Разработка вакансии - в офисе

Applied Intuition is looking for an Embedded Test Engineer to develop and execute automotive test cases, automate validation, configure HIL environments, and report results.

Задачи: — Руководство разработкой программного обеспечения для робототехники — Интеграция продуктов — Развёртывание решений — Руководство инженерными командами Требования: — Опыт в области архитектуры программного обеспечения — Знания в промышленной автоматизации — Опыт работы с облачными платформами — Навыки работы с конвейерами данных — Опыт работы с ROS и ROS2 — Знания робототехники и интеграции аппаратного обеспечения — Владение языками программирования C# и Python — Опыт в аналитике Условия: — Работа в офисе в North Vancouver, BC — Зарплата от $130,000 до $190,000 в год

Вы будете разрабатывать и поддерживать функционал приложения, писать качественный код и участвовать в код-ревью.

• Уверенно владеете C/C++, разбираетесь в указателях и ручном управлении памятью. • Понимаете базовые структуры данных и алгоритмы.

* Own the infrastructure strategy and roadmap across networks, data centres, offices and manufacturing IT, and give the team a consistent technical direction. * Lead the consolidation of our setup across 10+ countries, and build a repeatable playbook for standing up new offices and sites.

написание и ведение сопроводительной документации заведение задач на разработку и тестирование Требования понимание принципов работы с генеративным ИИ и сопутствующими технологиями.

• Разработка новых пользовательских интерфейсов и доработка существующего функционала на React. • Участие в проектировании архитектуры фронтенда, интеграция с бэкенд-сервисами.

✔️ Coordinate and support development planning studies, including pre-concept and concept selection activities for field development projects. ✔️ Prepare, review, and maintain development plans in line with project objectives and regulatory requirements.

• Опыт коммерческой iOS-разработки от 3 лет.

-Сбор статистики из разных источников (парсинг, скраппинг, интеграция с новыми поставщиками данных). -Агрегация и обработка полученных данных.

– Опыт коммерческой iOS-разработки от 3 лет. – Уверенное знание Swift, SwiftUI / UIKit.

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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: New York City Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: San Francisco Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Boston, MA 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: $185,000–$300,000 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 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 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.

TypeSafe ищет специалиста по безопасности для работы в офисе в Сан-Франциско. В обязанности входит разработка методов оценки моделей, анализ нежелательного поведения моделей, выявление потенциальных проблем и документирование результатов исследований. Кандидат должен иметь опыт в области безопасности ИИ, интерпретируемости моделей и проведения исследований, связанных с оценкой и выравниванием моделей.

Задачи: — Техническое обслуживание и устранение неполадок роботизированных сборочных систем. — Обеспечение бесперебойной работы оборудования. — Поддержка клиентов и удалённых технических специалистов. Требования: — Знания и опыт работы с механикой, электромеханикой и программированием. — Опыт работы с системами Beckhoff, Fanuc, PLC. — Навыки работы с SolidWorks, Zebra, принтерами, системами Vision, Cognex, Matrox. — Опыт анализа данных и работы с системами автоматизации Hermes. Условия: — Работа в офисе в городе Корк, Ирландия. — Годовая зарплата от 75,000 до 80,000 долларов США.

Sierra is looking for a Strategist in Agent Development for Travel Transportation and Hospitality. Задачи: — Разрабатывать и запускать AI агентов — Консультировать корпоративных клиентов Требования: — Опыт работы с AI, системной архитектурой, API, prompt engineering, data model, RAG, conversation design, evaluation Условия: — Работа в офисе в Сан-Франциско — Зарплата от $200,000 до $290,000 в год