Strong full-stack engineer: Python/TypeScript, scalable backends (FastAPI/Node), and enough frontend (React/Vue) to ship a usable app yourself. - Hands-on with modern GenAI use cases: RAG, agents, workflows, orchestration and evaluation. - Strong command of vibe-coding tools, paired with genuine care for clean code and architecture: speed without slop. - Strong ownership and a bias for delivery. This is made for high-velocity engineers who already have experience. - Fluent in AI-native tools (Slack, Linear, etc.). - Passionate about solving customer problems. Here, your customers are Mistral's own teams. - Excellent communication in fluent English: you can explain a technical idea to a lawyer, a marketer and a staff engineer in the same afternoon. NICE TO HAVE - Exposure to Legal, Public Affairs, Marketing or Compute/Infra domains, or a track record of getting fluent in an unfamiliar domain fast. - Data engineering or analytics experience (warehouse modeling, dbt, dashboards). - Contributions to open-source projects, especially around LLMs. - A builder's instinct for internal tooling and platform reuse. 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.

Location: Barcelona, Spain; Madrid, Spain About Workato Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com . Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles . We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care . That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Workato is looking for an Engineering Manager to lead the ChatBots and AI team within our Platform organization. This is a high-ownership role for someone who thrives in ambiguity: you turn unclear requirements into clear execution plans, make confident decisions with incomplete information, and keep both the team and leadership aligned. The team is fully remote and international - you'll build the processes and culture that make it work at pace. About the Team The ChatBots and AI team's mission is to deliver AI agents to end users. We own the runtime and integration layer - conversation storage, API design, streaming, and integrations with external interfaces like Slack and other applications. The team is made up of Senior and Staff engineers working in Ruby/Rails and Go on a modern stack: PostgreSQL, Kafka, Redis, Kubernetes, and AWS. You'll collaborate with dedicated QA, SRE, and UX/UI teams, as well as engineering teams across the broader organization. Workato has a strong cross-functional culture - your team won't work in isolation. What You'll Do Delivery Partner with Product Managers and stakeholders to scope projects, set timelines, and define what success looks like Plan and track execution across quarters and sprints; deliver on schedule without compromising quality Identify blockers early, resolve them decisively, and escalate when escalation is the right call Balance feature work against internal investments - AI-SDLC, CI/CD, platform upgrades, and technical debt Team Manage, mentor, and grow a team of Senior and Staff engineers Own hiring, onboarding, and performance management Design team processes that fit a distributed, asynchronous environment - and evolve them as the team and company change Apply AI tooling to how the team works, not just what it builds Technical Ownership Participate in architecture and design decisions as a technical peer to your engineers Make trade-off calls on scope, approach, and sequencing - and be accountable for them Understand the system deeply enough to allocate the team's capacity where it matters most Communication Keep leadership informed on progress, risks, and blockers with clarity and without spin Build working relationships with peer leads across engineering and product Represent your team's priorities and constraints in cross-team planning What We're Looking For 5+ years managing engineering teams, including Senior and Staff-level individual contributors Senior engineer-level technical depth - you can read the code, challenge a design, and hold your own in an architecture discussion Hands-on background in backend engineering; experience with Ruby, Go, or comparable languages and distributed systems Demonstrated ability to operate under ambiguity: defining direction where none exists, and committing to decisions before all the information is available Track record of shipping complex software on schedule in a fast-moving environment Experience managing a fully remote, distributed team across multiple time zones Strong written communication - in an async environment, writing is the primary management tool Nice to Have Experience building AI-powered products - agents, LLM pipelines, or orchestration systems Background in platform, integration, or developer-facing infrastructure Experience scaling a team through periods of rapid growth Familiarity with enterprise SaaS or automation platforms (REQ ID: 2941)

Location: Poland Workplace: Remote HI THERE!👋🏻 WE’RE TOOPLOOX 💎, A SOLVD INC. COMPANY We create AI-powered products and services that make a real difference. Our team of nearly 200 specialists - including a 40+ person R&D team with many PhDs - has pioneered AI solutions across industries from healthcare to e-commerce. We’ve published research in top-tier venues like NeurIPS and ICML, while delivering real-world applications that help our clients innovate and scale.   WHAT YOU WILL DO: - Collaborate with cross-functional teams to design and build AI Agentic solutions. - Contribute to defining technical requirements and implementing features across the software lifecycle - from proof of concept through implementation to evaluation and production. - Take ownership of assigned tasks and deliver high-quality, maintainable code. - Manage backend tasks while contributing to frontend development. - Stay informed about trends and advancements in AI and related fields, continuously learning and integrating new knowledge. - Employ a pragmatic, evaluation-driven approach to adopting innovative AI solutions.   EXPERIENCE AND SKILLS YOU NEED TO JOIN US: - Experience in full-stack development using mainly NodeJS (with TypeScript). - At least 1 year of experience in AI Engineering role. - Versatile in technology use, comfortable working across backend and frontend tasks. - Track record in staying current with AI and Agentic technologies, including best practices and architecture. - Openness to client collaboration, fostering clear communication and effective partnership. - Strong commitment to learning new technologies and swiftly adapting to new products and APIs. - Understanding of Retrieval-Augmented Generation (RAG) and its applications. - Familiarity with Multi-Agents concept, tools usage and MCP Servers. - Hands-on experience with LLM APIs/SDKs (e.g., OpenAI, Anthropic). - Knowledge of LLM orchestration and frameworks like Langchain or LlamaIndex, with practical implementation experience. - Understanding of prompt design principles and an ability to create effective prompts. - Experience configuring services on cloud platforms (e.g. AWS, Azure, GCP). - Basic experience with CI/CD pipelines and DevOps best practices. - Competence in REST API usage and efficient database integration. - Fluency in English language.   IT WOULD BE GREAT IF YOU ALSO HAVE: - Basic knowledge of machine learning principles. - Understanding Python source code. - Experience with React. - Experience with model fine-tuning and distillation. - Familiarity with LLM evaluation. - Experience with Model Context Protocol (MCP). - Experience with graph databases. - Familiarity with other programming languages and frameworks. - Familiarity with Voice Agents concepts and related frameworks e.g. Pipecat HOW WE WORK: At Tooploox 💎, you have the flexibility to choose your working hours ⏰ and location 📍. While we value remote work, we also believe in building relationships 🤝and invite you to join us in our Warsaw and Wrocław offices 🏢. Enjoy a relaxed atmosphere 🍃 and try some “home-made” pizza 🍕 from our office pizza oven. We love having pets 🐶 in the office, so feel free to bring yours along.😁 Join us and shape the future of AI while working the way you like!

