AI-инженер (LLM, агенты, AI product) вакансии - в офисе

DeepInfra is looking for a Software Engineering Intern to design, develop, and deploy AI model inference solutions at scale.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM   This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.     ABOUT THE ROLE   You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $185,000–$315,000 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: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.   ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world.   WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement   WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production   NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 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, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 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: Baku Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Why This Role Exists Xsolla is going all-in on becoming an AI-first company, and we're not waiting for a slow rollout to get there. We're offering AI Engineer Internships in regions across the globe to help drive that shift directly, not by sitting in the back office, but by building. You'll work on two things: Internal AI initiatives – helping unlock AI tooling and integrations across Xsolla faster than our existing teams can alone. Proof-of-concept builds on our own APIs – showing our product and engineering teams what's possible when you build with AI as a core part of your workflow, not an afterthought. This isn't a shadow-and-observe internship. You'll ship code that goes to customers – internal teams or external players and game developers – working closely with senior engineers and fellow interns across our global regions. Who You'll Work With You won't be isolated on an intern-only project island. You'll work closely with senior engineers who are actively rebuilding how we write software, and you'll be part of a global cohort of interns building in parallel across our regions. That combination is the point: senior engineers give you a bar for what production-grade, customer-facing code looks like, and your fellow interns give you a peer group to trade ideas, code, and AI workflows every week. What You'll Do Partner and collaborate with senior engineers to identify where AI tooling and integrations can remove friction, and build the fix. Build applications and integrations on top of Xsolla's APIs and SDKs that show internal teams how to move faster using AI-assisted development. Ship work that matters. What you build is expected to reach real users – whether that's an internal tool an engineering team adopts or a customer-facing integration – not a throwaway exercise that gets shelved after your internship ends. Use agentic coding tools (Claude Code, Cursor, or similar) as your default way of working – not a novelty you reach for occasionally. Share what you build. We run weekly 30-second lightning-talk demos where everyone shows how they used AI to solve something that week – you'll be expected to bring something real. Work with minimal process. You'll get context, a problem, and a mentor – the rest is on you to figure out and build. Learn from and collaborate with both directions: senior engineers who'll mentor you on production-grade practices, and fellow interns across markets you'll trade ideas and code with at the weekly demos. What We're Looking For You build things because you want to, and that you already use AI to do it faster. Genuine passion for building. You have side projects, hackathon entries, open-source contributions, or something you shipped just because you were curious. You didn't need an assignment to make it happen. Real AI fluency. You've actually used tools like Claude Code, Cursor, Copilot, or similar agentic coding tools to build something – not just asked ChatGPT to explain a concept. You should be able to explain how you used AI to get there and how you confirmed it actually worked – not someone who fires off a prompt and hopes for the best. Bias toward action. Given an ambiguous problem, you start building before you ask for a spec. Comfort with developing modern full-stack solutions – we care more about how fast you learn than what you already know cold. Open to current graduate students and recent graduates of a Computer Science, Software Engineering, or related program . How to Apply Please include: A link to a GitHub profile, deployed project, or anything else you've built – the more recent and self-directed, the better. A short answer (2-3 sentences, or a 2-minute video/Loom if you'd rather show than tell) to: “What's something hard you built recently, and why did you build it?” We're not grading for correctness or polish. We're looking for whether you have a real answer, and whether it's clear you actually did the work yourself (with AI as your tool, not your ghostwriter). Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the AI-First Engineering Intern, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements     Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

— Разработка масштабной системы видеомониторинга и интеллектуальной видеоаналитики. — Техническое лидерство направления Computer Vision.

Қазақстанда алғаш рет корпоративтік IT-мамандарға арналған Vibe Coding чемпионаты өтеді. Задачи: — Жасанды интеллектке тапсырманы дұрыс қойып, алгоритмдік есептерді тиімді промпт арқылы шешу. Требования: — Қатысушылар 22 жастан асқан корпоративтік IT-мамандар болуы. — Соңғы 5 жылда спорттық бағдарламалау бойынша жарыстарға қатысу тәжірибесі болмауы тиіс. — Әр компаниядан 2 бағдарламашы қатысуы керек. Условия: — Формат: офлайн дуэльдер, Double Elimination. — Командалар саны шектеулі. — Жүлде қоры — 1 000 000 ₸. — Үздік компания AlgoBatyr Cup корпоративтік кубогына ие болады. — Өткізу мерзімі: 2 қазан — чемпионат, 3 қазан — марапаттау. — Өткізу орны: Астана қаласы. Как подать заявку: 1. cpfed.kz платформасында тіркелу. 2. Командадағы екінші қатысушының тіркелгенін тексеру. 3. AlgoBatyr тіркелу формасын толтыру және логиндерді көрсету.

