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

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $700M 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. ABOUT THE ROLE We are looking for a Forward Deployed Engineer to be the technical-creative weapon behind our enterprise business. This role is part cinematic director, part AI production engineer, part educator. You build the demos and proofs of concept that show Fortune 500 brands what's possible, then make those customers succeed in production: broadcast-grade cinematic work, repeatable workflows on the Higgsfield stack, and trained client teams that keep creating after the engagement. The bar for this role is insanely high-quality cinematic knowledge and taste. You know why a shot works: lensing, lighting, blocking, camera movement, pacing, edit rhythm. And you know how to get that out of generative models, reliably, at commercial quality, on deadlines measured in days. WHAT YOU'LL DO SET UP ENTERPRISE CUSTOMERS FOR SUCCESS - Convert client briefs into tailored, visually stunning demos and proofs of concept. - Own the technical-creative side of pilots from kickoff to production rollout. - Track the generative AI model landscape constantly so our work stays ahead of anything the client has seen. DELIVER CINEMATIC WORK - Direct and produce cinematic AI campaigns end-to-end for enterprise customers: creative direction, shot design, character and asset consistency, generation, edit, delivery. - Set and defend a broadcast-grade quality bar that makes the platform look world-class in public. BUILD PRODUCTION WORKFLOWS - Turn one-off wins into repeatable pipelines: model chains, presets, prompt systems, automation (APIs, MCP, agentic workflows). - Reverse-engineer reference ads, film looks, and visual styles into reproducible Higgsfield workflows. EDUCATE AND ENABLE - Train customer teams hands-on: live workshops, demos, documented workflows they actually use. - Become a trusted creative-technical advisor to CMOs, creative directors, and production leads. FEED THE PRODUCT - Bring what you learn in the field back to Product, Engineering, and Research: gaps, failure modes, feature requests, new use cases. YOUR MUST HAVES - A portfolio of cinematic AI work at commercial quality. Portfolio first, we review every single one, and it matters more than your CV. - 5+ years in commercial, film, or creative production; 2+ years hands-on with generative AI. - Deep, current fluency across the generative stack: image and video models, consistency techniques, VFX and motion workflows. You can name the models, the pipelines, and exactly how you got each shot. - Real cinematic craft: shot design, lighting, composition, storyboarding, editing. You can explain why a frame works, not just generate it. - Proven client-facing delivery: pilots, PoCs, or commissioned productions taken from brief to finished high-end results on the client's timeline. - Comfortable presenting to executives and running live demos under pressure. - Ability to teach: you can make a non-technical creative team dangerous with these tools. - High sense of ownership, drive and startup, can-do mentality. You are expected to get running on the ground from Day 1. - High agency. Excellent English. NICE TO HAVES - Background in film, advertising, fashion, or e-commerce content production (director, DP, editor, creative director). - Expert-level familiarity with each AI model, including Higgsfield's proprietary models, tools, plugins and skills - Scripting or automation experience (Python, APIs, ComfyUI, MCP, agent pipelines). - Prior forward deployed, solutions engineering, or sales engineering experience at an AI or creative platform. - An existing audience or community in the AI creative ecosystem. - Experience working with enterprise stakeholders and Fortune 500 brands. THE DEAL - Competitive salary in USD. - On-site role in our Almaty office. - Relocation to Almaty from anywhere: we sponsor and process your work permit, cover your flights, and provide temporary housing while you settle in. - Full-time position.