О проекте Работа над платформой по автоматизации управления кадровой рекламой: организации, трекинга и контроля размещения как онлайн, так и оффлайн рекламы — от подачи заявки до финального закрытия кампании. Задачи: — Проектирование и реализация backend-логики платформы. — Разработка и документирование REST API для фронтенда. — Разработка интерфейса веб-приложения, взаимодействие с REST API бэкенда. — Автоматизация бизнес-процессов и авторизация пользователей. — Организация централизованного хранения артефактов (файлы, документы). — Интеграция с Яндекс.Метрикой. — Поддержка многопользовательских сценариев (гибкое управление ролями, кампаниями). — Участие в проектировании архитектуры платформы и UI/UX, коммуникация с дизайнерами (Figma). — Кроссбраузерная верстка, адаптация под различные устройства. — Разработка системы отчётности и визуализации метрик. — Тестирование и отладка фронта. — Опыт работы с CI/CD (GitLab CI / GitHub Actions). Требования: — Опыт коммерческой разработки от 3 лет, уверенный опыт full-stack разработки. — Опыт backend-разработки на Python. — Знания SQL, опыт работы с PostgreSQL. — Навыки проектирования REST API. — Знание современного Vue. — Опыт интеграции с backend через REST API. — Опыт адаптивной и кроссбраузерной верстки. — Навыки работы с системами контроля версий Git. — Умение работать с Figma. — Опыт ревью кода и написания тестов (включая unit-тесты). — Ответственность, самостоятельность, внимание к безопасности и качеству кода. — Аккуратность, умение работать как самостоятельно, так и в команде. Условия: — Формат: возможен как удаленный формат, так и в офисе. — Загрузка: полноценный рабочий день, оформление по ТК РФ. — Современный инструментальный стек. — Работа в команде профессионалов, участие в проектировании продукта.

Задачи: — full-stack разработка с использованием Node.js и React Требования: — уверенное владение backend: Node.js, Express, Sequelize — уверенное владение frontend: React, Vite, Tailwind CSS, Zustand, Axios — опыт работы с базами данных MySQL и PostgreSQL, включая транзакции, блокировки, конкурентный доступ, оптимизацию сложных SQL-запросов — понимание race conditions и проблем конкурентности — опыт работы с real-time технологиями: WebSocket, Socket.IO, Centrifugo — навыки работы с инфраструктурой и DevOps: Docker, настройка Nginx, Redis, RabbitMQ, очереди задач, Elasticsearch, Kibana, Prometheus, Grafana — понимание CDN, принципов защиты от DDoS на уровнях L3/L7, работы proxy и reverse proxy — умение работать с API и интеграциями, включая недокументированные API, OAuth, Telegram Bot API, TDLib — опыт использования AI-инструментов Claude и ChatGPT для анализа, написания кода, рефакторинга, отладки и поиска решений — понимание вопросов безопасности: SQL Injection, проверка типов и входных данных, race conditions, базовое понимание криптографии (RSA, SHA, хеширование), обфускация, browser/device fingerprinting — умение проектировать архитектуру высоконагруженных систем с учетом масштабирования, отказоустойчивости, конкурентной обработки данных, взаимодействия сервисов, очередей, БД, кеша и real-time компонентов Будет плюсом: — базовое понимание теории вероятностей — понимание принципов работы blockchain и основных сетей: Bitcoin, TON, Ethereum/ERC, TRON — опыт работы с нестандартными API и интеграциями

Location: Vienna, Austria Workplace: Hybrid ABOUT SENTRY Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. ABOUT THE ROLE Sentry's SDKs instrument dozens of platforms and our ingest pipeline takes in billions of events every day. The Telemetry Experience team owns what happens next: the product surfaces and APIs where that telemetry turns into something a developer can actually debug with. As a Senior Software Engineer on Telemetry Experience, you'll own that experience across the sentry.io http://sentry.io product - Python/Django and Postgres on the backend, React and TypeScript on the frontend. You'll work upstream with our SDK teams on what gets sent and with our ingest teams on how it arrives, then own the part customers actually touch: the APIs, the workflows, and the interfaces where it all lands. Your job is to make that feel native to every developer who uses it, whether they ship a backend service, a mobile app, or a game. IN THIS ROLE YOU WILL - Own projects end to end. Take a problem from a rough customer complaint through scoping, design, implementation across the stack, rollout, and measurement. You'll write the design doc, cut the work into shippable pieces, and stay with it until the numbers move - Work across the full stack of the Sentry monolith. React and TypeScript in the browser, Django and Postgres behind the API. Most projects here touch both, and the interesting decisions live at the seam - Partner closely with SDK and ingest teams. Telemetry arrives exactly as the SDKs send it and as the pipeline shapes it. You'll shape those contracts together with the engineers who own them, rather than working around what shows up - Collaborate daily with product managers, designers, and other product engineers. You'll bring the technical perspective that makes a design better, explain constraints in terms of what they cost the user, and sweat the details other people skip: empty states, error messages, loading behavior, the edge case that only bites 2% of accounts YOU’LL LOVE THIS JOB IF YOU - You'd rather own an outcome than a ticket. You take ambiguous problems, decide what to build, drive it across team boundaries, and follow through after launch. Nobody has to hand you a spec - You're obsessed with making an experience smooth. Friction offends you. You notice the extra click, the confusing label, the query that takes 400ms too long - and you fix them instead of filing them - You solve problems for customers, not for the codebase. Sentry's users are developers, so you can read their bug reports, sit in their tooling, and tell the difference between what they asked for and what they need - You communicate well in writing. Working across SDK teams, ingest teams, product, and design in a distributed company means your docs, PR descriptions, and updates do a lot of the work - You like being full-stack. You don't need a handoff to change an API and the component that calls it, and you enjoy holding the whole path from event payload to rendered pixel in your head QUALIFICATIONS - 5+ years of professional experience building and shipping full-stack web applications - Strong experience with React and TypeScript, and with Python (Django or similar) backed by a relational database such as PostgreSQL - depth in one side and real competence in the other is fine - A track record of driving non-trivial projects end to end, including the parts that require getting other teams to agree with you - Excellent written and spoken English communication skills - Experience leveraging AI-powered development tools to enhance productivity and code quality BONUS POINTS - Familiarity with the application monitoring and observability space - Experience building developer-facing products, SDKs, or public APIs - Experience with high-volume data stores or streaming systems (ClickHouse, Kafka) - A track record of contributing to open-source projects We are obliged by law to quote the minimum wage of EUR 60,844,-- gross per year for this position, in accordance with the respective collective agreement (IT-KV). The salary that Sentry offers you is adjusted to the current market situation and will be above the IT-KV. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs. EQUAL OPPORTUNITY AT SENTRY Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible. If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io. Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.