Задачи: — разработка и внедрение сквозных AI-автоматизаций под задачи закупок: от ИИ-ассистентов до генераторов документов на базе LLM — быстрое прототипирование решений (no-code/low-code, API, n8n) для проверки гипотез на реальных данных с доведением до состояния «можно показать заказчику» — обработка закупочной документации спецификой 44-ФЗ / 223-ФЗ с помощью нейросетей: ТЗ, договоры, коммерческие предложения, реестры — написание промптов, шаблонов и инструкций, обеспечивающих стабильный результат при работе с неструктурированными данными (сканы, дубли) — самостоятельная аналитика данных закупок (спенд-анализ, цены, сроки) и перевод бизнес-требований в технические постановки задач — развёртывание работающих прототипов во внутренней инфраструктуре или контейнерах (Docker, VPS), базовая работа с логами и окружениями — контроль качества моделей: сбор тестовых выборок, расчёт доли корректных ответов, закладывание архитектуры с учётом ошибок LLM (human-in-the-loop) — формализация требований, защита решений перед бизнесом и передача подтверждённых прототипов команде разработки для вывода в продуктив. Требования: — практический опыт создания работающих AI-решений (не просто использование чатов), уверенное владение промпт-инжинирингом и интеграциями по API — опыт в закупках, тендерах или снабжении от 2 лет. Глубокое понимание процессов end-to-end (от потребности до приёмки) и специфики ЭТП — навык быстрой сборки автоматизаций через no-code/low-code платформы без привязанности к первому варианту решения — умение работать с «грязными» данными, выгрузками из разных систем, Excel / Google Sheets; базовый SQL для самопроверки гипотез — способность отличить работающий прототип от сырого демо: знание границ применимости LLM и того, что нельзя выпускать в эксплуатацию — базовые навыки эксплуатации: запуск сервисов в Docker/VPS, работа с секретами, чтение логов (промышленная разработка и архитектура не требуются) — системное мышление для самостоятельного поиска точек реального эффекта от внедрения AI и отсечения нерелевантных задач — сильное техписательство: умение упаковывать сложные решения в понятную бизнесу документацию, схемы и презентации — ориентация на измеримый результат: способность посчитать эффект автоматизации в часах, деньгах или доле сокращённых ошибок. Условия: — комфортный современный офис в Москве — график работы – офис — ежегодный пересмотр зарплаты, квартальная и годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте (для Junior позиций) — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера

Задачи: — разработка, обучение и оптимизация ML/AI-моделей на PyTorch и/или TensorFlow — проектирование end-to-end ML-пайплайнов — работа с LLM, NLP, Computer Vision и Generative AI — подготовка моделей к production и масштабированию — интеграция моделей с backend — оптимизация inference и производительности — построение MLOps-процессов — работа с Docker и cloud-инфраструктурой — принятие архитектурных решений и техническое руководство AI-командой Требования: — от 4 лет коммерческого опыта в Machine Learning / AI Engineering — практический опыт разработки и внедрения ML-моделей в production — уверенный Python — PyTorch и/или TensorFlow — понимание Machine Learning и Deep Learning — знание ML-метрик и методов оптимизации моделей — Docker, Git — AWS или аналогичные cloud-платформы — практический опыт с MLflow, Kubeflow, AWS SageMaker или аналогичными MLOps-инструментами — свободный английский язык Условия: — full-time — офис в Ташкенте — официальное трудоустройство по ТК Узбекистана — вилка от $3,500

Лаборатория «Космос» — российский стартап, создающий собственные программно-аппаратные продукты: от первых прототипов до готовых устройств. В портфеле два продукта: «Каспер» — робо-компьютер для обучения детей; «Света» — интерактивная светозвуковая панель для дома и различных пространств. Задачи: — исследовать новые AI-модели, сервисы и способы их применения; — решать отдельные продуктовые задачи с помощью существующих AI-технологий: исследовать рынок, выбирать решение, тестировать и собирать прототип, например, найти и интегрировать технологию для работы Каспера с произношением ребёнка; — собирать внутренние AI-инструменты для команды из готовых моделей, API и автоматизаций; — автоматизировать работу с документами, голосовыми сообщениями, ссылками, PDF и базой знаний; — создавать инструменты для работы команды с видео, изображением, музыкой, звуком и другим контентом; — проводить исследования по продуктам, технологиям, конкурентам и патентам. Требования: — очень хорошее знание современных нейросетей, основных моделей и сервисов; — постоянное отслеживание новинок и тестирование; — умение применять AI-технологии для решения задач; — API, автоматизации и базовый код важны; — опыт классической разработки будет плюсом, но не обязателен; — самостоятельность, любопытство, способность быстро проходить путь от задачи и исследования до работающего решения. Условия: — работа в офисе в Санкт-Петербурге, центр города, м. Горьковская; — оплачиваемая работа; — занятость и график обсуждаются индивидуально; — уровень вознаграждения зависит от навыков, опыта и объёма занятости.

