Вакансии

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.

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.

Опытного специалиста, которому предстоит заниматься разработкой высоконагруженных, распределенных сервисов на Golang. уверенные знания языка программирования Go от 5 лет;

What you'll do: Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards.

Location: Hong Kong, Hong Kong SAR Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity Liquidity Platform provides cutting-edge technology that covers all aspects of crypto trading. We build low-latency connectivity to global crypto venues, including both Cefi and Defi venues, strategy services for automated pricing and trading bots, high-frequency data capturing and analysis, and state-of-art micro frontend for trading management. On top of all these infrastructures, we build highly customized strategies to facilitate crypto liquidities. If you are a strong technologist who is excited about the potentials of crypto trading, interested in fully-automated algo bots, we should talk. We are looking for a Java Software Engineer for Liquidity Platform Structured Product Engineering Team. During your tenure with us, you will be working closely with a liquidity manager for strategy development using an in-house build strategy toolkit. You will demonstrate and develop professional capabilities in the following areas: managing inventory & risk of applications, strategic thinking and problem solving, collaborating with product managers, engineers and liquidity managers, effective communication. What You’ll Be Doing Work closely with team technical lead, liquidity managers and product managers on strategy discussion and technical solution design. Work with team to own the strategy production environment for both feature buildout and infra upgrade for better performance. Continuously and proactively improve strategies to be more stable, scalable and robust with auto recovery ability for 24x7 crypto trading style. Run projects by maintaining a deep underlying of the technical infrastructure and a holistic view of the product and business What We Look For In You Solid STEM (Science/Technology/Engineering/Mathematics) education background. Passionate in the Crypto industry and with strong problem solving skills. Solid knowledge in structured products business or volatility trading is a plus. Hands-on experience in AI development is preferred. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

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.

➡️ 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.

Ищем Tech Lead для руководства командой NLP-инженеров и backend-разработчиков, которая развивает платформу парсинга документов в банке. Специалист будет отвечать за техническое развитие продукта, архитектуру LLM/NLP-решений, управление бэклогом и качество реализации.

Задачи: — Отвечать за всю AI-часть продукта: архитектура AI-системы от выбора LLM-моделей до построения RAG-pipeline и интеграции компьютерного зрения, принимать все ключевые технические решения — Обеспечивать качество рекомендаций, повышая конверсию на каждой итерации — Проводить быстрые итерации с выкатыванием изменений каждую неделю, сбором метрик, анализом и улучшением — Проводить эксперименты: A/B тесты промптов, гибридный поиск (текст + визуал + отзывы), мультимодальные модели, быстро проверять гипотезы на реальных пользователях — Масштабировать систему с 2000 туров на Мальдивы до 50,000+ туров по трём направлениям с тысячами запросов в день — Строить продукт с нуля, быстро экспериментировать и влиять на архитектуру Требования: — Опыт с продакшен LLM-приложениями, построение RAG-систем или чат-ботов на основе GPT/Claude — Экспертный уровень промпт-инжиниринга: правильная структура промптов, few-shot examples, chain-of-thought — Опыт работы с эмбеддингами и векторным поиском, понимание similarity search, hybrid search, reranking — Python на уровне продакшена: чистый, быстрый, поддерживаемый код Будет плюсом: — Опыт с компьютерным зрением и мультимодальными моделями (CLIP, GPT-4o, Claude 4.5 Sonnet) — Опыт с high-load системами и оптимизацией latency — Понимание рекомендательных систем — Понимание MLOps: мониторинг моделей, версионирование, A/B тестирование — Опыт построения recommendation систем и MCP для LLM систем — Личный опыт использования LLM для автоматизации задач Софт-скиллы: — Продуктовое мышление: AI как инструмент решения бизнес-задач — Умение работать с метриками: конверсия, время сессии, escalation rate — Быстрота принятия решений: выкатывать несовершенное решение и тестировать — Умение объяснять сложное простым языком для команды и бизнеса Условия: — Официальное оформление по ТК РФ — График 5/2, офис, сокращённый рабочий день по пятницам до 15:30 — Корпоративные программы обучения и развития — Медицинское обслуживание: ДМС и собственная медсанчасть — Специальные предложения от компаний-партнеров (рестораны, магазины, отдых, мероприятия) — Организация отдыха сотрудников и их детей, оплата детского сада — Аккредитованная IT компания — Офис на станции м. Курская — Корпоративные условия на приобретение туров — Дополнительный оплачиваемый отпуск 3 дня, оплата больничного — ДМС для членов семьи по корпоративным условиям — Корпоративные условия на изучение английского и занятия спортом