Ключевая миссия CTO: построить инженерную организацию нового поколения. Ожидается построение AI Native Engineering Organization, внедрение AI PDLC как основного процесса разработки, организация работы автономных Tiny Teams, создание культуры постоянных экспериментов и быстрого вывода гипотез в продукт, широкое использование AI для автоматизации инженерной деятельности, сокращение времени полного цикла Idea → Prototype → MVP → Production, формирование инженерной культуры с акцентом на скорость обучения и внедрения инноваций. Задачи: — Определять и реализовывать технологическую стратегию направления совместно с Product Lead и бизнесом; — Отвечать за разработку и развитие ключевых продуктов направления: мобильного приложения нового поколения, AI-помощника, платформы персонализированного риск-профиля и интеллектуальных сервисов повышения качества и продолжительности жизни; — Формировать AI Native инженерную организацию для высокой скорости вывода новых продуктов и функций; — Внедрять современные практики AI PDLC на всех этапах жизненного цикла AI-продуктов; — Организовывать эффективный процесс исследований (R&D), быстрого прототипирования и проверки продуктовых гипотез; — Руководить несколькими автономными инженерными командами (Tiny Teams), обеспечивая их эффективность и ответственность; — Развивать практики агентной разработки (Agentic AI), AI Coding и использование AI-инструментов для автоматизации инженерной деятельности; — Формировать масштабируемую архитектуру AI-first продуктов для быстрого внедрения новых моделей, сервисов и сценариев; — Управлять архитектурой решений, техническим долгом и технологическими рисками; — Обеспечивать надежность, масштабируемость, наблюдаемость и безопасность сервисов промышленного уровня; — Развивать инженерную культуру, основанную на автоматизации, непрерывном обучении, экспериментах и улучшении процессов; — Формировать технологический roadmap направления и обеспечивать достижение бизнес- и продуктовых целей. Требования: — Опыт руководства несколькими инженерными командами разработки от 2 лет; — Опыт создания и развития современных цифровых продуктов с высокой скоростью поставки изменений; — Опыт формирования и реализации технологической стратегии продукта; — Практический опыт построения архитектуры мобильных и backend-продуктов промышленного уровня; — Опыт управления архитектурой, качеством разработки и техническим долгом; — Практический опыт внедрения AI PDLC или аналогичных процессов разработки AI-продуктов; — Глубокое понимание жизненного цикла AI-продуктов: Data → Prompt → Model → Evaluation → Production → Monitoring → Continuous Improvement; — Понимание современных подходов к разработке LLM-приложений, Agentic AI, Multi-Agent Systems, Tool Calling, MCP, Workflow Orchestration и Retrieval-Augmented Generation (RAG); — Практический опыт применения современных AI-инструментов разработки (Cursor, Claude Code, GitHub Copilot и др.); — Опыт построения процессов R&D, быстрого прототипирования и проверки продуктовых гипотез; — Опыт организации работы автономных инженерных команд (Tiny Teams); — Опыт разработки мобильных приложений и высоконагруженных backend-сервисов; — Понимание принципов построения персонализированных цифровых сервисов и работы с пользовательскими данными; — Понимание современных практик DevSecOps, CI/CD, Observability и Platform Engineering; — Опыт эффективного взаимодействия с продуктовой командой и бизнесом. Будет преимуществом: — Опыт создания AI-first продуктов на базе современных LLM; — Опыт построения агентных платформ или мультиагентных систем; — Опыт внедрения AI Native Engineering в инженерной организации; — Опыт организации процессов AI Quality Engineering, Continuous Evaluation и AI Observability; — Опыт создания персонализированных рекомендательных систем; — Опыт разработки AI Copilot, AI Assistant или AI Agent продуктов; — Опыт работы в MedTech, HealthTech, Digital Health или Wellness; — Опыт создания мобильных consumer-продуктов с высокой ежедневной активностью пользователей (DAU/MAU); — Понимание современных подходов Product Discovery, Experiment Driven Development и Lean Startup. Условия: — Формат: Гибридный (от 2-х дней в неделю, м. Технопарк); — Бесплатный доступ к телемедицине и очным приемам в частных клиниках (включая стоматологию и сессии с психологами); — Условия ипотечного кредитования от Сбербанка; — Индивидуальный план развития; — Обучение: английский с корпоративным преподавателем, скидки на курсы в Skyeng, компенсация обучения от ведущих платформ; — Официальное оформление, стабильные выплаты, оплата больничного и отпуска, современная техника; — Частичная компенсация спортивного абонемента, бесплатные занятия сквошем и футболом.

