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

• Оптимизация скорости, стоимости и стабильности inference больших LLM. • Есть production-опыт оптимизации LLM inference: SGLang / vLLM / TensorRT-LLM.

- Minimum 3 years of experience building and maintaining production-level AI applications powered by LLMs. - At least 3 years of practical experience in Agentic Engineering, covering the entire process from solution design and implementation to integration, deployment, and ongoing support of AI agents.

Key Responsibilities: Develop and improve RAG applications: chunking, embeddings, retrieval and reranking. Build LLM workflows and agents with LangChain, LangGraph, LlamaIndex, CrewAI or similar.

AI / LLM Engineer (Go + Python) IT Вакансии Разработка и развитие production LLM/AI-систем и AI-агентов, построение agentic workflows, работа с prompt- и context-engineering, реализация structured output и function/tool calling, создание RAG-пайплайнов и интеграция LLM с API, базами данных и сервисами. Понимание RAG, embeddings, retrieval и reranking.

Требования: — Уверенное владение современными инструментами генерации и обработки изображений на базе ИИ — Умение работать с промптами, референсами, стилями, пресетами и настройками генерации — Умение добиваться повторяемого результата и сохранять заданную стилистику в серии изображений — Понимание принципов композиции, света, цвета, перспективы и построения изображения — Умение работать с исходным изображением продукта и интегрировать его в создаваемый визуал — Умение выявлять и исправлять характерные ошибки и артефакты AI-генерации — Базовые навыки работы в Adobe Photoshop или аналогичном графическом редакторе — Понимание требований к коммерческому визуальному контенту и подготовке материалов для дальнейшей обработки — Умение систематизировать рабочие решения: сохранять и описывать промпты, настройки, модели, пресеты и последовательность действий Задачи: — Создание и доработка визуального контента с использованием генеративных AI-инструментов: изображения, интерьерные сцены, продуктовый контент, карточки товара, баннеры и другие маркетинговые материалы — Генерация визуального контента на основе реальной продукции компании с сохранением ее внешнего вида, пропорций, материалов и ключевых особенностей — Настройка и применение AI-моделей, пресетов, промптов, стилей и шаблонов под визуальные стандарты бренда и конкретные задачи — Создание вариативного контента на основе исходных материалов: изменение окружения, фона, стилистики, цветовых решений и других элементов изображения — Подготовка и адаптация AI-сгенерированных материалов к дальнейшему продакшну: отбор лучших вариантов, устранение базовых артефактов и подготовка материалов к передаче ретушеру, дизайнеру или другим специалистам — Участие в разработке и настройке типовых AI-процессов (pipeline): генерация изображений, перекрасы, создание вариаций визуала и адаптация контента под разные каналы и форматы — Тестирование новых AI-инструментов и подходов для создания визуального контента, оценка качества и возможностей их применения в рабочих процессах — Систематизация успешных решений: создание шаблонов промптов, пресетов, простых инструкций и гайдов для повторного использования командой — Взаимодействие с фотографами, ретушерами, дизайнерами и другими участниками процесса производства визуального контента Условия: — Белая заработная плата до 120 000 рублей до вычета налога — Оформление по ТК РФ с первого рабочего дня — Выплаты дважды в месяц — Удаленный формат работы — График работы 5/2, 8 часовой рабочий день с 8.30 до 17.30 — Наставничество и обучение — Оплачиваемые отпуска и больничные — ДМС — Скидки на продукцию компании — Бонусы от партнёров — Подарки сотрудникам и детям — Программы признания и поощрения стажа — Обучение и развитие внутри компании — Возможности карьерного роста

