Вакансии

Design and build production RAG systems and AI agents. Run open-source LLMs self-hosted, from model selection to serving and optimization.

• Разработка backend-сервисов и REST API на FastAPI. • Интеграция и работа с LLM.

написание спецификаций для разработчиков на основе бизнес-требований и макетов интерфейсов. участие в процессе тестирования созданного функционала.

-Разрабатывать и поддерживать backend-сервисы на Python (FastAPI, asyncio). -Развивать логику диалогового агента: сценарии и состояния звонка, извлечение данных из реплик, работу с LLM.

Задачи: — Разрабатывать программное обеспечение для сбора, обработки и анализа данных. — Участвовать в проектировании архитектуры и компонентов ПО, выборе инструментов и технологий. — Писать, отлаживать и оптимизировать программный код. — Разрабатывать новые функции стека и внедрять их на различные аппаратные платформы. — Участвовать в демонстрационных и приёмо-сдаточных мероприятиях создаваемых решений. — Составлять техническую документацию к разработанному ПО. — Содействовать решению проблем при эксплуатации разработанного ПО в рамках своих компетенций. — Использовать современные инструменты разработки, управления версиями, развёртывания ПО и проведения экспериментов для обеспечения согласованности и сохранности результатов работы. Требования: — Высшее техническое образование. — Уверенное владение Python, опыт коммерческой разработки. — Работа с PostgreSQL (написание запросов, оптимизация, миграции). — Опыт работы с объектными S3-хранилищами (загрузка, выгрузка, управление доступом). — Работа с RabbitMQ (публикация/подписка, обработка сообщений, гарантии доставки). — Понимание принципов работы LLM-агентов и умение строить их с помощью LangChain, LangGraph, ADK и других фреймворков. — Опыт работы с распределёнными системами (масштабирование, отказоустойчивость, согласованность). — Знание алгоритмов и структур данных, принципов разработки ПО, гибких методологий, систем контроля версий (Git) и контейнеризации (Docker). — Понимание принципов и способов интеграции больших языковых моделей в промышленные системы. — Знакомство с протоколом MCP (Model Context Protocol) и опыт его применения (преимущество, но рассматриваются кандидаты, готовые быстро освоить). Будет плюсом: — Опыт работы с векторными БД (Qdrant, Weaviate, Milvus и др.). — Знание Redis. — Опыт работы с графовыми БД (Neo4j и др.). — Знакомство с Grafana (мониторинг и визуализация метрик). — Понимание принципов CI/CD (GitLab CI, Jenkins и др.). — Умение сделать простой фронтенд (HTML/CSS/JS, React/Vue — базовый уровень). Условия: — Конкурентный уровень заработной платы. — Расширенная программа ДМС (большой выбор клиник, включая стоматологию). — Социальная поддержка (выплаты при рождении ребенка, консультации корпоративного психолога). — Возможность бронирования. — Современный кампус с собственной парковкой. — Гибкое начало рабочего дня (по согласованию с руководителем). — Предоставление других льгот и доступ к разнообразным партнерским программам в соответствии с внутренними правилами. — Хорошая транспортная доступность (МЦД-1 до ИЦ Сколково, транспорт от станций метро Славянский бульвар, Тропарево, Кутузовская, Молодежная, Солнечная, Филевский парк).

— Поддержка и развитие AI-сервиса на Python и LangChain. — Интеграция LLM-моделей, разработка AI-агентов и RAG-систем.