О позиции Разработка дашбордов и аналитики на Apache Superset с элементами AI для поддержки экспертизы лекарственных средств и медицинских изделий. Обязанности • Разработка и поддержка интерактивных дашбордов в Apache Superset • Написание и оптимизация сложных SQL-запросов, создание витрин данных • Кастомизация дашбордов (Jinja, CSS, Python) • Внедрение AI/ML-решений для аналитики и прогнозирования • Взаимодействие с заказчиками, сбор требований, презентация результатов Требования • Высшее техническое / ИТ-образование • Опыт BI-разработчика от 2 лет • Опыт работы с Apache Superset от 1 года • Продвинутый SQL • Опыт работы с PostgreSQL / ClickHouse / MS SQL • Знание Python (Pandas, SQLAlchemy) • Понимание DWH и моделирования данных Будет плюсом: опыт AI/ML в аналитике, Power BI/Tableau, Airflow, работа в фарме или госсекторе. Условия • Зарплата от 500 000 тенге • Работа в офисе в Астане • Социальный пакет по ТК РК • Участие в проектах цифровизации государственной экспертизы

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. About the Role We’re looking for a new-generation AI builder — someone between a software engineer, prompt engineer, automation hacker, and product innovator. This is not a traditional SWE role. You’ll work on AI-native products, internal agents, automations, and experimental workflows powered by the latest frontier models, open-source tooling, MCP ecosystems, and multimodal systems. You should be the kind of person who constantly explores what’s happening in AI: - new agent frameworks - open-source tooling - AI video & creative workflows - MCP servers - coding agents - automation stacks - multimodal systems - new product patterns emerging every week You don’t just follow trends — you prototype them. WHO WE’RE LOOKING FOR You might be a fit if you: - Are a hustler who ships fast and experiments constantly - Have strong intuition for building new AI-native products and workflows - Stay deeply plugged into the AI ecosystem and emerging tooling - Understand how modern AI agents actually work under the hood - Can automate things quickly and creatively - Think in systems and workflows, not just prompts - Have strong product taste and curiosity - Thrive in fast-moving, ambiguous environments - Learn new tools obsessively fast MUST-HAVE SKILLS - Experience with JavaScript or Python (ideally both) - Comfortable building prototypes, automations, and internal tools - Understanding of: - LLMs - tokens/context windows - APIs & CLI tooling - MCP ecosystems - agent frameworks - tool use & orchestration - RAG / retrieval concepts - Experience using modern AI coding workflows and AI-native tooling - Ability to quickly turn ideas into working demos or systems BIG PLUS - Experience with ML or training/inference infrastructure - Experience with multimodal or video-generation tooling - Familiarity with open-source AI ecosystems - Experience building agentic systems or autonomous workflows - Strong vibe-coding energy WHAT YOU’LL WORK ON - Build AI-native internal and external products - Prototype new agentic workflows and automation systems - Explore frontier AI tooling and identify new product opportunities - Experiment with multimodal generation systems - Build automations across engineering, creative, and operational workflows - Work closely with product, infra, and research teams - Help the company stay ahead of where the AI market is going THE DEAL - Top-of-market compensation in USD. - Small team, high autonomy, and outsized impact. - On-site role in our Almaty office (we will relocate you from anywhere).

Ipotekabank — банк в Узбекистане, входящий в международную финансовую OTP Group, специализирующийся на ипотечном и розничном кредитовании. Офис в Ташкенте.

FAIR (Meta) is the artificial intelligence research division of Meta. On-site position in Paris, France.