Location: Yerevan, Armenia Problem Space Logistics operations today are still largely: manual reactive fragmented across tools running on incomplete or late data full of conflicting constraints under real-time decision pressure driven by evolving business rules a mix of legacy and new systems Much of this is unstructured: emails, documents, free-text updates, exceptions nobody modelled. That is where AI changes the game. We’re building a system that: ingests real-time operational data, structured and unstructured supports planning and execution decisions, with AI agents that act where it’s safe and hand over to humans where it isn’t adapts to constantly changing constraints What You’ll Work On AI in production. Building LLM- and agent-powered features into production .NET services: tool calling, structured outputs, retrieval over operational data, document and message understanding. The seams. Designing the boundaries between deterministic business logic and probabilistic AI: validation, fallbacks, human-in-the-loop. Trust. Making AI measurable and trustworthy: evals, test sets, observability, guardrails and cost/latency budgets. Ownership. Owning features end to end, from problem framing with product to running them in production. Design Principles keep things simple before scalable prefer explicit logic over magic abstractions, and that includes AI: deterministic where you can, model where you must optimize for change, not perfection (models, prompts and providers will change) measure AI behaviour, don’t trust vibes avoid “framework-driven architecture” accept that some parts will be ugly, temporarily Tech Stack .NET · Vue.js · service-oriented architecture · relational + operational data storage · cloud-based infrastructure · LLM APIs and agent tooling (e.g. Semantic Kernel / Microsoft.Extensions.AI, MCP) · vector/semantic search · eval and tracing tools How We Build AI-native development is the default. You use coding agents (e.g. Claude Code, Copilot) every day. You own what you ship, whoever typed it: you review AI-generated code critically, test it and understand it. What We Expect Strong, senior-level .NET engineering Ability to navigate uncertainty and work in ambiguity Willingness to challenge decisions Focus on outcomes, not just code Understanding of trade-offs and complex systems, including when not to use AI Preferring ownership over comfort Strong Plus Having shipped LLM/AI features to production and kept them running Experience with evals, prompt/version management or AI observability Python for prototyping and data work Logistics or other real-time operations domain experience What You Won’t Find Here over-engineering everything upfront unnecessary microservices “clean architecture” for the sake of it process-heavy development AI demos that never reach production wrapping a chatbot around a problem and calling it solved

Location: Yerevan, Armenia Role Purpose The AI Product Stream Lead defines and delivers AI-powered supply chain solutions that solve real customer and operations problems on the Cargoo platform. You own a product stream end to end, from framing where AI creates value (automation, decision support, agents) to shipping it and proving it works in production. You lead a cross-functional team, balancing customer value, technical and data feasibility, AI quality and cost, business priorities and delivery timelines. You also help set how Cargoo builds product in an AI-native way. Key Responsibilities AI Product Vision & Strategy Shape the stream’s product vision and strategy with stakeholders, in line with Cargoo’s AI strategy and customer needs. Identify and prioritize AI opportunities across freight operations (e.g. exception handling, quoting, document processing, planning and execution support) by value, feasibility and risk. Decide where AI should automate, where it should assist, and where a human must stay in control. Own product decisions, balancing customer value, technical feasibility, AI quality, cost, business priorities and delivery timelines. Leadership & Delivery Lead the development team through the whole product lifecycle, from discovery to rollout and adoption. Decide scope, schedule and quality, including when an AI feature is good enough to ship and when it needs another iteration. Run fast discovery loops: prototype with AI tools, validate with real users and data, then commit. Make sure the team meets internal policies, data protection rules and responsible-AI standards (incl. EU AI Act awareness). Product Management & Requirements Create clear Use Cases, Requirements and Business Rules. For AI features, add expected behaviour, edge cases, failure modes and escalation paths. Define success and evaluation criteria for AI features with engineering: accuracy, latency, cost per task and acceptable error rates, backed by representative test sets. Write User Stories and Acceptance Criteria that cover both deterministic logic and probabilistic AI behaviour. Work with engineering and data owners on data readiness: which data we need, its quality, and who owns it. Own and continuously refine the Product Backlog so the team always works on the highest-value opportunities. Track adoption and impact after release (time saved, automation rate, user trust) and feed the learning back into the roadmap. AI-Native Ways of Working Use AI tools every day for research, specs, prototyping, data analysis and feedback synthesis. Help the team and wider product org adopt AI-assisted delivery practices. Candidate Profile Education & Experience 5+ years managing software development projects, strongly preferably as a Product Owner. Proven managerial skills: team leadership, decision-making and conflict resolution. Degree or diploma in Information Technology, Informatics or a related field. Technical Skills (Must Have) Deep understanding of Agile values, principles and frameworks (Scrum, Kanban, Lean) and the ability to apply them well. Strong analytical skills, comfortable working with data to make product decisions. Solid working understanding of how LLMs and AI agents work, what they are good at, and where they fail (hallucinations, non-determinism, cost, latency). Hands-on, daily use of AI tools in your own work. Fluent English, written and spoken. Strong Plus Having shipped at least one AI/ML or LLM-based feature to production. Experience defining evaluation criteria or test sets for AI features. Logistics background or experience with logistics solutions. Experience with data products, workflow automation or decision-support systems. Behavioral Traits Excellent communication with technical and non-technical audiences, including customers, executives, managers and subject matter experts. Able to explain AI trade-offs in plain language. Strong leadership and decision-making, able to guide teams and resolve conflicts. Analytical, structured and value-driven in prioritization. Evidence over hype. Curious and fast-learning, comfortable with ambiguity and quick iteration.