Location: London Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. About LangChain At LangChain, our mission is to make intelligent agents ubiquitous. We provide the agent engineering platform and open source frameworks developers need to ship reliable agents fast. Our open source frameworks, LangChain and LangGraph, see over 90+ million downloads per month and help developers build agents with speed and granular control. LangSmith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences. LangChain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more. About the role: We’re hiring Sales Development Representatives to join our SDR team and help shape the future of how companies adopt LangChain. As part of our SDR team, you’ll turn high inbound interest and targeted outbound demand into qualified opportunities and create an exceptional first-touch experiences for prospects. You’ll work closely with our Marketing, Sales, and Operations alongside using LangChain and LangGraph-powered agents to automate list building, enrichment, and outreach freeing you to focus entirely on high-impact prospecting and conversations with teams exploring agentic AI. What makes this role different: You’ll drive pipeline and revenue while learning to leverage AI, automation, and LangChain itself to become a next-generation GTM operator. What you will do: - Follow up with inbound and outbound prospects via phone, email, and LinkedIn to uncover fit, needs, and potential value. - Partner closely with Account Executives to hand off qualified opportunities and ensure a smooth buyer experience. - Capture and share insights from conversations to inform our sales plays, product roadmap, and agent development. - Experiment with new channels, messaging, and automation to continuously increase conversion and efficiency. - Use LangChain powered agents to test, learn, and improve prospecting strategies How to be successful in this role: - 1–2 years of experience in a Sales, SDR, or BDR role within SaaS or technology (or strong curiosity and drive if you’re early in your career) - Clear, confident communicator who can engage both technical and business audiences - Motivated by learning, iteration, and experimentation you treat outreach like a craft - Comfortable with a mix of structure and ambiguity you can execute repeatable processes while improving them along the way - Excited about modern sales tech, AI tools, and shaping how next-generation GTM teams operate - Positive, persistent, and highly organized you follow up, follow through, and bring energy to every interaction Compensation & Benefits - Compensation: We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations. - Annual On Target Earnings - 110,000 GBP (70/30 split) 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: Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. About LangChain 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. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. 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. About the role Location: Singapore - Work closely with companies on the frontier of LLM-applications, bringing ideas to production-ready apps - Collaborate on a wide variety of LLM-apps from concierge search, codegen, agentic co-pilots and more - Give technical demos the entire suite of LangChain's products - Lead trainings and workshops on best practices, targeted at developer audiences - Collaborate closely with the enterprise sales team to win deals - Collaborate closely with engineering, helping translate customer insights and feedback into product improvements - Lead internally- and externally-facing, special projects that dogfood our new products - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement How to be successful in this role - Engineers who love working with customers or are aspiring future founders - Deployed engineers / solution architects who have experience in the role at developer focused companies. - You have an engineering background and enjoy being a trusted partner to companies - You like to find a way to “make it work”. Bent towards action and service orientation. - You enjoy keeping up to date on the latest industry techniques - You’re comfortable presenting best practices to bigger teams - Bonus if familiar with LangChain or building with LLMs - Can thrive in a fast moving environment. Views unstructured environments as an opportunity to figure out the most impactful work and define the future success of the company. Startup experience is a bonus. - Ownership minded - Minimum experience of 3+ years in a similar technical role: software engineering, customer engineering Compensation & Benefits - We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. 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.

Founding Engineer IT Вакансии Ищем Founding Engineer, который будет доводить продукты студии от согласованного скоупа до продакшена примерно за две недели.

Разрабатывать и исследовать ML-модели для генерации изображений и визуализации интерьерных/строительных решений на основе товаров Лемана ПРО. Проектировать и реализовывать end-to-end пайплайны для PoC: от сбора и подготовки данных до обучения, оценки и демонстрации результатов.

