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

Location: Remote US About the role More and more PlanetScale databases are created, connected and queried by AI agents. Cursor, Claude Code, Codex and a growing list of other tools now sit between developers and their infrastructure. You will own that experience end to end. You'll make sure PlanetScale shows up everywhere developers build with AI, that our MCP server and CLI work flawlessly in every agent, and that we can measure how well it all works. Then you'll show the world how to do it well through demos, docs, blog posts, videos, and conferences. This is a hands-on role combining engineering, content creation, and a strong public voice. You'll work closely with the teams that build our MCP server, CLI, API and docs. The landscape of how developers work with AI changes fast. You'll have the opportunity to move quickly, experiment, and take the lead on the future of AI use with databases and infrastructure. Make PlanetScale great with AI tools Build and maintain the plugins for PlanetScale in every AI marketplace and directory: agent plugins, skill registries, MCP directories, IDE extension stores and AI app builders Own our integrations with AI coding tools, agent frameworks and platforms Stay current with AI tools as they launch and ensure our customers have a great experience from day one Test the PlanetScale MCP server and CLI across Claude Code, Cursor, Codex, VS Code and other clients, and catch regressions before users do Find friction in creating a database, connecting, running migrations and debugging queries from inside an agent, then fix it or drive the fix with the owning team Improve the context agents rely on: tool descriptions, skills, llms.txt, docs written for agents, and error messages agents can act on Attention to AEO (answer engine optimization): make sure agents find and recommend PlanetScale Build and maintain skills for working with Postgres, MySQL, Vitess, Neki, and PlanetScale Measure how well we're doing Build evals that run real agent tasks against PlanetScale databases Benchmark how agents perform with PlanetScale and work towards continuous improvement Track how often AI assistants and agents recommend PlanetScale for database questions, and whether what they say about us is accurate Instrument and report on agent usage: databases created by agents, time to first connection, MCP versus CLI usage, and where sessions fail Show people how to do it well Build demos and sample apps that show PlanetScale and AI tooling at their best Write docs, guides and blog posts on using databases effectively with AI, including safe access, branching and performance assessment Make videos and attend conferences to communicate with our audience how to build effectively with AI These attributes best describe you Daily use of AI coding agents, with strong opinions about what makes a tool work well with them Experience building an MCP server, plugin, CLI or SDK that real developers use Software engineering background in languages like TypeScript and Go, and comfort with APIs, OAuth and the command line Experience with writing docs, blogs, and / or video content creation Good at communicating with a broad audience and customers alike on socials Experience working with relational databases (Postgres, MySQL, SQLite), schema design, migrations, connection handling, and Postgres or MySQL in production Data fluency: designing evals, writing the queries behind a dashboard, and telling a real trend from noise Clear communication of technical ideas in writing, on video and on stage Independence and speed: spotting a gap, shipping a fix, and telling people about it Genuine curiosity about the AI tooling landscape and a habit of keeping up with it Bonus points Contributions to the MCP spec, SDKs or popular open-source MCP servers Experience writing agent skills, plugins or rules files for Claude Code, Cursor or Codex Experience with LLM eval tools and building benchmarks for agents Experience with AEO or GEO, or with tracking how LLMs surface and recommend a product A blog, YouTube channel or GitHub that developers already follow Experience with Vitess, database sharding, or running databases at scale Why PlanetScale We're redefining how high-growth companies manage data at scale—and we work with some of the most exciting brands in gaming, consumer tech, and B2B SaaS. As a Software Engineer, you'll be at the core of building the platform that powers world-class apps used by hundreds of millions of users worldwide. PlanetScale is a profitable company with a philosophy centered around building small teams of p99 individuals and is recognized as one of the fastest growing companies in America. At PlanetScale we believe in supporting people to do their best work and thrive no matter the location. Our mission is to build a diverse, equitable, and inclusive company. We strive to build an inclusive environment where all people feel that they are equally respected and valued, whether they are a candidate or an employee. We welcome applicants of any educational background, gender identity and expression, sexual orientation, religion, ethnicity, age, citizenship, socioeconomic status, disability, pregnancy status, and veteran status. If you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate! Total Compensation and Pay Transparency An employee's total compensation consists of base salary + variable comp where appropriate + benefits + equity. A member of our Talent Acquisition team will be happy to answer any further questions when we engage with you to begin the interview process. Base Salary Range: $170,000 - $220,000

Обязательные требования: — Знание архитектур нейросетей (Transformer, CNN, RNN, GAN, Diffusion); — Владение методами обучения моделей с нуля и дообучения (fine‑tune) существующих решений; — Опыт работы с фреймворками PyTorch, TensorFlow, JAX; — Навыки написания кода для инференса и развёртывания моделей в продакшн‑среде; — Понимание принципов оптимизации: градиентный спуск, функции потерь, регуляризация; — Комплекс компетенций ML‑инженера с фокусом на самостоятельную реализацию алгоритмов; — Уверенное владение языками программирования Python и C++; — Способность реализовать с нуля отдельные компоненты модели: например, механизм внимания или отдельный слой; — Глубокое понимание внутренней логики работы моделей (не ограничиваясь использованием готовых методов вроде model.predict()). Задачи на проекте: — Внедрение обученных моделей в закрытый контур экосистемы компании (на частных серверах) с обеспечением их автономной работы и защитой от внешних воздействий; — Адаптация и оптимизация AI‑алгоритмов для эксплуатации на защищённых мобильных устройствах с учётом ограниченного объёма вычислительных ресурсов и необходимости минимизировать энергопотребление; — Размещение обученных моделей в закрытом контуре экосистемы компании (на частных серверах), поддержание их автономной работы и реализация мер защиты от внешних воздействий.