Задачи: — Руководить командой Computer Vision Engineers — Проектировать архитектуру production AI-систем — Менторить инженеров и проводить code review — Декомпозировать задачи и контролировать качество реализации — Разрабатывать пайплайны обработки десятков и сотен RTSP-потоков — Оптимизировать инференс на GPU и CPU — Принимать ключевые технические решения — Участвовать в найме и развитии AI-команды Основной стек: Python, PyTorch, OpenCV, YOLO, RTSP, GStreamer, NVIDIA DeepStream, TensorRT, Triton Inference Server, ONNX, OpenVINO, CUDA, FastAPI/gRPC, Docker и Kubernetes. Что важно: ✅ Сильный коммерческий опыт в Computer Vision и Video Analytics ✅ Опыт технического лидерства или менторства ✅ Запуск production AI-систем ✅ Уверенное знание Python, PyTorch, OpenCV и YOLO ✅ Практический опыт с RTSP, GStreamer, DeepStream и TensorRT ✅ Оптимизация моделей через ONNX, TensorRT, OpenVINO, CUDA или Quantization ✅ Понимание высоконагруженной обработки видеопотоков ✅ Умение принимать и аргументировать архитектурные решения Будет плюсом: ➕ Triton Inference Server ➕ C++ и CUDA ➕ Kafka и потоковая обработка данных ➕ MLflow и MLOps ➕ ViT, DETR, Swin и Video Transformers ➕ VLM, RAG, LangGraph, vLLM и Function Calling ➕ Опыт найма и формирования AI-команд Предлагаем влияние на архитектуру и технологический стек, сильную инженерную команду и работу над высоконагруженной системой промышленного уровня.

Задачи: • Формировать AI-стратегию и roadmap бизнес-направления. • Находить наиболее перспективные точки применения AI. • Самостоятельно запускать первые прототипы и AI-пилоты. • Быстро проверять гипотезы и показывать первые измеримые результаты. • Создавать AI-агентов, RAG-решения и AI-автоматизации. • Формировать и приоритизировать портфель AI-инициатив. • Совместно с FDE и AI-командой доводить успешные пилоты до production и масштабирования. • Переосмысливать бизнес-процессы с учетом возможностей AI. • Работать с руководителями бизнес-направлений и защищать AI-инициативы. • Следить за развитием AI-технологий и применять новые подходы в реальных бизнес-кейсах. Требования: • 7+ лет профессионального опыта в технологиях, AI/ML, разработке продуктов или digital transformation. • Практический опыт запуска AI/ML или технологических продуктов. • Сильное понимание LLM, Generative AI, AI Agents и RAG. • Способность самостоятельно собрать работающий AI-прототип. • Product mindset и ориентация на быстрый результат. • Стратегическое мышление и способность формировать AI-roadmap. • Умение связывать технологии с конкретным бизнес-эффектом. • Опыт работы с руководителями и топ-менеджментом. • Высокая самостоятельность и ответственность за результат. AI-инструменты и технические навыки: • Практический опыт работы с OpenAI, Claude, Gemini, Llama, Qwen или аналогичными LLM. • Работа с LLM API, Prompt Engineering, Tool/Function Calling. • Создание AI-агентов с использованием LangChain, LangGraph, LlamaIndex или аналогов. • Практическое понимание RAG, embeddings, vector databases. • Использование AI coding-инструментов: Codex, Cursor, Claude Code или аналогов. • Python, REST API, SQL — на уровне, достаточном для самостоятельного создания прототипов. • Опыт работы с n8n, Make или другими инструментами автоматизации. • Понимание принципов работы и ограничений LLM, стоимости моделей и вопросов безопасности корпоративных данных. Кого мы ищем: • Не классического бизнес-аналитика или координатора. • Нужен человек, который способен: понять бизнес → увидеть возможность применения AI → самостоятельно собрать первый пилот → показать результат → сформировать roadmap → масштабировать решение вместе с командой. Главный результат: • Быстрые первые победы и последующая системная AI-трансформация бизнес-направления.