Ключевая миссия CTO: - Построение AI Native Engineering Organization; - Внедрение AI PDLC как основного процесса разработки; - Организация работы автономных Tiny Teams; - Создание культуры постоянных экспериментов и быстрого вывода гипотез в продукт; - Широкое использование AI для автоматизации инженерной деятельности; - Сокращение времени прохождения полного цикла Idea → Prototype → MVP → Production; - Формирование инженерной культуры, где скорость обучения и внедрения инноваций становится ключевым конкурентным преимуществом. Задачи: - Определять и реализовывать технологическую стратегию направления совместно с Product Lead и бизнесом; - Отвечать за разработку и развитие ключевых продуктов направления: мобильного приложения нового поколения, AI-помощника, платформы персонализированного риск-профиля и интеллектуальных сервисов повышения качества и продолжительности жизни; - Формировать AI Native инженерную организацию, обеспечивающую высокую скорость вывода новых продуктов и функций; - Внедрять современные практики AI PDLC на всех этапах жизненного цикла AI-продуктов — от идеи и исследований до промышленной эксплуатации; - Организовывать эффективный процесс исследований (R&D), быстрого прототипирования и проверки продуктовых гипотез; - Руководить несколькими автономными инженерными командами (Tiny Teams), обеспечивая их высокую эффективность и ответственность за конечный результат; - Развивать практики агентной разработки (Agentic AI), AI Coding и использования AI-инструментов для автоматизации инженерной деятельности; - Формировать масштабируемую архитектуру AI-first продуктов, обеспечивающую быстрое внедрение новых моделей, сервисов и пользовательских сценариев; - Управлять архитектурой решений, техническим долгом и технологическими рисками; - Обеспечивать надежность, масштабируемость, наблюдаемость и безопасность сервисов промышленного уровня; - Развивать инженерную культуру, основанную на автоматизации, непрерывном обучении, экспериментах и постоянном улучшении процессов; - Формировать технологический roadmap направления и обеспечивать достижение бизнес- и продуктовых целей. Требования: - Опыт руководства несколькими инженерными командами разработки от 2 лет; - Опыт создания и развития современных цифровых продуктов с высокой скоростью поставки изменений; - Опыт формирования и реализации технологической стратегии продукта; - Практический опыт построения архитектуры мобильных и backend-продуктов промышленного уровня; - Опыт управления архитектурой, качеством разработки и техническим долгом; - Практический опыт внедрения AI PDLC или аналогичных процессов разработки AI-продуктов; - Глубокое понимание жизненного цикла AI-продуктов: Data → Prompt → Model → Evaluation → Production → Monitoring → Continuous Improvement; - Понимание современных подходов к разработке LLM-приложений, Agentic AI, Multi-Agent Systems, Tool Calling, MCP, Workflow Orchestration и Retrieval-Augmented Generation (RAG); - Практический опыт применения современных AI-инструментов разработки (Cursor, Claude Code, GitHub Copilot и др.); - Опыт построения процессов R&D, быстрого прототипирования и проверки продуктовых гипотез; - Опыт организации работы автономных инженерных команд (Tiny Teams); - Опыт разработки мобильных приложений и высоконагруженных backend-сервисов; - Понимание принципов построения персонализированных цифровых сервисов и работы с пользовательскими данными; - Понимание современных практик DevSecOps, CI/CD, Observability и Platform Engineering; - Опыт эффективного взаимодействия с продуктовой командой и бизнесом. Преимущества: - Опыт создания AI-first продуктов на базе современных LLM; - Опыт построения агентных платформ или мультиагентных систем; - Опыт внедрения AI Native Engineering в инженерной организации; - Опыт организации процессов AI Quality Engineering, Continuous Evaluation и AI Observability; - Опыт создания персонализированных рекомендательных систем; - Опыт разработки AI Copilot, AI Assistant или AI Agent продуктов; - Опыт работы в MedTech, HealthTech, Digital Health или Wellness; - Опыт создания мобильных consumer-продуктов с высокой ежедневной активностью пользователей (DAU/MAU); - Понимание современных подходов Product Discovery, Experiment Driven Development и Lean Startup. Условия: - Формат: гибридный (от 2-х дней в неделю, м. Технопарк); - Бесплатный доступ к телемедицине и очным приемам в частных клиниках (включая стоматологию и сессии с психологами); - Условия ипотечного кредитования от Сбербанка; - Индивидуальный план развития; - Обучение английскому языку с корпоративным преподавателем, скидки на курсы в Skyeng, компенсация обучения от ведущих платформ; - Официальное оформление, стабильные выплаты, оплата больничного и отпуска, современная техника; - Частичная компенсация спортивного абонемента, бесплатные занятия сквошем и футболом.

Задачи: — Разрабатывать и поддерживать нативные приложения для Android. — Создавать пользовательские интерфейсы по дизайн-макетам. — Интегрировать приложения с бэкенд-сервисами и REST API. — Участвовать в проектировании архитектуры и code review. — Оптимизировать производительность, стабильность и качество кода. — Взаимодействовать с backend-разработчиками, QA и дизайнерами. Требования: — Коммерческий опыт Android-разработки от 2 лет. — Уверенное знание Kotlin (Java — будет плюсом). — Хорошее знание Android SDK и жизненного цикла компонентов Android. — Опыт разработки UI с Jetpack Compose и/или классическими View. — Работа с Kotlin Coroutines и Kotlin Flow. — Понимание многопоточности, управления состоянием и принципов SOLID. — Опыт с архитектурой Data / Domain / Presentation, MVVM, MVI и другими паттернами презентационного уровня. — Опыт интеграции REST API. — Работа с локальными БД: SQLite, Room. — Уверенное использование Git. — Опыт с Dependency Injection: Dagger / Hilt. Будет плюсом: — Опыт с многомодульной архитектурой Android-приложений. — Написание unit- и UI-тестов. — Понимание CI/CD в мобильной разработке. — Опыт оптимизации производительности и работы с памятью.