Location: Hybrid - San Francisco About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role We are looking for a Product Manager to join our Product team. You will own Vercel's compute platform — Fluid compute, Vercel Functions, Sandbox, and more — the layer that runs every workload our customers deploy. You will set the direction for how developers configure, scale, and run code on Vercel, from a single function, to multi-service architectures, to agents. You will report to the Product Lead and will be located in San Francisco, CA (hybrid). Vercel invested in its own microVM-based compute infrastructure externally called “Fluid compute”. Fluid changed what’s now possible to run on Vercel. For example, we’ve delivered Sandboxes, a new primitive to run untrusted and agent-generated code. We are just scratching the surface of what Fluid can deliver. This is a senior role with wide latitude: you'll decide where that platform goes next. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What you'll do Own the product vision, strategy, and multi-year roadmap for Vercel's compute platform. Define how Vercel serves AI and agent workloads, where long-running, I/O-bound, and code-executing tasks have a fundamentally different compute profile than traditional request/response traffic. Shape the developer experience of running workloads on Vercel: resource model, attributes, API and config files. Partner with Engineering on the performance and reliability bar for compute, including cold starts and creation time latency Define pricing for new products and resources. Set the compute primitives that adjacent product areas build on, and work with those teams on what they need from the platform Work directly with Enterprise customers and the field on compute requirements that block adoption or scale What you need You've built and shipped infrastructure or developer platform products, ideally compute, serverless, containers, or runtime platforms You have the technical depth to reason about concurrency, cold starts, isolation models, and the cost and performance tradeoffs of a compute platform You have owned a platform area that other product teams build on, and set technical direction others adopted You have experience with AI or agent workloads and how their resource profile differs from conventional web traffic You have experience working directly with Enterprise customers on infrastructure requirements You have experience using usage and product analytics data to drive roadmap decisions Bonus if you Have worked at a cloud provider or on a serverless, container, or edge compute platform Have an engineering background or have built software yourself Have worked on multi-runtime platforms and the tradeoffs of supporting several language runtimes Have worked on sandboxing, isolation, or secure execution of untrusted code Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA base pay range for this role is $208,000 - $312,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

This is a Senior Software Engineer position with a strong focus on: C/C++.

As Staff Product Manager for Pricing, you will own the strategy and roadmap for how Xometry prices and evaluates manufacturability across the EMEA region — a technical, cross-functional, high-ownership role at the intersection of pricing strategy, manufacturing domain expertise, and applied AI.

💎 Создание и развитие собственных базовых языковых моделей Авито: проверка гипотез в области претрейна, continual pre-training, post-training, RL и синтетических данных, масштабирование обучения и оптимизация инференса (квантование, speculative decoding), построение процедур оценки качества моделей, написание продакшен-кода на Python и PyTorch.