Location: Ljubljana, Slovenia Workplace: hybrid Are you ready to join our digital revolution journey?    At Aleph, we’re not just part of the digital advertising landscape—we’re shaping its future. Representing the world’s leading platforms, including TikTok, Amazon, Google, and nearly 55 others, we operate in 130+ markets across new and existing geographies.   Our mission is to empower advertisers and brands to unlock the full potential of these platforms' advertising capabilities. By fostering long-lasting partnerships, we create limitless opportunities for people and businesses to advertise effectively at both local and global levels.   With a presence spanning continents, Aleph offers you the chance to be part of a fast-growing, innovative team where your work makes a direct impact. If you’re ambitious, forward-thinking, and eager to thrive in a dynamic, global environment, Aleph is the perfect place to build your career. At Aleph, we're committed to ensuring that all of our customers' and partners' data is protected and that our work complies with data protection legislation across the markets we operate in — including as AI regulation reshapes that landscape. We're looking for an experienced AI Tech and Data Privacy Associate Manager (or Manager, depending on experience), to join our global team and help manage sensitive information, support contract preparation, carry out data protection assessments, and advise on the growing intersection of AI governance and privacy compliance across our global footprint. What You Will Do Advise on and support the practical implementation of legal requirements across all AI risk categories (e.g., under the EU AI Act — prohibited, high-risk, limited-risk, and minimal-risk systems), including risk classification, compliance obligations, and coordination with product and tech teams. Monitor emerging AI regulations more broadly and advise on their intersection with data protection across our markets. Advise the business on responsible AI governance and internal AI use policies. Advise, coordinate, and support colleagues across the business on data protection and privacy compliance issues, including in non-EU markets. Collaborate on internal audits at Aleph Group level in the field of data protection. Help prepare reports, presentations, and educational materials on data protection, privacy, and AI compliance topics. Participate in data protection, privacy, and AI-related legal projects. Promote a strong culture of data protection and responsible AI compliance across Aleph. Support AI-related technology projects, including API integrations with third-party AI providers, ensuring data protection, IP, and contractual compliance throughout implementation. Negotiate and draft agreements related to AI/technology procurement (vendor contracts, API and data-sharing agreements, licensing terms), including IP protection, ownership, and indemnification provisions. Coordinate with product, tech, and other teams to assess IP, confidentiality, and data protection risks before onboarding new AI tools or vendors. Organize and maintain data protection records and related documentation at a global level. Support the preparation of contracts with business partners and other legal documents (for example, internal policies) in the field of data protection and GDPR compliance. Carry out Data Protection Impact Assessments (DPIAs) together with the wider team. Take on other ad hoc legal and compliance-related tasks as needed. What We Are Looking For A degree in Law. Minimum 4–6 years of hands-on experience in data privacy and compliance, with a strong focus on GDPR — this is not an entry-level role. Solid expertise in data privacy laws and practices, including a deep understanding of GDPR. Hands-on experience completing legal/compliance requirements for the implementation of AI systems across all risk categories (e.g., under the EU AI Act), including but not limited to high-risk systems — this is a requirement, not just a plus. Working knowledge of AI-related legal and regulatory frameworks more broadly. Demonstrated ability to research and apply data privacy requirements in non-EU markets (LATAM, APAC, and/or MEA), given our global operating footprint. Proficient English communication skills, written and verbal — this is a must. A tech-oriented mindset, genuine curiosity about how AI and emerging technologies intersect with privacy law, and strong motivation to continuously learn new legal frameworks and compliance tools. Experience working in a global or regional setting, with the ability to operate confidently outside a single-market (EU-only) focus. Practical experience negotiating and drafting technology/AI related agreements (vendor contracts, API and data-sharing agreements, licensing terms), including IP protection, ownership, and indemnification provisions. Why Join Aleph Shape data protection and AI governance practice at scale: your work will directly protect the trust of Aleph's customers and partners across a global footprint spanning Europe, LATAM, APAC and MEA. Apply AI compliance expertise at scale: you'll drive real implementation work across the full spectrum of AI risk categories as regulation matures, not just policy-watching. Build deep expertise fast: exposure to DPIAs, cross-border data transfers, AI risk assessments, and multi-jurisdictional privacy frameworks gives you a faster path to becoming a recognized privacy expert than most single-market roles. Join a growing, collaborative legal team based in Warsaw that values mentorship and hands-on learning over hierarchy. In line with the EU Pay Transparency Directive, we are committed to fair and open compensation practices. The minimum gross annual base salary is EUR 39,000, with the final level (Associate Manager or Manager) and offer reflecting your experience, skills, and scope of the role. In addition to base salary, this role includes a variable component, paid annually. Why Join Us?   Aleph is a place of many cultures, perspectives, and talents. We support each other, creating an environment of giving and receiving. We value partnership and communication because we believe it takes a group of people to achieve great things. We are energized by our ever-changing industry, our curiosity keeps us learning and seeking out new opportunities.     We stay flexible and adaptable, and believe in moving with the speed of change. We encourage everyone to strive for more, providing our internal talent with growth opportunities and the ability to learn together.    #ALEPH