Location: Warsaw, Mazowieckie, Poland; Limassol, Cyprus; Sofia City, Bulgaria Workplace: hybrid Capital.com is building out its internal platform capabilities, and AI is a growing part of that. The role combines architectural ownership with hands-on delivery: you will design, build, deploy and operate the platform, including its infrastructure and DevOps. Reporting to the Director of Product Security, you will set up this function as its first member and make the early technical decisions that the future team will build on. As Platform Architect, you will own the architecture of the platform that more than 1,000 employees rely on, including their access to AI tools such as Anthropic Claude, OpenAI and future providers. Responsibilities: Build the AI platform architecture: the reference design for how LLM capabilities are accessed, governed, monitored, and extended across the organisation. Own every architectural decision for the AI platform, and document, justify, and stand behind each one. Evaluate and select new models, tools, and frameworks as the market moves. Deliver the platform as a service, so teams can move their agents into governed cloud infrastructure. Govern Anthropic (Claude API, Claude Code, Anthropic Enterprise), OpenAI, and future providers, covering API access controls, credential management, model version policy, cost allocation, and acceptable use standards. Own technical relationships with Anthropic and OpenAI at the enterprise level. Build cloud infrastructure for AI workloads on AWS and GCP: Bedrock, SageMaker, Vertex AI, Cloud Functions, and supporting services (S3, Cloud Storage, IAM, and monitoring on both platforms). Deploy and securely configure n8n, and build automation workflows connecting LLMs to Jira, Confluence, Slack, Google Workspace, HR systems, and proprietary data sources. Design and secure MCP servers and gateways connecting AI agents to internal services. Build Python integrations for AI-powered internal tooling: RAG pipelines, agent frameworks, prompt libraries, and internal AI assistants. Deliver hands-on: you write the code, build the workflows, and deploy the tooling. This isn't an advisory role. Build data privacy and security architecture for LLM usage in a regulated environment, including prompt classification, output controls, and audit trails aligned with FCA, CySEC, ASIC, and DORA. Build observability across the full stack: token consumption, cost per team, latency, error rates, and policy violations across cloud platforms and direct API providers. Build an AI adoption framework of standards, patterns, and onboarding materials that let teams across Technology use AI safely and consistently. Run internal enablement through workshops, documentation, and direct support for teams moving from ad-hoc AI use to governed, repeatable processes. Report AI platform status, risks, and roadmap to Technology leadership Requirements: 8+ years in engineering, with at least 2 years building LLM-based systems in production, not prototypes or POCs. Comfort operating as the first person in a function: you set your own priorities, unblock yourself, and deliver without a team around you. Production-grade Python: tooling that others depend on, not scripts you hand off. Deep, hands-on experience with the Anthropic and/or OpenAI APIs: function calling, tool use, streaming, RAG, prompt management, token optimisation, and model versioning. Hands-on experience with agentic platforms, MCP servers, and MCP gateways, including designing flows between AI agents and internal services. n8n: deploying, securely configuring, and maintaining multi-step automation workflows at organisation scale. Solid AWS for AI workloads: Bedrock, SageMaker, Lambda, S3, IAM, and CloudWatch, deployed and operated in production. Solid GCP for AI workloads: Vertex AI, Cloud Functions, Cloud Storage, IAM, and Cloud Monitoring. Hands-on DevOps capability to deploy and run what you build. Architectural thinking: end-to-end system design, clear trade-off documentation, and the ability to defend decisions to senior stakeholders. Security engineering for what you build: secrets and credential management, key rotation, and least-privilege IAM across cloud and SaaS. Data protection and auditability by design: classifying what data can reach which model and provider, controlling and logging prompts and outputs, and building audit trails that hold up to a regulator. Fluency in the LLM threat surface, including prompt injection, data exfiltration through model outputs, insecure tool and agent use, and model supply-chain risk, with working knowledge of a recognised framework such as the OWASP LLM Top 10 or NIST AI RMF. Nice to have: Fintech, brokerage, or financial services background. DORA or ISO 27001:2022 knowledge as it applies to AI system risk. Familiarity with the EU AI Act and other AI regulatory requirements, as well as AI-specific risk and governance standards such as NIST AI RMF or ISO/IEC 42001. LLM orchestration frameworks: LangChain, LlamaIndex, or similar. Hands-on experience with LLM guardrail and DLP tooling: Bedrock Guardrails, Vertex AI safety filters, or prompt-firewall and PII-redaction tools. Experience building internal developer platforms or AI centres of excellence. AWS Solutions Architect Professional, Google Professional ML Engineer, or equivalent. Grow with Capital.com and help shape how millions of people access the markets.