You will own the inference serving stack: prefill/decode disaggregation, continuous batching, KV-cache management, speculative decoding, MoE serving, quantization, and GPU performance engineering with CUDA/Triton.

Нужно оформить профиль массажиста: разработать прайс и визуальное оформление с помощью ИИ и графических инструментов.

- Отвечать за AI-направление студии: определять, какие процессы и как автоматизировать, расставлять приоритеты и доводить решения до реального эффекта; - Курировать и контролировать работу ИИ-помощников для разных направлений (геймдизайн, нарратив, разработка, продюсирование);

– Опыт работы от 4-х лет на Python. – Практический опыт построения RAG-систем и работы с векторными хранилищами, желательно PostgreSQL + pgvector.

Нужно разработать AI-конструктор, который будет автоматически создавать сайты на основе анализа конкурентов, готовой базы блоков и правил генерации контента. У нас уже есть база сайтов, блоков и правила написания текстов.

Что предстоит делать: писать интеграции AI-агентов с корпоративными системами; допиливать внутренние сервисы: авторизация, логирование, личные кабинеты, дашборды;

Ваша задача — строить RAG-системы, мультиагентные процессы и интегрировать LLM (OpenAI, Anthropic Claude) в реальные системы брокера (CRM, техподдержка, KYC/Compliance, аналитика). 🛠 Требования к кандидату: 5+ лет в бэкенд / full-stack разработке.

Design and deploy autonomous and multi-agent orchestration workflows capable of executing complex, multi-step enterprise processes. Implement structured tool-use frameworks and integrate external APIs and services using protocols such as Model Context Protocol (MCP).

-Проектирование сценариев и пайплайнов: разработка сложных системных запросов и построение цепочек (агентов) с использованием визуальных инструментов (основной стек — Langflow). -Опыт работы с LLM: уверенное понимание архитектуры современных текстовых моделей, их ограничений и возможностей.

5+ лет опыта разработки на Python.

Обязанности: выполнение индивидуальных технических заданий в направлении AI-разработки (AI-продукты для бизнеса, автоматизация бизнес-процессов).

Разработка платформы для создания автономных AI-агентов разработчиков. Разработка и внедрение мультиагентных пайплайнов для автономизации SDLC.

— Создавать персонажей, окружение и key art с помощью AI; — Курировать AI-художников, давать фидбек и контролировать качество;

- 2+ years building with large language models in production.