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: GTM Engineering builds the AI agents, systems, and automation that power how our go-to-market teams work. We partner across Sales, Marketing, Customer Success, Support, and other GTM functions to identify high-leverage problems and build solutions that improve speed, quality, and scale. Our work spans four core areas: - Identify — find high-leverage GTM workflows where AI can meaningfully improve how we operate - Build — design, build, and deploy production AI agents and automated workflows across GTM - Enable — drive adoption through thoughtful rollouts, playbooks, best practices, and ongoing enablement - Evangelize — share what we build and learn externally through content, demos, talks, and open source examples ABOUT THE ROLE: You'll own the health, cost, performance, and business impact of the GTM Agent System, and build the feedback loops that keep it improving. Because we build the platform we run on, you'll also operate the agent on LangSmith the way we tell customers to, and turn that practice into the reference story enterprises keep asking us for. You'll work across Python 3.11, FastAPI, LangGraph, DeepAgents, LangSmith, Supabase Postgres, BigQuery, Anthropic and OpenAI models, and Slack and Next.js surfaces. WHAT YOU'LL DO: - Monitor production health across every graph, catching errors, slow runs, expensive runs, and silent failures before reps report them - Triage incoming issues from Slack, tickets, and rep reports, fixing small things directly and routing the rest to the right owner - Run the weekly eval suite, investigate failures, and turn real production bugs into permanent regression tests - Track cost and latency by model, graph, use case, and role, and recommend concrete changes to model choice, reasoning effort, and caching - Track usage and adoption per rep and per feature, and own the weekly health report the team runs on - Build the business metrics that show leadership what the agent is worth, from reply rates and meetings booked to hours reclaimed and ROI - Build our own monitoring and alerting on LangSmith, and write the “how we run our own agent” story for customers WHAT YOU'LL BRING: - Strong production Python and SQL, comfortable working in traces, logs, and warehouse tables - Real experience running LLM applications, including tracing, evals, and prompt and cache mechanics - SRE or production operations instincts: percentiles, SLOs, and separating noise from real pattern - Healthy skepticism about metrics; you check what a number actually counts before you publish it - Clear writing skills, and interest in publishing what you learn - High agency; you notice what's missing and take initiative to build it NICE TO HAVES: - LangGraph or LangSmith experience - Experience building an eval suite from scratch - BigQuery or dbt - Prior DevRel-adjacent writing - Empathy for sales and go-to-market users Salary: $165,000 - $220,000 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.

Задачи: — Создавать видео и изображения с помощью Seedance, Kling, Sora, Runway, Pika, Midjourney и других AI-инструментов; — Придумывать визуальные идеи для роликов; — Писать промпты и работать с референсами; — Монтировать видео для TikTok, Reels и YouTube Shorts. Требования: — Опыт работы с AI-инструментами для генерации видео и изображений; — Уверенное владение Premiere Pro; — Знание After Effects и Photoshop; — Понимание современных трендов и визуального стиля соцсетей; — Умение быстро собирать ролики и работать с правками; — Внимательность к деталям и соблюдение сроков. Условия: — График 5/2, офис в Астане (левый берег); — Работа в молодой команде, связанной с AI, видео и соцсетями; — Минимум бюрократии и быстрый запуск идей; — Свобода в креативе и возможность предлагать свои форматы; — Доступ к новым AI-инструментам и работа с реальными проектами.

Задачи: — Создавать видео и изображения с помощью Seedance, Kling, Sora, Runway, Pika, Midjourney и других AI-инструментов; — Придумывать визуальные идеи для роликов; — Писать промпты и работать с референсами; — Монтировать видео для TikTok, Reels и YouTube Shorts. Требования: — Опыт работы с AI-инструментами для генерации видео и изображений; — Уверенное владение Premiere Pro; — Знание After Effects и Photoshop; — Понимание современных трендов и визуального стиля соцсетей; — Умение быстро собирать ролик и работать с правками; — Внимательность к деталям и соблюдение сроков. Условия: — График 5/2, работа в офисе; — Минимум бюрократии и быстрый запуск идей; — Свобода в креативе и возможность предлагать свои форматы; — Доступ к новым AI-инструментам и работа с реальными проектами.