Задачи: — Автоматизация торговых операций — Разработка моделей управления рисками на основе искусственного интеллекта — Анализ эффективности торговых операций Требования: — Опыт работы с машинным обучением — Знание SQL — Опыт работы с большими языковыми моделями (LLM) — Опыт работы с LangChain — Знание MLOps — Опыт обнаружения аномалий — Опыт финансового контроля — Владение Python — Опыт работы с OpenAI API Условия: — Гибридный формат работы в Лондоне

Location: Москва AI HUB SberWorks — это флагманское направление по созданию мультиагентной среды. Мы разрабатываем платформу, где AI агенты автономно решают задачи разработки, аналитики, тестирования и развертывания. Мы ищем инженера, который не просто пишет код, а погружается в контекст применения сервисов, предлагая лучшие архитектурные решения. Обязанности * Проектирование и разработка высоконагруженных backend-сервисов на Python (FastAPI/AsyncIO). * Участие в создании и развитии инфраструктуры для мультиагентных систем (оркестрация, обмен сообщениями, интеграция с LLM). * Проектирование API (REST/gRPC) и интеграция с внутренними и внешними сервисами. * Обеспечение качества кода: написание unit/integration-тестов, участие в код-ревью. * Оптимизация производительности и отказоустойчивости сервисов. * Активное взаимодействие с продуктом и инженерами смежных команд для трансформации требований в технические решения. Требования * Уверенное знание Python 3.x и опыт коммерческой разработки от 3 лет. * Опыт работы с современными веб-фреймворками (FastAPI, Django, aiohttp). * Глубокое понимание принципов асинхронного программирования. * Опыт работы с реляционными (PostgreSQL) и нереляционными (Redis, MongoDB) базами данных. * Опыт работы с брокерами сообщений (Kafka, RabbitMQ). * Понимание микросервисной архитектуры и паттернов распределенных систем. * Опыт работы с Docker и Kubernetes. Приветствуется (Будет плюсом): * Активное использование AI-инструментов в повседневной работе (Copilot, Cursor, ChatGPT/Claude для код-ревью и генерации тестов). * Опыт разработки агентов (LangChain, LangGraph, AutoGen) или интеграции LLM в продукты. * Наработанные промпт-инженерные навыки для решения рутинных задач. Мы ценим: * Готовность к высокому темпу разработки и быстрой итеративности. * Глубокое погружение в бизнес-логику: мы ждем, что вы понимаете, _зачем_ пользователю нужен ваш сервис. Условия * комфортный современный офис рядом с м. Тульская * возможность выбрать удобный график – офис/гибрид * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * 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: Москва Наша команда развивает интеллектуальные системы для ведущего банка —рекомендательные сервисы и AI-агенты. Наша цель — создавать решения, которые помогают клиенту решить его потребности с помощью продуктов и сервисов экосистемы Сбера, персонализируют клиентский опыт и оптимизируют бизнес-процессы. При этом минимизируя ненужный инфо-поток от экосистемы на клиента. Мы ищем специалиста, который объединит экспертизу в анализе данных, бизнес-аналитике