Location: Ukraine; North Macedonia; Turkey; European Union; Serbia; Bosnia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We are looking for a Senior AI Engineer to own and scale the AI layer of one of our core D2C subscription products. You will be fully responsible for production LLM features and the browser automation built around them end to end — prompt systems, structured outputs, evaluation, observability, and model selection — from first experiment to live release, with quality, reliability, and cost as your accountability. This is a high-impact role suited for someone who decides with data, not intuition. Unmeasured prompt changes, untraced failures, and model swaps without benchmarks are not acceptable. You work in a modern TypeScript stack — Next.js, Cloudflare Workers and Containers with Hono, Hatchet task queues, Drizzle on Supabase Postgres, Vercel Blob. Browser automation on Browserbase and Playwright is roughly half of the job. KEY RESPONSIBILITIES PROMPT SYSTEMS & STRUCTURED OUTPUTS - Design dynamic prompt templates with conditional logic and context injection that maximise generation quality - Enforce predictable outputs with JSON mode, function calling, Zod/JSON schemas, validators, and repair loops - Own complex LLM workflows (LangChain, LlamaIndex, or custom) that integrate cleanly into application logic BROWSER AUTOMATION - Build and maintain browser automation on Browserbase Functions and Playwright that traverses web flows reliably - Classify screens with a model inside each traversal, and decide what the model handles versus deterministic code - Ship automations as frozen, published workers — versioned, reproducible, and safe to roll back - Orchestrate runs through Hatchet with retries, timeouts, and failure traces that explain every broken run EVALUATION & EXPERIMENTATION - Build evaluation pipelines — test datasets, LLM-as-a-judge, RAGAS-style metrics — and score responses and screen classifications in Langfuse - Trace complex LLM chains to find bottlenecks in cost, latency, and context-window usage - Run A/B experiments across models and prompts through an AI gateway (OpenRouter, Cloudflare AI Gateway); release only on quantitative benchmarks - Re-evaluate models as new architectures emerge; fine-tune when domain requirements demand it PRODUCTION OWNERSHIP - Take AI features from experiment to live production on Cloudflare Workers and Containers, and stay accountable after release - Manage rate limits, fallbacks, and model cost so features stay reliable at scale - Resolve production incidents in owned AI and automation systems with documented root-cause analysis QUALIFICATIONS MUST-HAVE EXPERIENCE - 【5+】 years of software engineering with Node.js, TypeScript, Next.js, and Postgres, including edge or serverless runtimes such as Cloudflare Workers - Production browser automation with Playwright (Browserbase or similar): resilient selectors, retries, failure handling at scale - Production experience with dynamic prompting — content that depends on input variables and injected context - Structured outputs in production: JSON mode, function calling, Zod/JSON schemas - Experience with unified LLM APIs or AI gateways (OpenRouter, Cloudflare AI Gateway): rate limits, fallbacks, cost-effective model selection - LLM observability with Langfuse or similar: tracing, test datasets, scoring integration - Evaluation methodology: RAGAS or custom LLM-as-a-judge systems LEADERSHIP ATTRIBUTES - Decides on benchmarks and trace data, not intuition - Analytical — converts generation logs into metrics a business can act on - Iterative — builds feedback loops and improves continuously - Owns the outcome from experiment to production, and after - Verifies before trusting — treats LLM output as unproven until validated LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (60 minutes) - Final Interview (30 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Location: Remote; Seattle, WA; London; New York, NY; San Francisco, CA Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. WHY THIS MATTERS Runway is building AI to simulate the world. We think world models, not language models alone, are the path to general-purpose simulation: systems that experience the world, learn from their mistakes, and change how stories get told, how science gets done, and how the next frontiers of humanity are reached. Applied AI is where that research meets a customer with a deadline. Every one of the world's largest studios, brands, and platforms hits a moment where Runway stops being a demo and becomes the way they actually make things. Our team exists for that moment, and we organize around one question: what's blocking this customer from production, and how do we remove it? ABOUT THE ROLE This is a role for people who want to own a problem, not an account. You'll sit with the biggest studios, brands, and Fortune 100 companies in the world, figure out what's actually standing between them and production, and build whatever removes it. Some weeks that's a workflow. Some weeks it's a plugin or an integration nobody has written yet. Some weeks it's getting a room of executives to make a decision they've been putting off. Your work will be on screen: Emmy-winning shows, Oscar-winning films, Super Bowl commercials, the stuff people actually watch. And the things you build for one customer tend to become product for all of them. Our team's first Shopify plugin started as a customer blocker and was in engineering's hands within a few weeks. We treat this team as R&D for that reason, not as a cost center. We have offices in NYC, San Francisco, Seattle, and London. NO TWO WEEKS ARE THE SAME, BUT YOU CAN EXPECT TO: - Find the real problem: sit with the creative, technical, and executive teams at a customer, map how they actually work, and locate the blocker between them and production. Usually it's one of three things: a missing integration, an unproven pipeline, or a stakeholder who isn't convinced yet. - Build the first of its kind: the demo that shows a studio head or a Fortune 100 CMO something nobody has shown them before. Working proofs of concept on the customer's own brand, footage, or catalog, often built in a day or two before the meeting, and the best of them become product for everyone. - Make it reusable: turn the one-off that unblocked one customer into the workflow, plugin, or integration the next ten customers start from. - Run the evaluation: own evaluation plans end to end, guide managed trials, build tailored demos on the customer's own footage and brand, and carry the technical side of deal cycles with AEs. - Scope deployments that land: 4–12 week engagements with customer-defined success criteria, a hands-on builder and an executive sponsor on their side from day one, and enough discipline to keep them on scope when the asks start piling up. - Get customers to production fast: take new technical and non-technical customers from signed contract to first production call in days rather than quarters, grow API-only accounts into Platform + API, and fix the onboarding so the support tickets stop coming. - Present to anyone: walk an analyst through a pipeline in the morning and a studio head through a production plan in the afternoon. - Bring the field back to the product: embed with Product, Engineering, and Creative to turn what you saw at the customer into roadmap. Every repeat ask is a product requirement, not a patch. - Measure what the customer measures: time to production, usage before and after a project, what they shipped because you were there. We track our own numbers in Salesforce and the warehouse; you'll own yours. WHAT WE VALUE - People who aren't satisfied with surface-level answers and will go into the data, the code, and the room to find the real one - Low ego: the customer's outcome matters more than who gets the credit - Comfort with open-ended problems in unstructured environments, and the instinct to create structure instead of waiting for it - Builders who would rather prototype than debate, and who keep iterating with the customer until it actually works - Adaptive and introspective: willing to learn, guide, lead, and follow WHAT WE NEED - You build things that run in production. Python or TypeScript, APIs, integrations, and data pipelines. Whether you write the code yourself or with coding agents, you can read it, debug it when it breaks, and explain line by line why it's built that way, including to a customer's engineering team. You've shipped something a customer actually ran: a workflow, an integration, a plugin, or an internal tool. - You've deployed AI or ML systems and integrations inside complex organizations and can point to the outcome, not just the delivery - You can hold a room of executives and a room of engineers, and translate between the two. Some of those rooms are at the customer, so expect some travel. - Nice to have: data tooling (SQL, BigQuery, Retool), or experience in media, entertainment, or advertising production Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024