Задачи: — Проектирование и разработка микросервисной архитектуры на Java 17+ с использованием Spring Boot (MVC, Data JPA, Security) — Построение пайплайнов Retrieval-Augmented Generation (RAG): от парсинга сырых данных до индексации эмбеддингов — Разработка и поддержка векторных баз данных Qdrant: проектирование схем шардирования, настройка гибридного поиска (BM25 + Dense Vectors) и оптимизация запросов — Создание мультиагентных систем на базе LangChain/LangGraph для автоматизации бизнес-процессов — Глубокий промт-инжиниринг: написание промптов под разные сценарии одного агента, техники Few-shot, Chain-of-Thought, структурированный вывод (JSON mode) — Отладка семантики моделей: снижение энтропии ответов, управление вариативностью через параметры инференса, механизмы self-healing при деградации внешних провайдеров LLM — Оптимизация производительности PostgreSQL: тюнинг сложных SQL-запросов, работа с индексами (B-tree, GIN/GIST, триграммы), проектирование транзакционной изоляции — Вынос вычислений в контейнерную среду: Docker, Kubernetes (Helm), построение отказоустойчивых CI/CD-конвейеров в GitLab CI/Jenkins Требования: — Уверенное владение Java 17+, понимание многопоточности (CompletableFuture, виртуальные потоки Project Loom — будет плюсом) — Экспертный уровень владения стеком Spring: жизненный цикл бинов, аспектно-ориентированное программирование, тонкая настройка пулов соединений БД и параметров безопасности — Опыт проектирования реляционных моделей в PostgreSQL, умение читать EXPLAIN ANALYZE, эффективные миграции (Liquibase/Flyway) — Практический опыт работы с векторными СУБД (Qdrant) или Weaviate/Pinecone/Milvus, понимание метрик близости (Cosine Similarity, Dot Product, Euclidean Distance) — Опыт разработки с библиотеками LangChain и/или LangGraph, построение графов состояний, интеграция внешних инструментов (tool calling) — Навык написания эффективных промптов (Prompt Engineering) и управления поведением LLM без изменения весов модели — Опыт работы с Docker и Kubernetes (манифесты, Helm-чарты), знание Linux shell на уровне уверенного пользователя — Настроенные процессы CI/CD (GitLab CI или Jenkins): сборка Maven/Gradle, покрытие тестами (JUnit 5, Testcontainers), статический анализ кода

Location: Atlanta, GA 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 The Deployed Engineering 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 The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do 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 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: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Задачи: — главный агент-оркестратор; — специализированные агенты; — реестр инструментов; — управление контекстом и состоянием; — межагентное взаимодействие; — интеграция с корпоративными системами; — безопасность; — наблюдаемость; — тестирование качества; — отказоустойчивость. Требования: — От 3 лет коммерческой backend-разработки. — Опыт технического проектирования распределённых систем. — Практический опыт работы с LLM и агентными системами. — Желателен хотя бы один агентный или LLM-продукт, доведённый до пилотной либо промышленной эксплуатации. — Опыт технического лидерства или владения архитектурой крупного модуля. — Умение работать в условиях неполных требований и постепенно формировать целевую архитектуру. — Способность общаться как с разработчиками, так и с владельцами бизнес-процессов. Условия: — комфортный современный офис: Москва, ул. Вавилова 19 — офисный формат работы на период испытательного срока, после ИС - возможен гибрид — ежегодный пересмотр зарплаты, структура дохода: оклад + 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.

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $500M in annual revenue run rate, 25M+ 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. WHAT YOU WILL WORK ON - Develop product use cases and one-click presets for generative image/video models - Develop and optimize complex generative content pipelines (images, video, audio, text). - Design and optimize agents based on LLMs for product pipelines. - Work tightly with ML and Product teams to integrate new features. YOUR MUST HAVES You don’t need to meet every single requirement to be a strong candidate — if you’re excellent in a few of these areas and eager to grow, we’d still love to hear from you. - 1+ year of experience in Prompt Engineering - Advanced hands-on experience with generative models (t2t, t2i, t2a, v2v, v2a, i2v, and others) - Deep understanding of the AI model landscape and emerging trends - Basic experience in building and configuring agents based on LLMs and other generative models - General knowledge of ComfyUI pipelines - Intuitive “vibe coding” approach - Strong adaptability and readiness to quickly learn and apply new technologies - Willingness to work in a fast-paced, high-intensity startup environment. - Excellent communication skills and ability to collaborate across research, engineering, and product teams. THE DEAL - Competitive salary in USD. - On-site role in our Almaty office. - Full-time position with high growth potential.

Стажировка оплачивается — 800 € в месяц. Частичная занятость — 5 часов в день, с понедельника по пятницу. Офис в Барселоне. Минимум 6 месяцев. Обязателен договор между университетом и компанией (convenio de colaboración). Нужно иметь возможность оформить университетский договор о стажировке (convenio) минимум на 6 месяцев.