Location: Poland; Georgia; Serbia; Bulgaria; Armenia We build cloud CPaaS/CCaaS infrastructure - the routing, messaging and real-time layer that contact centres run on. High traffic, event-driven services, and a UI that has to stay correct while thousands of live conversations move through it. We're hiring a senior engineer for a team where AI agents are part of the normal development loop, not a pilot. You'll own features end-to-end across a Go backend and a React/TypeScript frontend, and you'll be accountable for everything you ship — including the parts an agent wrote. This is not a prompt-engineering role. It's a senior engineering role where AI-assisted delivery is the default working method. Requirements What will you do at MMDSmart? Own features end-to-end across Go backend and React/TypeScript frontend; Design and develop solutions for high-load and distributed production systems; Use AI coding agents as an integral part of your everyday development workflow; Guide AI agents, review and verify their output, and take ownership of the final result; Build and evolve backend services, APIs, frontend functionality, and external integrations; Investigate complex production issues and drive them to resolution; Contribute to architecture decisions, technical discussions, and system improvements; Help improve our codebase and development practices to make AI-assisted engineering more effective. You are a perfect match if you have: 5+ years of professional software engineering experience and strong Senior-level engineering fundamentals; Strong hands-on production experience with Go - 4 years of experience; Practical experience with React and/or TypeScript; you don’t need to be a frontend expert, but you should be comfortable working with frontend code; Hands-on experience with high-load and distributed production systems; Experience designing, building, and debugging production services and APIs; Hands-on experience with AI coding tools such as Claude Code, Cursor, Windsurf, Copilot, or similar - beyond simple autocomplete; Ability to use AI to work effectively across different parts of the stack while critically reviewing and verifying its output; Strong engineering judgement, ownership, and ability to make technical decisions independently. Our Tech Stack: Backend: Go, microservices, REST APIs, GraphQL Frontend: React, TypeScript, Zustand / Redux Toolkit, WebSocket / SSE Event-driven: Kafka, NATS / JetStream, RabbitMQ, event-driven architecture Data: PostgreSQL, Redis, MongoDB Infrastructure: GCP, Kubernetes, Docker, CI/CD, Infrastructure as Code Observability & Performance: structured logging, metrics, tracing, profiling, high-load and concurrency tooling AI Development: Claude Code, Cursor, Windsurf, Copilot and other agentic development tools Domain: CPaaS / CCaaS, messaging, voice, real-time communication, external provider integrations Will be a plus: CCaaS / CPaaS / telecom background: contact-centre routing, ACD, omnichannel messaging. Voice stack: WebRTC, SIP, media servers, or CPaaS APIs API gateway and microservices integration; GraphQL federation. Kubernetes, Docker, CI/CD ownership, infrastructure-as-code. Polyglot persistence: Redis for caching and ephemeral state, PostgreSQL where a document model is the wrong fit; plus the judgement to tell the difference. MongoDB Atlas or self-managed cluster operations. Internal tooling, evals or automation built on LLM APIs. Open-source contributions, especially in Go. What you get: An AI-first engineering environment where AI is part of real production development; The opportunity to use AI to work across the full stack and expand beyond your primary expertise; Work on high-load communication products with real business impact; A team where Senior Engineers influence technical decisions and architecture; Remote work. Benefits Why do talents choose and stay at MMDSmart? Embrace the opportunity to work in a company that cares about: Your Wellness: Access to mental health programs, comprehensive medical insurance, and a sports card*. Your Happiness: Enjoy the company of cool teammates, a friendly atmosphere, a strong mentorship, and a variety of bonuses & corporate gifts. Your Development: Benefit from free educational events & courses, and English classes with native speakers. Your Career: Focus on your professional development in a supportive environment. Work-Life Balance: Choose your working format - remote, office-based, or hybrid and engage in team-building activities. Think this role's got your name on it? Go ahead and apply, we'd love to see what you've got! Equal-Opportunity Employment We are an equal opportunity employer committed to creating a diverse and inclusive work environment. 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. *Medical Insurance and Sport Card perks are available for employees located in Bulgaria.

Location: San Francisco, CA; New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. About the Team The Infrastructure team builds and maintains the systems that power LangChain’s developer platform, including LangGraph Cloud and LangSmith. The team focuses on reliability, scalability, and developer productivity across the stack, working closely with backend, frontend, and platform engineers to ensure services are deployed, tested, and operated with confidence. About the Role We’re hiring a Software Engineer to join the Infrastructure team and own developer productivity across our LangGraph Cloud/Platform and LangSmith products. You’ll work closely with Infrastructure, Backend, and Frontend teams to ship with confidence across Kubernetes-based services, APIs, and UI flows. You’ll also help pioneer quality practices specific to LLM applications, such as prompt regression testing and evaluation suites. Location: In person 5 days/week in San Francisco, CA or New York, NY What You'll Do - Own test strategy end-to-end across APIs, services, UI, data, and infrastructure (Kubernetes, Terraform, Helm) - Stand up ephemeral test environments in Kubernetes for pull requests and release candidates; seed test data and run hermetic test suites - Shift quality earlier in CI/CD pipelines (GitHub Actions) through parallelization, caching, deterministic seeds, flake tracking, and quality gates - Build observability into testing workflows with rich failure artifacts such as logs, traces, and dashboards - Establish performance and reliability baselines for critical paths, including SLIs, SLOs, and regression detection - Partner on incident workflows by reproducing issues, adding targeted regression tests, and improving runbooks and postmortems - Write documentation including test plans, playbooks, and contributor guidelines for writing high-quality tests Example projects you might own - A pull-request ephemeral end-to-end testing harness that deploys a minimal LangSmith stack in CI and runs Playwright and API suites against seeded tenants - A k6 performance scenario that simulates multi-tenant traffic and surfaces p95/p99 latency regressions per release - A flake-budget system that automatically quarantines flaky tests, opens issues with artifacts, and tracks time-to-deflake What You'll Bring - 3+ years of experience as a software engineer or infrastructure engineer - Strong hands-on experience with Python and testing frameworks such as pytest - Experience working with CI/CD systems (GitHub Actions preferred) and improving pipeline performance and reliability - Solid understanding