Разработка вакансии - в офисе

Проектировать архитектуру и развивать backend-сервисы для управления инфраструктурой хранения и процессинга данных; Отвечать за техническое качество направления: код-ревью, стандарты разработки, тестирование, документацию;

взаимодействовать и помогать клиентам в решении вопросов по работе программы 1С; анализировать проблемы\ошибки в системе и находить их решение;

Ищем ответственного и сверхактивного сотрудника, который возьмёт на себя полный контроль, управление и ЛИЧНОЕ УЧАСТИЕ в полном производственном процессе по созданию YouTube-роликов: от проверки сценария до финальной подготовки ролика к публикации. - Свободное владением русским языком, высокий уровень грамотности;

Формирование эффективной команды: участие в подборе сотрудников, постановка задач и контроль их выполнения, контроль эффективности сотрудников, а также развитие их компетенций;

Анализ существующих бизнес-процессов, выявление узких мест, неэффективных операций и областей для оптимизации. Разработка и представление оптимальных решений на базе 1С: БГУ и 1С: ЗКГУ, учитывающих специфику деятельности учреждения и требования законодательства.

- разработка и доработка конфигураций на платформе «1С: Предприятие 8» на управляемых формах; - интеграция программных продуктов 1С с другими информационными системами;

Проектирование и поиск решений для прикладных задач на платформе 1С 8.3. Разработка и адаптация конфигураций 1С (доработка, адаптация, модификация).

• Разработка и поддержка backend-сервисов на PHP/Laravel. • Проектирование и внедрение микросервисной архитектуры.

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're looking for a Senior Fullstack Engineer for our commercial product LangSmith, an observability and evals platform. In this role, you'll have the opportunity to shape the technical direction of our platform while working closely with enterprise customers, developer end-users and internal stakeholders. WHAT YOU WILL DO: - Lead the technical architecture and implementation of key product features for LangSmith, working across our entire Go, Python, and Typescript stack. - Collaborate closely with product and design teams to iterate on new features. - Mentor and guide more junior members of the team. Drive aggressive project timelines while ensuring high engineering standards are being met. - Lead by example in writing clean, maintainable, and well-tested code   WHAT YOU BRING: - 5+ years of experience in software engineering working on complex platform products - Fullstack engineering experience with Go or Python on the backend and React + Typescript on the frontend. - Strong understanding of database systems, particularly Postgres and Redis - Experience designing and scaling APIs, preferably in a high-performance, data-intensive application - A “get stuff done” attitude - comfortable shipping fast and iterating based on user feedback - Strong communicator with the ability to collaborate closely with various internal stakeholders and engage directly with our top-tier customers - Strong ownership mindset - Bonus: Experience with AI/LLM-powered applications, developer tools, or observability platforms   Annual salary range: $175,000-$240,000 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.

Location: New York, NY 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 LangSmith team owns and builds LangChain's core platform for observability, evaluation, and production reliability of AI systems. From tracing and annotation to run rules, evaluations, and beyond, this team owns LangSmith end-to-end. If you want to define what great AI observability looks like at production scale, this is where that work gets done.   ABOUT THE ROLE We are looking for a Senior Backend Engineer to join us. In this role you will be building the backend systems that power LangChain’s observability and evals platform. You will work on the core services that allow developers to monitor and evaluate their AI applications at scale. While the focus is on backend feature development, familiarity with fullstack or frontend engineering, performance tuning, and debugging production issues would be extremely valuable.   WHAT YOU'LL DO - Design, develop, and maintain backend services and APIs to support LangSmith’s tracing, monitoring, and evaluation workflows. - Collaborate on architectural decisions to ensure systems are performant and maintainable. - Optimize storage and query performance for high-volume observability and evaluation data. - Ensure system reliability through strong testing, monitoring, and alerting practices. - Troubleshoot and resolve production issues, performing root-cause analysis and implementing long-term fixes. - Create and maintain technical documentation, including system design and API references. - Work closely with full-stack engineers, product managers, and product designers on rolling out new features.   WHAT YOU'LL BRING - 5+ years of professional experience in backend engineering working on highly complex products - Proficiency in one or more backend languages/frameworks, ideally Python or Go - Strong understanding of API design and building reliable data services. - Experience with high-throughput or mission-critical systems. - Demonstrated ability to optimize backend services for performance and reliability. - Experience with database systems (Postgres, Redis, Clickhouse), and cloud platforms (AWS, GCP, Azure) - Strong communication skills, with the ability to collaborate cross-functionally - Customer centricity and ownership mentality   Compensation Annual salary range: $180,000- $240,000 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.