Задачи: — разработка и поддержка сервисов на Python с использованием async — работа с Large Language Models (LLM) и их интеграция — разработка на LangChain и LangGraph — оптимизация SQL-запросов — prompt-инжиниринг и настройка LLM-инференса Требования: — высшее образование в области технических или физико-математических наук — опыт работы с различными LLM — опыт разработки на LangChain и LangGraph — актуальный опыт работы на схожей должности от года — 3+ года опыта программирования на Python — опыт работы с async-сервисами — глубокое знание SQL и оптимизации запросов — опыт prompt-инжиниринга и настройки LLM-инференса Условия: — полная занятость — офис в Москве — зарплата от 260 000 до 325 000 ₽ в месяц

Задачи: — Разработка desktop приложений на TypeScript + React (Electron / Tauri). — Работа с Node.js, WebSocket, стримингом и очередями. — Интеграция топовых AI-провайдеров и работа с локальным инференсом. — Создание функционала AI-агентов (tool calling, automation, sub-agents). — Интеграции с Telegram, Discord, Slack и WhatsApp. — Релизы, CI/CD и обеспечение качества продукта. Требования: — 2+ года коммерческого опыта с TypeScript, Node.js и React. — Реальный опыт работы с Electron или Tauri. — Уверенное владение WebSocket, Docker и GitHub Actions. — Активное использование AI-инструментов в работе. — Английский для чтения документации и рабочих задач. Будет плюсом: — Знание Python (FastAPI), MCP и опыт LLM-интеграций. — Опыт с Playwright или нативными API macOS/Windows. Условия: — Работа в офисах в Санкт-Петербурге и Москве. — 28 дней отпуска. — Компенсация профессионального обучения и курсов. — Гибкое начало рабочего дня. — Работа над передовым продуктом в сфере искусственного интеллекта. — Постоянный обмен опытом и возможность быстрого роста.