of API testing, mocking/stubbing, and data setup/teardown - Comfort defining quality standards, writing test plans, and driving cross-team execution Nice to Have - Experience with load and performance testing tools such as k6 - Familiarity with observability tooling such as Datadog or OpenTelemetry - Experience testing services running on Kubernetes and containerized environments - Basic infrastructure experience with Helm, Terraform, Kubernetes networking, or secrets management - SQL fluency for validating data (Postgres, ClickHouse, BigQuery) - Familiarity with Go, Node, or React for targeted white-box tests and improving system testability Compensation - Annual salary range: $165,000- $250,000 USD COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Задачи: — Сотрудничество с бизнес-стейкхолдерами для понимания их потребностей и требований — Анализ и документирование бизнес-процессов, рабочих процессов и функциональностей систем — Проектирование и предложение технических решений, соответствующих бизнес-целям и технологической стратегии FxPro — Разработка детальных системных спецификаций, диаграмм и блок-схем для руководства разработчиками — Тесное взаимодействие с командами разработки для контроля реализации системных решений — Обеспечение бесшовной интеграции новых систем с существующей инфраструктурой и платформами Требования: — Опыт работы системным аналитиком не менее 5 лет — Экспертиза в анализе и документировании требований для backend-сервисов — Опыт создания детальных системных спецификаций, wireframes, диаграмм и блок-схем — Владение созданием комплексной технической документации — Знание системной архитектуры — Опыт работы с RESTful APIs, GraphQL и интеграцией сторонних API — Знание отраслевых стандартов и требований регуляторов — Сильные навыки решения проблем и устранения неполадок — Отличные устные и письменные коммуникативные навыки — Способность к сотрудничеству и работе в команде — Аналитическое мышление — Адаптивность к изменяющимся бизнес-требованиям — Свободное владение английским и русским языками Желательно: — Глубокие знания торговых систем — Понимание принципов UX/UI дизайна Условия: — Отличный компенсационный пакет — Медицинская страховка — Пенсионный фонд — Собственный спортзал с персональным тренером — Бесплатное ежедневное питание, закуски и напитки — Корпоративная дисконтная карта на различные товары и услуги — 21 день ежегодного отпуска и 10 дней больничных в год — Трансфер из Лимассола — Подарок на день рождения — Бонус на релокацию и поддержка в оформлении визы/разрешения на работу

Задачи: - Разрабатывать и развивать frontend на React / Next.js, реализовывать интерфейсы по Figma с TailwindCSS - Строить мультидоменную и мультивитринную архитектуру, конфигурационный подход для storefront - Интегрировать frontend с backend на Django через REST API, работать с платёжными и subscription API, webhook-события - Реализовывать ключевые страницы: Landing, Pricing, Checkout, Login, My Account; GEO-зависимый контент - Оптимизировать Core Web Vitals, обеспечивать SEO и кроссбраузерность Требования: - От 3 лет коммерческого опыта с React, уверенное знание Next.js и TypeScript, опыт с TailwindCSS - Уверенная работа с REST API, опыт интеграции frontend с backend на Django - Опыт с SSR / SSG, понимание routing и middleware в Next.js - Понимание принципов multi-tenant / multi-domain архитектуры, feature flags - Будет плюсом: интеграция с платёжными системами, recurring payments, финтех Условия: - График: 5/2 с 10 до 18, отпуск 21 день, оплачиваемый больничный - Формат работы: удалённо

Location: Remote Who we are Our mission is to bring clarity and control to the world's most complex codebases. AI is accelerating code creation, but the infrastructure to understand, oversee, and evolve that code hasn't kept pace. Sourcegraph gives engineering organizations full visibility across their systems, precise context for their agents, and the ability to execute coordinated code changes at scale. As agentic development becomes the dominant engineering paradigm, we provide the context layer teams need to take control of their codebase. With Code Search, Deep Search, MCP, and Agentic Batch Changes, we deliver on that mission today - giving engineering teams and their AI tools the cross-repo context to navigate massive codebases with confidence, and the ability to make changes across hundreds of repositories at once. Companies like Stripe, Reddit, and Leidos rely on Sourcegraph to ship faster and with higher quality. We're backed by a16z, Sequoia, and Redpoint, and proud to operate as a globally distributed team that values high agency, direct communication, and customer love. If you want to build the infrastructure that lets every engineering team - and every agent they deploy - operate on their codebase with confidence, join us. Hours & location 🌎 While we hire almost anywhere in the world, we have a preference for someone to reside in the following locations for this role. However, if you feel qualified, we welcome you to apply regardless of location. No matter what, working hours must overlap with EST for at least 20 hours/week. Preferred locations: USA Why this job is exciting Sourcegraph is at the forefront of building AI tools to solve the biggest problems in the software industry, problems that only get bigger as codebases grow and as more of the work is done by agents. The Code Understanding team owns the surfaces where that intelligence meets the developer: Deep Search , our agentic, multi-step answer engine across an enterprise's entire lineup of codebases, Query Assist , turning natural language queries into Sourcegraph query syntax, Smart Hovers , concisely summarizing symbols right where devs need it, guided diff review, and the APIs that both humans and AI agents rely on every day. Most of what makes those surfaces tick is agent engineering : a blend of software engineering, machine learning, and statistics. Agent engineering tells us which model to use and when, how to retrieve and pack context, how to measure answer quality, where to fine-tune or distill a smaller model to cut costs and latency, and how to expand a single LLM call into a reliable multi-step agent. As the staff ML and agent engineer on Code Understanding , you'll be the technical owner of it: setting the tam’s direction for models, evaluations, and agentic systems, making our products measurably better, faster, and cheaper, and raising the team's fluency in building with models. This is a staff-level role : we're hiring a technical leader, not just a strong individual contributor. The primary need is a production ML and evaluation authority who also builds production agent systems. You'll own the hardest, most ambiguous problems in this space, set standards others follow, and influence direction beyond your immediate team. You'll get the exhilarating chance to drive the vision on how we can provide the best code understanding experience on the market by combining our deterministic, large-scale systems and AI into experiences never seen before. Concretely, you'll own work like: Agentic systems. You'll design and harden the multi-step, tool-using agent loops behind current and new agentic experiences, turning research and experiments into reliable, observable, and affordable products at enterprise scale. Pragmatic use of evaluations. Crafting agentic products means needing to tell when a change actually helped, which is hard when agents keep changing and the product keeps shifting. You'll bring judgment about where evaluations earn their keep, when to use targeted smoke tests and metrics, and how to avoid noise dressed up as rigor, so we can move fast with confidence. Models: selection, upgrading, and training. You'll decide which models we run where, drive upgrades, and fine-tune our own when that's the right call. Retrieval and context engineering. You'll push on how we ground models in a customer's code - retrieval, ranking, context windows, citations - to make answers more accurate and verifiable. Cost and latency. Every surface has a per-user economic budget. You'll treat cost and latency as product features, and profile, distill, cache, and right-size models so we can ship ambitious features sustainably. You'll do this on a small, senior-leaning team that ships quickly, owns a lot of product surface, and has streamlined product management: engineers here talk to customers, frame the problem, and own it end-to-end. You'll have real agency over technical direction and a direct line to the impact of your work. 