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.

At Salesloft, our Principal Engineer for AI sets the technical direction for how machine intelligence works across our Predictive Revenue System. You lead through technical credibility and make the engineers around you better.

➡️ Ищем AI/LLM Engineer, который будет проектировать и развивать production-системы на базе LLM. Ищем инженера, который умеет собрать LLM-систему целиком: от prompt/context logic и агентных сценариев до backend-сервисов, интеграций, тестирования и запуска в production.

t/Ai Yo‘nalishida Oliy Ma’lumot Va Ml/Dl Bo‘yicha Kamida 2 Yillik Tajriba; Python, Pytorch/Tensorflow Va Hugging Face Bilan Ishlash;

Задачи: — Работа с NLP и AI-проектами, запуск AI-проектов в продакшн и построение архитектуры вокруг сторонних LLM-решений. — Обучение нейросетевых моделей на GPU-кластере. Требования: — Большой опыт разработки на Python с использованием Pandas, NumPy, Scikit-learn. — Опыт работы с LangChain, vLLM. — Опыт работы с PyTorch, Hugging Face Transformers. — Глубокое понимание машинного обучения, глубокого обучения и NLP. — Опыт запуска AI-проектов в продакшн и построения архитектуры вокруг сторонних LLM-решений. — Опыт обучения нейросетевых моделей на GPU-кластере. — Знание SQL. — Владение Git. — Высшее техническое образование в области Computer Science, прикладной математики, AI/ML или смежных областях. Условия: — Работа в команде экспертов. — Широкий технологический стек, сотни проектов. — Гибкий график работы. — Льготы и меры господдержки, предусмотренные для IT-компаний (аккредитованы Минцифры). — Возможность разрабатывать IT-решения для разных отраслей и пробовать новые технологии. — Возможность работать удалённо с доступом к просторным офисам с зонами коворкинга. — Возможность профессионального роста: стать тимлидом, архитектором, full-stack разработчиком. — Развитая система наставничества, сертификация за счёт компании, участие в конференциях, изучение английского языка. — Активный обмен опытом, митапы, хакатоны, доклады по развитию hard и soft skills. — 50+ клубов по интересам и профессиональных сообществ. — Уютный мерч. — Полный соцпакет и официальная "белая" зарплата. — Корпоративная база знаний и социальная сеть для сотрудников. — Гибкий ДМС с возможностью подключения родственников.

AI-native Developer IT Вакансии Студия DreamVR ищет инженера, который умеет самостоятельно превращать продуктовые задачи в работающие системы, предполагающие полную ответственность за результат. Разобраться в контексте, определить критерии готовности, выбрать решение, реализовать его и проверить результат после запуска.

You will lead and execute core 0-to-1 initiatives in cutting-edge domains such as Agentic AI. You will translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production.

— обработка Excel, PDF и сканов; — извлечение и нормализация данных;

• Проектировать и разрабатывать AI-агентов; • Разрабатывать и оптимизировать промпты, учить агентов взаимодействовать с продуктами компании;

You'll lead the team that builds the intelligence every ZoomInfo AI agent reasons over — what's true about companies and the people in them, how they relate, and what they're buying. You'll set the technical bar for a team of senior engineers while staying close to the code, shipping alongside the people you lead.