Location: India Workplace: remote Overview   We are looking for a Senior SDET to test the resilience and correctness of distributed backend systems supporting a high-stakes account provisioning and onboarding workflow. This role is focused on the execution of pre-approved, benign tracer/replay scenarios against staging endpoints, analysis of request/response behavior, and documentation of observable account/CID lifecycle and downstream state behavior. The ideal candidate has strong distributed-systems and API-testing experience and maintains disciplined technical evidence capture and traceability. This role is not intended to perform unrestricted adversarial testing. Testing activities will be limited to approved staging environments and pre-approved benign scenarios.   Project Details   • Title: Senior SDET • Rate: $13.5/hr • Start Date: 26 October • Duration: 5 Weeks • Commitment: 33 Hours per Week • Location: India (Remote) • Job Type: Freelance (with the possibility of full-time employment based on performance and project needs) Responsibilities • Analyze distributed system APIs to validate correctness, consistency, and failure handling across services involved in account creation, data persistence, and related record-linking • Execute pre-approved request variations and boundary-validation scenarios using sanitized tracer payloads against designated staging endpoints • Investigate system behavior under malformed, malicious, or unexpected inputs and document findings clearly • Capture complete request/response evidence, including HTTP status codes, latency, headers, and payload bodies, subject to approved data-handling requirements • Validate behavior of near-real-time inline checks (evaluated within milliseconds at the gateway) as distinct from longer-running background verification/risk pipelines (evaluated over minutes to hours), confirming each layer of defense behaves as expected • Verify data persistence, referential integrity, and correct linkage of related records/relationships written by backend services during processing • Execute controlled replay suites and compare expected versus observed API behavior • Correlate replay results with the API schemas and network evidence produced by the Middleware SDET • Document observable account/CID lifecycle behavior and downstream state changes for handoff • Capture and archive test logs and evidence in a structured, retrievable format to support audits and post-incident reviews • Collaborate with backend engineering teams to reproduce, isolate, and validate fixes for distributed-system defects • Contribute to test strategy for backend/middleware reliability, including failure-mode and chaos-style testing • Maintain traceability between test evidence, defects, and system requirements • Reconcile backend observations with the frontend FSM and middleware/API evidence produced by earlier workstreams Required Qualifications • Strong experience of 5-8+ years in testing distributed systems and analyzing inter-service API behavior • Hands-on experience with request payload tampering, fuzzing, or adversarial API testing techniques • Understanding of layered defense architectures, including the distinction between synchronous/inline validation and asynchronous/background verification processes • Familiarity with testing data persistence and relational/hierarchical integrity in backend data stores • Demonstrated discipline in test log archival, evidence capture, and structured documentation practices • Solid understanding of backend/middleware architecture, failure modes, and system boundaries • Familiarity with API testing tools and scripting for building custom fuzzing/tampering test cases • Strong analytical and investigative skills for root-causing complex, systemic defects • Experience executing controlled API replay or staging validation is strongly preferred • Experience correlating API responses with observable application/account lifecycle states is preferred • Experience supporting audit, compliance, or evidence-based reporting requirements is a plus #L1-CC1 Why join Welo Data?   ✨ Limitless Flexibility: Work on projects that fit your schedule while collaborating with a global leader in AI data services and localization.   🌱 Limitless Growth: Apply your skills, access diverse content types, develop through structured learning, and explore career paths that can lead to permanent roles.   🌍 Limitless Support: Be part of a global community with real-time assistance from our Community Experience team.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.     We can’t wait to meet you!     About Welo Data   Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.    At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Задачи: — Разработка генеративных ИИ-моделей для синтеза визуального и проектного контента на основе структурированных данных товарного каталога в рамках проверки гипотез (PoC) внутри корпоративной платформы по оценке ИИ-инициатив — Разработка архитектуры агентов: управление состоянием диалога и контекстом, динамический выбор инструментов (tool calling), настройка уровней автономности и сценариев human-in-the-loop — Построение системы метрик: разработка офлайн- и онлайн-показателей, кросс-валидация, прямая оценка бизнес-эффекта — Непрерывный мониторинг дрейфа моделей и качества данных в продакшене — Построение пайплайнов оценки (LLM Evals): контроль галлюцинаций, релевантности ответов и мониторинг поведения системы — Обеспечение безопасности: защита от prompt injection, предотвращение утечек персональных данных (PII/privacy) и аудит прав доступа агента — Оценка стоимости, latency и масштабируемости LLM-решений Требования: — Глубокое понимание жизненного цикла ML-модели: от подготовки признаков до интерпретации результатов — Знание методов борьбы с переобучением, data leakage, регуляризации — Уверенный выбор алгоритмов под задачу — Владение матстатистикой для проверки гипотез, расчета доверительных интервалов и самостоятельного дизайна A/B-тестов — Опыт работы хотя бы в одном из направлений: классическое машинное обучение, временные ряды и прогнозирование — Языки и библиотеки: Python (pandas/polars, NumPy, scikit-learn, CatBoost/XGBoost/LightGBM, PyTorch), продвинутый SQL — Написание поддерживаемого production-кода: модульная архитектура, юнит-тесты, логирование, документация, работа с GitFlow и код-ревью — Практический опыт работы с API языковых моделей, платформой Hugging Face и orchestration-фреймворками — Опыт работы в e-commerce, retail или других продуктовых highload-системах — Инфраструктура и оркестрация: Airflow, MLflow, Kafka, Redis, Kubernetes — Мониторинг и наблюдаемость: Prometheus, Grafana, OpenTelemetry — Опыт эксплуатации GPU-инфраструктуры и оптимизации inference — Адаптация моделей через fine-tuning (LoRA/PEFT) — Опыт проектирования agentic workflows или multi-agent-систем — Понимание принципов информационной безопасности, privacy и работы с персональными данными