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHO WE ARE LOOKING FOR Everyone at Higgsfield is an A-player. We’re looking for an AI Creator to join our Brand & Launch team. You: - Have exceptional creative taste and a strong understanding of commercial storytelling, branding, and internet culture. - Know how to create visually striking AI-generated content for launches, campaigns, social media, and product marketing. - Have hands-on experience with prompting, AI image/video generation tools, and fast creative iteration workflows. - Can turn rough ideas into polished visual concepts with speed and strong creative judgment. - Understand pacing, hooks, composition, trends, and what makes content perform online. - Take ownership end-to-end and constantly push for higher creative quality. - Are excited by the future of AI-native advertising, filmmaking, and creative production. WHAT YOU WILL WORK ON - Create AI-generated visuals and videos for product launches, campaigns, social media, and brand storytelling. - Develop creative concepts, visual directions, prompts, references, and AI workflows. - Collaborate closely with creative directors, editors, motion designers, and growth teams. - Experiment with cutting-edge AI tools and push the boundaries of AI-native commercial production. - Generate high volumes of creative assets while maintaining exceptional visual quality. - Help shape the visual identity and creative direction of Higgsfield AI launches and campaigns. YOUR MUST-HAVES - Strong portfolio showcasing AI-generated visuals, campaigns, creative experiments, or commercial content. - Hands-on experience with AI image/video generation tools and prompting workflows. - Strong visual taste and understanding of branding, storytelling, composition, and aesthetics. - Ability to move quickly, iterate fast, and execute under tight timelines. - Deep understanding of social media formats, trends, and audience engagement. - Interest in AI-powered creative tools and the future of content creation. - Willingness to complete a test assignment focused on generating AI content. THE DEAL - Competitive salary in USD. - On-site role in our Almaty office (we will relocate you from anywhere). - Full-time position with high growth potential.

Bitmanager.ai is an AI startup operating in the fast-growing area of conversational AI agents. Languages required: Russian and English (professional proficiency). Work format: On-site in Moscow.

Задачи: • Формировать AI-стратегию и roadmap бизнес-направления. • Находить наиболее перспективные точки применения AI. • Самостоятельно запускать первые прототипы и AI-пилоты. • Быстро проверять гипотезы и показывать первые измеримые результаты. • Создавать AI-агентов, RAG-решения и AI-автоматизации. • Формировать и приоритизировать портфель AI-инициатив. • Совместно с FDE и AI-командой доводить успешные пилоты до production и масштабирования. • Переосмысливать бизнес-процессы с учетом возможностей AI. • Работать с руководителями бизнес-направлений и защищать AI-инициативы. • Следить за развитием AI-технологий и применять новые подходы в реальных бизнес-кейсах. Требования: • 7+ лет профессионального опыта в технологиях, AI/ML, разработке продуктов или digital transformation. • Практический опыт запуска AI/ML или технологических продуктов. • Сильное понимание LLM, Generative AI, AI Agents и RAG. • Способность самостоятельно собрать работающий AI-прототип. • Product mindset и ориентация на быстрый результат. • Стратегическое мышление и способность формировать AI-roadmap. • Умение связывать технологии с конкретным бизнес-эффектом. • Опыт работы с руководителями и топ-менеджментом. • Высокая самостоятельность и ответственность за результат. AI-инструменты и технические навыки: • Практический опыт работы с OpenAI, Claude, Gemini, Llama, Qwen или аналогичными LLM. • Работа с LLM API, Prompt Engineering, Tool/Function Calling. • Создание AI-агентов с использованием LangChain, LangGraph, LlamaIndex или аналогов. • Практическое понимание RAG, embeddings, vector databases. • Использование AI coding-инструментов: Codex, Cursor, Claude Code или аналогов. • Python, REST API, SQL — на уровне, достаточном для самостоятельного создания прототипов. • Опыт работы с n8n, Make или другими инструментами автоматизации. • Понимание принципов работы и ограничений LLM, стоимости моделей и вопросов безопасности корпоративных данных. Кого мы ищем: • Не классического бизнес-аналитика или координатора. • Нужен человек, который способен: понять бизнес → увидеть возможность применения AI → самостоятельно собрать первый пилот → показать результат → сформировать roadmap → масштабировать решение вместе с командой. Главный результат: • Быстрые первые победы и последующая системная AI-трансформация бизнес-направления.

АО «Казахтелеком» приглашает на позицию Senior AI Officer специалиста, способного самостоятельно запускать AI-пилоты, демонстрировать их бизнес-эффективность и разрабатывать AI-стратегию для направления. В обязанности входит формирование AI-стратегии и дорожной карты, выявление и запуск AI-кейсов, создание AI-агентов, RAG и автоматизаций, а также доведение успешных пилотов до промышленного внедрения. Важна работа с руководителями для обеспечения связи AI-инициатив с бизнес-результатами. Кандидат должен иметь более 7 лет опыта в технологиях, AI/ML, продуктовой разработке или цифровой трансформации, практические навыки создания AI-решений, уверенное понимание LLM, AI Agents, RAG, владение Python, API, SQL, опыт работы с LangGraph/LangChain, n8n/Make, а также навыки vibe coding с инструментами типа Codex, Cursor, Claude Code. Требуются самостоятельность, продуктовый подход и стратегическое мышление. Формат работы — офис, зарплата в диапазоне 1–2 млн тенге NET.