и продуктовом анализе. Тебе предстоит погрузиться в клиентские пути, формировать и проверять гипотезы, быть драйвером инноваций, влияя на развитие ключевых продуктов банка. Обязанности ### Чем предстоит заниматься: * работать с бизнес-заказчиками: выявлять и уточнять бизнес-требования, переводить их в фичи дорожной карты развития продукта * вести продуктовую аналитику: формулировать и отслеживать метрики успеха, анализировать воронки, проводить A/B-тесты и оценивать влияние изменений на ключевые показатели * анализировать данные по клиентам и запускаемым кампаниям * проводить ресерч новых источников данных для улучшения качества рекомендательной системы * участвовать в разработке и развитии стратегии развития продуктов, определять приоритетные направлений для исследований * анализировать рынок и продукты с точки зрения клиентского опыта, формировать и проверять - продуктовые гипотезы, разрабатывать концепции и прототипы * проектировать MVP на основе гипотез * согласовывать бизнес-процессы: UML диаграммы, бизнес-схемы * взаимодействовать со смежными командами в качестве заказчика * разрабатывать методологии расчетов ключевых показателей по направлению и механизмов их внедрения. Требования ### Что для нас важно: * высшее образование: техническое или экономическое * опыт работы в качестве CJE, продуктового аналитика, системного аналитика от 2 лет * опыт работы с системами управления взаимодействием с клиентом и рассылками (CRM, CDP) * опыт организации исследовательских сессий, сбора и обработки обратной связи * опыт в продуктовых исследованиях (customer development, дизайн-мышление, ux-исследования и пр.) * знание основ статистики (методология оценки A/B-тестов, проверка гипотез) * знание BPMN и опыт построения процессов и постановки требований * умение ставить эксперименты и интерпретировать результаты * навыки продуктовой аналитики: определение метрик, A/B-тестирование, проверка гипотез, анализ воронок * навыки применения ИИ в профессиональной деятельности (например, Гигачат, Кандинский). ### Дополнительным преимуществом будет: * опыт работы с LLM: проектирование, внедрение или оптимизация чат-ботов/AI-агентов (LangChain, RAG, fine-tuning) * опыт работы с BigData-стеком (Hadoop, Spark, Hive), умение строить и оптимизировать пайплайны обработки больших данных * опыт работы с HighLoad-стеком (Java, Scala, Flink), понимание принципов проектирования высоконагруженных распределенных систем * опыт работы аналитиком от 2-х лет, опыт в экосистемных компаниях будет преимуществом (Ozon/Яндекс/Тинькофф/MTC/WB) * владение Miro, Figma. Условия ### Что мы предлагаем: * срочный трудовой договор (декретная ставка) * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * корпоративный спортзал и зоны отдыха * уникальную систему обучения Сбера для профессионального и карьерного развития * программу адаптации и помощь руководителя на старте * расширенный ДМС и льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписку Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративную пенсионную программу.