Задачи: — Разработка и поддержка автоматизированных тестов на Python — Автоматизация управления конфигурацией системы обработки трафика — Написание тестовых скриптов для генерации/воспроизведения мобильного трафика, валидация соответствия трафика спецификациям 3GPP — Нагрузочное тестирование системы обработки мобильного трафика: выявление узких мест (в том числе связанных с оборудованием) — Разработка и поддержка веб-интерфейса для конфигурирования и мониторинга системы (FastAPI/JS) — Интеграция тестов в CI/CD — Взаимодействие с разработчиками: воспроизведение, диагностика, локализация дефектов Требования: — Опыт автоматизации тестирования от 3 лет, с акцентом на системное/тестирование высоконагруженных систем — Опыт написания скриптов на Python и Bash (работа с pcap, CLI-командами, управление сетью, SSH) — Умение анализировать pcap-файлы, валидировать соответствие протоколам (3GPP и др.) — Знание тест-фреймворков: pytest, контекстные фикстуры, параметризованные тесты — Глубокое знание Linux: файловая система, процессы/потоки, сеть (TCP/IP, NUMA, PCI/PCIe), мониторинг (sysstat, eBPF, perf) — Понимание аппаратной платформы: NUMA-распределение, DPDK, сетевые карты Intel X710, irq affinity, DMA, влияние CPU-топологии на latency — Навыки работы с метриками: сбор (prometheus/node_exporter), анализ (p95/p99 latency, throughput, context switches) — Опыт разработки веб-интерфейсов на Python/JS (FastAPI, Flask или аналогичные): создание REST API, обработка HTTP-запросов, интеграция с фронтендом (HTML/CSS/JS — базовое понимание) — Опыт с CI/CD-инструментами (GitLab CI/Jenkins), интеграция тестов в pipeline — Английский язык — B1 (чтение спецификаций, технической документации) Условия: — ДМС + стоматология — Корпоративные скидки в фитнес-клуб World Class — Корпоративный тариф на абонементы FITMOST — Программа корпоративных скидок Best Benefits – на спорт и не только — Спортивные мероприятия (турниры по футболу, волейболу, киберспорт, забеги, шахматы) — Курсы английского языка, в том числе с носителем языка — Сообщества по интересам: вместе читаем книги, ходим на интересные мероприятия и делимся маршрутами путешествий — Внешние профессиональные курсы и конференции, сертифицированное обучение, которые вы выбираете сами — Профильные митапы – организовываем, проводим и принимаем участие — Билеты со скидкой в Музей криптографии для сотрудников и их семей — Комфортный офис в Москве с кофе-поинтами и разнообразными снеками — Насыщенные и яркие корпоративные праздники — Классный мерч