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   This 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. Sales 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   You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work 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 - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement 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: $185,000–$315,000 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.

Location: New York, NY 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 This 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 You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work 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 and customers - 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 - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement   WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production   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 Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 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.

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 This 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 You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work 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 and customers - 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 - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production 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 Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 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.

Продумывать и внедрять архитектурные и технологические решения направления — как в продуктах команды, так и на стыке с решениями, которые реализуют другие команды. Искать и устранять фундаментальные технические риски, стандартизировать и внедрять платформенные решения уровня всей организации.

🔸 Собирать новые игры на общем игровом движке: игровое поле, ставки и фишки, история раундов, анимации выигрыша и другие игровые механики. 🔸 Интегрировать Rive-анимации и управлять их state machine непосредственно из игровой логики.

React + TypeScript, Python (FastAPI), PostgreSQL, Docker, GitLab CI. • человека с опытом в стартапе или небольшой команде;

— разрабатывать и дорабатывать frontend веб-платформы; — работать с картами, таблицами, формами, графиками и дашбордами;

Задачи: — Проектирование и реализация backend- и frontend-частей веб-приложений и внутренних систем — Разработка async API и сервисов на Python (Litestar, FastAPI) — Проектирование моделей данных, схем БД и миграций — Работа с аналитическими нагрузками: тяжёлые запросы, агрегации, оптимизация под OLAP — Проработка бизнес-логики и доменных моделей (DDD), слоистая архитектура — Интеграция сервисов между собой: gRPC, брокеры сообщений, фоновые задачи — Контейнеризация сервисов и настройка окружений (Docker, GitLab CI) — Разработка пользовательских интерфейсов на React + TypeScript — Интеграция фронтенда с backend-API, кодогенерация клиента из OpenAPI, обработка edge-кейсов — Разработка и поддержка переиспользуемых UI-компонентов — Участие в проектировании архитектуры приложений и выкатка своего кода в прод Требования: — Опыт коммерческой разработки от 3 лет, из них год+ в роли fullstack — Python 3.12+, полная типизация — Litestar или FastAPI, Pydantic v2, Dishka — SQLAlchemy 2.0, Alembic, asyncpg — PostgreSQL: индексы, план запроса, оконные функции, оптимизация тяжёлых запросов — Опыт хотя бы с одним аналитическим или поисковым хранилищем: ClickHouse, Elasticsearch, Neo4j — Слоистая архитектура, DDD — Git, Docker, GitLab CI (или аналог) — Фоновые задачи и очереди: taskiq или Celery, NATS, Redis — React 19, TypeScript, Vite, bun — TanStack Router, TanStack Query, TanStack Table, Zustand, react-hook-form, zod — Компонентные библиотеки: Mantine 8 либо Tailwind 4 + Radix/shadcn — Feature-Sliced Design или другая явная слоистая структура фронтенда — HTML, CSS, component-based подход — Системное мышление, внимание к качеству кода, самостоятельность в проработке задачи Будет плюсом: — structlog, uv, ruff, pytest с async-тестами — gRPC (grpclib, betterproto2) — MinIO / S3 — Интеграция self-hosted LLM через OpenAI-совместимый API, pydantic-ai — Ansible, Terraform, Grafana — Biome, кодогенерация API-клиента (@hey-api/openapi-ts) — motion, ECharts / Recharts, графовые визуализации — vitest, Playwright Условия: — Полная занятость, работа в офисе — Влияние на архитектуру backend- и frontend-частей продукта — Собственная инфраструктура on-premise, современный стек без легаси — Конкурентная заработная плата, обсуждается по итогам собеседования