Задачи: — участвовать в полном цикле разработки AI-агентов и универсальных ассистентов: от идеи и проектирования до запуска в продакшн — проводить эксперименты, тестировать гипотезы и исследовать новые подходы для создания агентских решений — разрабатывать и внедрять LLM-пайплайны, чат-ботов и интеллектуальные системы — обучать и дообучать NLP-модели под конкретные задачи продукта — интегрировать разработанные модели и логику в бизнес-процессы — мониторить качество работы моделей в продакшне, находить узкие места и оперативно вносить улучшения. Требования: — опыт в NLP и понимание технологий: от классических алгоритмов до трансформеров и генеративных моделей (LLM) — практический опыт коммерческой разработки AI-агентов, чат-ботов и LLM-пайплайнов — опыт обучения глубоких нейронных сетей — уверенное владение PyTorch, NumPy, Pandas, а также фреймворками для работы с агентами: LangChain, LangGraph (или их аналогами) — уверенное владение Python, Git, SQL, Bash, Docker. Умение писать чистый, поддерживаемый и тестируемый код — навык перевода бизнес-требований в конкретные технические и алгоритмические решения. Будет плюсом: — понимание принципов микросервисной архитектуры и опыт проектирования REST API — опыт разработки асинхронных и многопоточных приложений (asyncio, aiohttp, multiprocessing и др.) — опыт взаимодействия с реляционными и нереляционными базами данных — практический опыт настройки и поддержки CI/CD-пайплайнов (Jenkins, GitLab CI, ArgoCD или аналоги) — опыт развёртывания и управления приложениями в Kubernetes. Условия: — комфортный современный офис рядом с м. Кутузовская — гибридный формат работы — ежегодный пересмотр зарплаты, квартальная и годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — 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: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development. _______________________________________________________________________ WHAT YOU’LL DO - Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane - Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement - Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting - Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol - Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows - Lead architectural decisions and mentor engineers as the team scales - Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load - Contribute to roadmap planning, technical strategy, and cross-functional alignment KEY PROBLEMS YOU’LL HELP SOLVE - Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience - Making credential and identity handling for tool access both airtight and fast - Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed - Keeping latency low and reliability high as traffic scales from early adopters to production fleets - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ WHO YOU ARE Required Qualifications: - 6+ years of backend engineering experience with production-grade systems - Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design - Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines) - Fluency in Go, and/or Rust (both preferred) - Familiarity with AI/ML platforms or model serving infrastructure - A strong product mindset—you're excited about building developer-facing tools - Ownership mentality with a bias for shipping, learning, and iterating - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience Bonus Qualifications: - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture _______________________________________________________________________ WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $160,900 – $260,700 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance - so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started and we need exceptional engineers to help us build the backbone of the future of agent-based development. _______________________________________________________________________ WHAT YOU’LL DO - Set technical direction for core systems powering the AI Gateway 0 the model router, MCP gateway, and control plane - and make sure architectural decisions hold up as usage scales by 10x - Consistently identify gaps in our infrastructure, process, or tooling before they become blockers, and drive the fix from idea to production - Take a significant, hands-on role in defining, delivering, and implementing the Gateway's technical strategy, in close partnership with engineering leadership - Own the hardest, highest-ambiguity problems in the system: dynamic model selection, auto-failover, cost-based routing, and policy enforcement that has to work end-to-end - Act as the go-to expert for secure credential storage, session summarization, caching, and rate limiting - the capabilities everything else depends on - Build the infrastructure that lets us, and our customers, evaluate, replay, and backtest agent and LLM behavior with confidence - Mentor senior and mid-level engineers, and raise the technical bar for the team through code, design review, and example - Partner with product, design, and leadership to shape not just what the control plane UI does, but where the product goes next KEY PROBLEMS YOU’LL HELP SOLVE - Define the unified abstraction layer across diverse model and tool providers (OpenAI, Anthropic, Google, AWS Bedrock) that the rest of the org builds on - Architect secure, scalable identity and credential vaulting for tool and model access, trusted enough to run at enterprise scale - Build the infrastructure for real-time and historical analytics of AI agent behavior that leadership and customers both rely on - Guarantee that policy enforcement and logging work end-to-end - from prompt to tool to response - with no gaps an auditor (or attacker) could find - Set the bar for developer experience through intuitive APIs and first-class observability - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ WHO YOU ARE Required Qualifications - 8+ years of backend engineering experience, with a track record of owning production-grade systems at significant scale - Deep specialization in distributed systems, cloud-native infrastructure, and API design - recognized by peers and cross-functional partners as a go-to expert, not just experienced - Experience building secure, high-throughput services (gateways, proxies, load balancers, policy engines), and a