Location: Paris, France Workplace: OnSite 🤖 WHO WE ARE We’re building Mo — a health companion for everyone. We’re a small team within Alan, on a mission to redefine the future of care by democratizing access to medical expertise. We are building Mo, an intelligent, empathetic, multimodal LLM-based conversational AI assistant able to prescribe, triage, and proactively follow up on care. Imagine giving every person in the world instant, 24/7 access to personalised medical expertise - through chat, voice, or video. That’s what we are building 🤖. We kicked off the project in 2023, and we have launched Mo to all our french members (1M) in Q1 2026, making it the first safe AI health companion live at scale in Europe. 🚀 WHAT KEEPS US UP AT NIGHT We’re building a medical agent that works — reliably, safely, and at scale. You’ll work at the intersection of product engineering, ML engineering, and medical expertise. Our mission is to build the most accurate and reliable medical agent in the world, while delivering an outstanding conversational experience. Things we’re working on: - 💬 Deliver the most memorable chatting experience — You’ll work on making Mo the obvious choice when it comes to asking a health question. It means having a world-class snappy and delightful chatting experience, blazing fast time to answer, and rich content shared. - 🧱 Integrate Mo with Alan services and our healthcare system — You’ll work on integrating Mo with our other services (digital chat with HP, map of physical location of HPs, tailored prevention programs, …) to help members get from words to actions. - ➕ Extend our architecture to support the next chapters of Mo — You’ll work on our architecture, and agentic framework, to support Mo’s next needs (get more context, use new skills, be accessible in other countries we operate in) If you’re excited by the idea of building the future of healthcare, this is the team for you - we're at the start of the journey. If you’re curious, here https://arxiv.org/abs/2411.12808 is a paper we published recently. 🎯 IS IT YOU WE’RE LOOKING FOR? We’re looking for Product engineers with 3+ years of experience who get excited about building state-of-the-art AI systems and applying them to real-world, high-stakes problems in healthcare. - You’ll work at the frontier of LLMs, multi-agent architectures, and human-in-the-loop learning — and see your work deployed in production, helping real people. - You’ll implement new capabilities for Mo, working across engineering, data, and medical expertise - You'll have deep product ownership over the use cases supported in Mo, making sure we actually help our members get and stay better. - You’ll have significant influence on system architecture and code quality - You’ll mentor engineers, contribute to our product & engineering culture, and help build the team (including participating in hiring, shaping our interview loops, etc.). You would be a good fit in Mo if most of this sounds like you: - Applied background in software engineering and systems architecture - Experience with traditional ML, or LLMs, or ML dev ops is a big plus. - Product-minded: you want your solutions to be used, and impactful - Self-directed, pragmatic, driven, hard working - Humble and still willing to grow (no matter your seniority!) - Collaborative, enthusiastic about teamwork, learning, and teaching - Fluent in English (no need to speak French!) - Ex-founders are typically great fit in our team But above all, we are looking for high potential and curiosity: make sure to show us this when you apply! Everything else is a bonus. 🤘 HOW WE DO IT ? We benefit from Alan’s platform, infrastructure, distribution, and health expertise — but operate with the speed and focus of a startup. If you’re curious about Alan’s broader vision, our https://www.notion.so/alaninsuranceShareholder Letters https://alan.com/en/blog/discover-alan/a/alan-2025-q3-letter-to-shareholders are worth a read. People joining Alan are often surprised and delighted by our innovative working method. We have a set of cultural values https://alan.com/about/company-culture that guide our approach to work, such as: HOW WE WORK: OUR LEADERSHIP PRINCIPLES - Mission is the Boss — We think long-term and are methodical optimists who take risks, seeking our mission's success above all else. - Distributed Ownership — Accountable enlightened despots: everyone owns their decisions and results. - Radical Transparency — All information is accessible and written-first, so everyone can make the best decisions asynchronously. - Always Growing — Direct, positive, and caring feedback, combined with self-growth ownership. 🙌 PERKS & BENEFITS https://alan.com/en/careers/a/salary-equity At Alan, we believe that being in good health is a basic need, and it starts with our employees. This is why Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. Therefore, we offer: - Fair rewards. Generous equity packages complement your base salary. - Flexible Office. Amazing office space at our HQ, sponsored co-working hubs or a full-remote experience with home office equipment sponsorship, we want you to live where you’re the happiest. - All the tools you need. Top of the range equipment: Macbook Pro, keyboard, laptop stand, monitor, and noise-canceling headphones. - Flexible vacation policy and flexible working hours. Organize your time as you wish. - Delightful healthcare insurance: Extremely comprehensive health insurance - 100% for you and your children, 90-100% for partners depending on your country (permanent contracts only). - Transport. Country-specific commuter benefits. - Learning & Training opportunities. A highly flexible Training policy free books and budget to attend and speak at conferences if the opportunity arises. - Personal growth through coaching: At Alan, coaching isn't just a perk - it's core to who we are. Every Alaner is paired with a dedicated coach from day one, who helps maximize their impact, nurture engagement, and navigate Alan's values to develop their full potential. Learn more about our coaching culture https://alan.com/en/blog/discover-alan/a/alan-culture-excellence-through-coaching. - Parental leave. Extended parental leave for all new parents. IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply as it can only bring learnings or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. #LI-DNP

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 Role: We are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines. You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it. YOU WILL: - Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows. - Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience. - Own the Domain: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, and own the full lifecycle of the systems you build. - Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem. - Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation. WHAT WE ARE LOOKING FOR: - AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have likely already built with LangChain or LangGraph. - Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production. - Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously. - Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications. - Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture. Nice to Haves: - Expertise with LangSmith for evaluation and monitoring. - Experience building or maintaining open-source projects. - A background in technical consulting, solutions engineering, or high-growth GTM teams. Compensation: - We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. - Salary: $160K - $180K 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: London 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 The Deployed Engineering 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 The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do 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 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 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.