📅 Within one month, you will… Get the Code Understanding products and their model/agent pipelines running end-to-end locally, and land your first improvements to a model, prompt, retrieval path, or eval. Build a clear picture of where the AI engineering pain is, and the product surfaces most constrained by them. Get to know the team and our customers, and start forming your own opinions about where our agentic products should go next. Join the team's on-call support rotation. 📅 Within three months, you will… Own a meaningful agentic slice of the product end-to-end, driving it from problem-framing through rollout and measurement. Establish how the team ships model and prompt changes responsibly: the evals, dashboards, and guardrails that make quality and cost regressions visible before customers feel them. Begin up-leveling teammates in building with models by pairing with them, reviewing their code, and modeling good agent engineering instincts. 📅 Within six months, you will… Be the recognized technical authority for agent engineering and agentic systems on Code Understanding. You will be the person teammates, and increasingly the wider department, defer to on model, eval, and agent-design decisions. Have measurably moved the products: better answer quality, lower cost/latency, or new agentic capabilities that weren't feasible before. Be setting the direction of the team's roadmap where it intersects agents, bringing conviction, backed by evidence, about which bets are worth making, and pulling other engineers up to execute on them. About you You are a staff engineer and technical leader with hard-won skills across production machine learning, evaluation, and agent systems . This high-leverage role relies on your ability to make sound model and evaluation decisions for a fast-moving product, build the production systems around them, steer technical direction, and be a force multiplier for a talented, product-minded team. You're equally comfortable reasoning about an eval harness, a fine-tuning run, a retrieval pipeline, and the multi-step agent loop that ties them together, and you make everyone around you better at all of it. You operate at staff scope: you own the most ambiguous, highest-risk problems in your domain, go into whatever codebase a problem requires, set standards and patterns others adopt, and translate fluidly between engineering goals and business objectives. You influence direction beyond your immediate team. You lead through technical excellence and mentorship. You have personally owned a production model lifecycle. You have trained or fine-tuned at least one model and taken it from dataset construction through evaluation, production rollout, and monitoring. You can explain how you chose between training or fine-tuning and prompting or retrieval, how you chose baselines and metrics, what error analysis revealed, and how production evidence affected the next version. You build agents, fluently and opinionatedly. You've designed multi-step agentic systems and made them reliable, observable, and cost-bounded. You have a point of view on where agents shine and where deterministic code or human judgment is required. You have strong evaluation judgment. You build representative datasets, meaningful baselines, useful error taxonomies, and release criteria that connect offline measurements to production behavior. You know where rigorous evaluations earn their keep, where lightweight smoke tests or qualitative review are enough, and where a precise-looking metric is misleading. You treat cost and latency as product constraints. You make measured quality, latency, and cost tradeoffs and use the appropriate combination of model selection, prompting, retrieval, caching, distillation, and fine-tuning rather than reaching reflexively for a more complex model. You operate autonomously on ambiguous problems. Given a rough product idea, a few customer quotes, and a Slack thread, you come back with a plan, a prototype, milestones, and a point of view on tradeoffs, without it being pre-scoped. You own high-technical-risk projects end-to-end. You contribute beyond your domain. As a senior IC, you go into whatever part of the codebase a problem requires, recognize issues beyond your immediate area, and translate between engineering goals and business objectives. You up-level the people around you. You mentor by pairing on hard problems, providing substantive design and code reviews, and spreading agent engineering literacy across the team. You see investing in your teammates' growth as part of the job. You're customer and product-driven. You're comfortable on customer calls and in feedback threads, you turn raw signals into requirements, scopes, and milestones, and you push back when feedback would lead the product astray. You're pragmatic, not a perfectionist. You ship the smallest correct thing, prefer robust solutions over complicated ones, and keep a high-quality bar with simplicity. On the engineering fundamentals: You're a strong software engineer who can ship production services. You're comfortable across our stack - Go on the backend, TypeScript on the frontend, GraphQL, Postgres, Docker - or you're clearly able and eager to get there. You're fluent with agentic coding tools, and you understand and own every line it submits. You're comfortable in an async-first, multi-service, fast-paced remote environment. Nice-to-haves: You've shipped an LLM-powered or agentic developer-facing product you can speak about opinionatedly: what worked, what didn't, what you'd do differently. You've fine-tuned, distilled, or trained models to meet cost, latency, or quality targets in production. Experience with retrieval, ranking, embeddings, or search relevance. Experience working directly with enterprise customers and translating their needs into a product. Experience mentoring or up-leveling engineers, especially raising a team's agent engineering fluency. Level 📊 This job is an IC4. You can read more about our job leveling philosophy in our Handbook. Compensation 💸 We pay above-market salaries because we want to hire exceptional people who can focus on building great products, not worrying about paying bills. As an open and transparent company, our compensation philosophy and pay bands are visible to every Sourcegraph teammate, and we strive to make our approach equitable, explainable, and competitive. Your base salary is determined by the IC4 pay band for your location zone (1-4). Our pay bands are informed by market data and designed to ensure competitive compensation wherever you live. During the recruiting process, we'll discuss the range applicable to you based on job level, relevant skills, experience, qualifications, and location zone. 