history of making judgment calls other engineers rely on - Fluency in Go and/or Rust - A track record of identifying systemic gaps - in architecture, process, or tooling-— and driving the fix across team boundaries, not just within your own - A strong product mindset, with real experience shaping technical direction rather than only executing against it - Comfortable operating with wide latitude: given a problem and significant autonomy in how to solve it, including when and who to pull in - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience BONUS QUALIFICATIONS - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth 2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture - A track record of setting technical standards that other teams or engineers went on to adopt _______________________________________________________________________ WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $170,350 – $275,550 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE The ways customers buy from us are multiplying as fast as the business is growing. Enterprise order forms. Private offers through AWS, GCP, and Azure. A self-serve business running on usage-based pricing, with commits, drawdowns, and true-ups behind it. Each one is a distinct path from signature to cash, and each one runs today on some mix of manual steps and automation that grew up with the business. This role owns what comes next. You'll run order operations end to end - booking, provisioning, invoicing, amendments, and renewals - on a stack we picked deliberately and recently: Salesforce, Metronome for metering and billing, Rillet for ERP. The stack is modern, but the processes on top of it were built to keep up with growth, not designed to scale. Your job is to decide what each one should become: keep it, rebuild it, automate it, or retire it. Our bias is to invest in systems rather than in a growing queue of manual work, so you'll be setting the automation roadmap at the same time you're operating the function - deciding what a person should touch, what a workflow should handle, and what should never have been a step in the first place. Getting that right is what lets order volume grow by an order of magnitude without ops growing with it. This is a senior individual contributor role. You'll own order operations, working closely with Deal Strategy and Operations, GTM Systems, Finance and Accounting, and Enterprise Engineering. Those teams are your partners and much of your build capacity. Bringing them onto one shared order-to-cash roadmap is a core part of the job, and the reason we're hiring someone senior to do it. WHAT YOU'LL DO - Own the order-to-cash path end to end: order form intake from Deal Desk, booking in Salesforce, plan and entitlement setup in Metronome, invoicing and revenue recognition through Rillet, and the amendments, true-ups, and renewals that follow - Build out cloud marketplace operations across AWS, GCP, and Azure: private offer setup, usage reporting to each marketplace, and reconciling marketplace disbursements back to what we billed. Every new channel launches against defined readiness criteria, so marketplace deals run on the same clean path as direct ones - Own self-serve billing operations: usage metering, plan changes, dunning, credits, rebills, refunds, and the escalations behind them - Own billing and usage completeness at month-end close. Every order, credit, and metered event is reconciled between Metronome and Rillet before revenue is recognized, not after - Partner with Deal Strategy and Product as our pricing evolves. Bring the billing view into pricing and deal-structure decisions early, so new models and non-standard terms can be billed accurately and automated, not handled by hand - Set the automation roadmap. Instrument the path, put a number on every place a human touches an order, and decide what gets automated, what gets designed away, and what stays manual on purpose - Treat every billing error as a defect: find the root cause and fix the class of problem, not just the one invoice - Ship automations yourself where that's fastest, and partner with GTM Systems and Enterprise Engineering where the work belongs in core systems or the product - Write the playbook and the controls behind it: approvals, segregation of duties, reconciliations, and exception handling, built so order ops scales through systems rather than headcount and holds up under audit - Own three numbers and move them: touchless order rate, signature-to-provisioned cycle time, and billing accuracy WHAT WE'RE LOOKING FOR - 6+ years in order management, order-to-cash, billing operations, or revenue operations at a B2B SaaS company, including time building the function at an early-stage or fast-scaling one - Hands-on fluency with a modern billing and ERP stack. We run Salesforce, Metronome, and Rillet - you should know something comparable well enough to have opinions, and get to depth on ours quickly - Real experience with usage-based pricing. Per-seat is straightforward; metered consumption, commits, drawdowns, overages, and true-ups are where order ops gets interesting, and that's most of our business - Working knowledge of ASC 606 and month-end close. You don't need to be an accountant, but you should know what Revenue Accounting needs from billing data and why - Cloud marketplace experience (AWS, GCP, or Azure private offers), or a track record of getting deep on a system like that fast - A history of automating your own job. We'll ask you to walk us through a manual process you deleted: what it cost before, what you built, and what it costs now - The ability to build alignment across teams with different priorities and get to a decision, without relying on org authority - Comfort shipping a v0 earlier than feels comfortable, then iterating with real feedback NICE TO HAVE - SQL, Python, or low-code tooling in your own hands rather than on someone else's backlog - Experience building agents or LLM workflows for internal operations. We'd like to run more of our own back office on the LangSmith Platform, wherever it's the right tool and meets the same accuracy bar as the rest of order-to-cash - Audit prep or SOX readiness experience Compensation: $155,000 - $185,000 salary + options 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.