Location: Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; London, United Kingdom; Madrid, Spain; Munich, Germany; Prague, Czech Republic; Warsaw, Poland; Yerevan, Armenia Coding agents are only as good as the context they're given. Most explore a repository like a new hire on day one – grepping, opening files, guessing. JetBrains Context replaces that with actual knowledge of your whole codebase and resources, served to any agent that asks. If you want to own the layer that decides what an agent knows before it writes a single line, this is for you. 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 As agents get better at searching for themselves, what is the durable value of a managed retrieval layer? We need someone with an opinionated answer to own JetBrains Context as a product – defining what it is for, who it is for, how we measure success, and where it goes next. This is a hands-on role where you'll manage the product from a terminal and agent session rather than slides. You'll bridge the technical core and cross-functional teams: collaborating closely with engineering and ML teams on indexing pipelines and retrieval quality, working with Air, IDE, and Junie teams on integrations, and partnering with marketing, developer advocacy, sales, and customer success on positioning and adoption. You'll take full ownership of defining problem statements, setting explicit trade-offs, and balancing cost, latency, and freshness across the platform. Day to day, you will: Build and maintain a deep working understanding of chunking, embeddings, index freshness, retrieval, reranking, and agent-facing surfaces. Define and defend an opinionated vision for the product's evolution, including explicit target audiences, use cases, and key success metrics. Translate product strategy into actionable problem statements, priorities, plans, and milestones with an explicit definition of “done”. Communicate product direction clearly to engineering, leadership, cross-functional stakeholders, customers, and prospects. Analyze competing context and code-search products through direct use to establish clear differentiators and identify gaps. Define core operational and product metrics – index freshness, retrieval quality, agent task outcomes, adoption, retention, and unit economics – to guide decision-making. Represent the product externally by sharing roadmaps, publishing updates, speaking to developer audiences, and gathering community feedback. Partner with ML teams on model evaluation and platform teams on service scale, reliability, and cost. What you’ll bring A well-argued point of view on where AI-first development is going and what agents genuinely need from a context layer. Comfort with technical depth across embeddings, retrieval quality, sub-agents, tool-calling, indexing costs, and API design. The habit of using the product you build daily alongside competitors' tools. Communication that adapts to different audiences, from staff engineers and enterprise architects to conference attendees. A data-informed approach that combines telemetry, evaluation results, customer conversations, and market signals. Comfort with ambiguity and a preference for defining a new category over copying an existing one. What you’ll need Proven experience owning a complex developer, platform, or infrastructure product end to end, including strategy and roadmap. Hands-on familiarity with modern AI coding tools and agent workflows. The technical capability to work directly with engineering on retrieval behavior, APIs, data models, and integration surfaces. The ability to define metrics for quality-sensitive products and build evaluation habits that maintain product standards. Experience communicating a product externally through written content, talks, or community engagement. Practical experience with search, retrieval, RAG, developer search, or static analysis at scale is a plus. What success looks like Within your first months, you'll form and share a clear thesis for what JetBrains Context is and is not – one the engineering team recognizes as theirs and leadership can invest in. You'll establish a metrics story that distinguishes real retrieval quality from vanity usage, a roadmap with clear trade-offs, and a documented evaluation of serious competitors. Longer term, success means JetBrains Context becomes a deliberate choice for developers and organizations, agents get measurably better answers because it exists, enterprises adopt it for its governance and scale, and the market clearly understands its unique value because you've communicated it effectively. 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. 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-HYBRID #LI-AA1 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.

Задачи: — Развитие платформы: работать над функционалом, стабильностью и производительностью. — Развивать AI-функционал: LLM-based сценарии, tool calling, RAG, работу с контекстом, кэширование и другие механики. — Разбираться со сложными production-инцидентами и устранять не только последствия, но и причины проблем. — Клиентские внедрения: превращать пожелания клиента в дорожную карту запуска. — Проектировать архитектуру интеграции Sance.AI с инфраструктурой клиента. — Отвечать за техническую часть сложных клиентских запусков — от discovery до production. — Команда и инженерные практики: менторить junior/middle-разработчиков, помогать с декомпозицией задач, архитектурой и сложными техническими вопросами. — Проводить code review и повышать качество решений команды. Требования: — От 4 лет коммерческого опыта в разработке, от 1 года опыта в продуктовой команде. — Уверенные знания в asyncio, очередях, кешировании, конкурентности. — Практический опыт создания production-функционала на базе LLM, а не только использование ChatGPT. — Опыт с OpenAI API или другими LLM API. — Знания prompt engineering, tool calling, RAG, caching и context management. — Опыт с embeddings, vector search и agentic workflows. — Опыт тестирования и evals. — Понимание production-проблем: latency, стоимость, rate limits, hallucinations, retries и observability. — Уверенная работа с REST API сторонних сервисов, webhooks и внешними сервисами. — Умение разбираться в документации. — Опыт интеграций с CRM — особенно amoCRM и/или Bitrix24. — Умение довести размытую бизнес-задачу до работающего production-решения, видеть системные проблемы и помогать команде расти. — Будет плюсом опыт B2B/Enterprise-внедрений, highload и event-driven систем. — Собственные AI-проекты и опыт работы в стартапах. Условия: — Работа в быстрорастущем AI-стартапе, влияние на продукт, архитектуру и процессы. — Разнообразные задачи, крупные клиенты и короткий путь от идеи до production. — Быстрый карьерный рост.