💰 The starting salary for the IC4 pay band in each zone is: Zone 2: $176,000 USD Zone 3: $132,000 USD Zone 4: $88,000 USD 📈 In addition to competitive cash compensation, we offer meaningful equity (because when Sourcegraph succeeds, we want you to succeed, too) and generous perks & benefits . Interview process Below is the interview process you can expect for this role (you can read more about the types of interviews in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all! We expect the interview process to take 5.5 hours in total. 👋 Introduction Stage - we have initial conversations to get to know you better… [30m] Recruiter Screen [30m] Hiring Manager Screen 🧑‍💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team, including cross-functional partners… [60m] Resume Deep Dive [60m] System Design [60m] Harden a Code Research Agent Interview [60m] Cross-functional team collaboration / Values 🎉 Final Interview Stage - we move you to our final round, where you gain a better understanding of our business and values holistically… [30] Leadership We check references and conduct your background check Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process. Learn more about us You can learn more about what it is like to work at Sourcegraph by reading our handbook . We are an ambitious team who are collectively working hard to build the most influential company in the world. You can read more about our culture , competitive compensation and benefits here. Sourcegraph is an equal opportunity workplace; we welcome people from all backgrounds. Sourcegraph participates in E-Verify for U.S. Employees.

Location: Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia If you want to build and own the systems that decide what JetBrains customers are entitled to use and bill them accurately for it, this is for you. You will focus on designing backend services, keeping complex commercial flows correct, and tackling hard distributed systems challenges on the critical path of every paid request. About JetBrains We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale. What you’ll do At JetBrains, the Cloud Platform department builds the underlying infrastructure that powers authentication, paid capabilities, usage metering, and accounting. Within this department, the Licensing & Billing team sits right at the center of our commercial model, turning what a customer buys into what they are actually allowed to use, and accounting for that consumption accurately enough to bill on. The complexity of our entitlement, quota, and metering systems continues to grow. In this role, you will own the correctness and evolution of these backend services, take full ownership of end-to-end data flows, tackle distributed consistency across unreliable upstream systems, and ensure revenue-affecting data migrations happen cleanly without taking services offline. Day to day, you will: Design, build, and operate backend services that decide what a customer is entitled to and what their usage costs. Own flows end to end, from ingesting licensing and purchase data from upstream systems to enforcing quotas and recording consumption. Evolve our domain model to handle new commercial structures, combining seat-based plans and usage-based models. Design integrations with external systems, ensuring correctness through idempotency, ordering, reconciliation, and eventual consistency. Plan and execute live data migrations using feature flags, dual writes, backfills, and verification at every stage. Build observability into our systems by defining invariants, metrics, and alerts to catch silent divergence before customers do. Design internal APIs with explicit focus on versioning, backward compatibility, and developer experience for other JetBrains teams. Improve system performance and reliability under continuous production load while decommissioning legacy subsystems. Write integration tests against real dependencies and maintain reliable test infrastructure. Investigate production incidents, find root causes, and follow through on lasting fixes. What you’ll bring An engineer’s dedication to accuracy, especially in domains where system errors have direct financial impact. Pragmatic judgment when designing distributed systems where correctness under unreliable delivery is the main constraint. A habit of trusting metrics, traces, and logs to understand production behavior rather than relying on assumptions. Comfort navigating and simplifying large existing codebases containing legacy decisions. Clear, direct communication skills to agree on API contracts across teams with different priorities. A focus on testing as an essential design tool rather than an afterthought. What you’ll need A proven track record of building and operating backend services on the JVM platform using Kotlin or Java. A solid working knowledge of relational databases, including transactions, isolation levels, locking, indexing, and live schema migrations (PostgreSQL preferred). A deep understanding of distributed systems patterns, such as idempotency, retry strategies, eventual consistency, and data reconciliation. Practical experience making live data migrations or system changes without downtime using feature flags and staged rollouts. Experience designing versioned, backward-compatible APIs for other engineering teams. Hands-on experience with event-driven architectures and message brokers like Kafka. The ability to diagnose, debug, and resolve production incidents in complex environments. Proficiency in both written and spoken English. What success looks like Success in this role means building a bulletproof entitlement and metering foundation that product teams can trust without hesitation. You will have successfully migrated live commercial systems to support new billing models without downtime or data divergence. Silent errors will be caught automatically by system invariants before affecting users, and internal teams will integrate seamlessly with your clean, versioned APIs. Why join JetBrains? Strong base salary. We offer competitive pay that reflects your skills and experience. Flexible work location. Enjoy the freedom to work from home or from the office. Remote work. Spend up to 30 days per year working remotely from abroad. Extra time off. More days to relax, recharge, and do the things you love. Medical insurance allowance. Enjoy peace of mind for you and your family Learning and development opportunities. Access to conferences, courses, and language classes. Relocation support. We help make your move as smooth and stress-free as possible. (keep if relevant for the role) Language classes. Pick up the local language or sharpen your English skills. Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays. Mental health support. To help you feel your best, we provide easy access to professional mental health services. Sports benefit. Enjoy an on-site gym or sports club stipend. Internal events. Join company-wide celebrations and team gatherings. *Some benefits may vary depending on location. #LI-KT1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.