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

Ищут специалиста, который соберёт LLM, RAG-компоненты и агентов в единую систему для бизнес-задач. Будете писать промпты под сценарии, внедрять метрики качества и A/B-тесты, разворачивать сервисы в Docker.

Location: Limassol; Nicosia; Athens; Thessaloniki; Fully Remote - in other eligible locations Workplace: hybrid The Role:   We are looking for a Software Development AI Technical Expert to serve as the department’s designated AI specialist and lead the responsible evaluation, adoption and practical application of AI across Software Development and Software Quality Assurance. The role will research emerging AI technologies, support experimentation and pilot projects, and translate successful solutions into practical tools, standards and development practices. You will provide technical guidance on AI-enabled development, code quality, security, AI advocacy, capability building and impact measurement. You will work closely with Software Development and Software Quality Assurance teams to develop practical, responsible and measurable AI-native ways of working that improve productivity, quality, security and innovation. The main responsibilities of the position include: Act as the subject-matter specialist for AI-enabled Software Development and Software Quality Assurance, maintaining current knowledge of large language models, AI development tools, AI agents and emerging technologies. Research and benchmark AI applications, tools, vendors and industry practices, assessing their relevance, maturity, limitations, security and potential value to the organisation. Provide expert advice on the practical and technical application of AI across the Software Development Lifecycle, from requirements and design through coding, testing, deployment and monitoring. Explore, prototype and evaluate AI capabilities and use cases, defining clear objectives, success criteria, evaluation methods and recommendations. Contribute to AI pilots from concept through implementation and evaluation, identifying lessons learned, adoption requirements and opportunities for scaling successful solutions. Support the transition of approved AI tools and practices into Software Development and Software Quality Assurance, including AI code assistants, automated code review, AI-supported testing and intelligent CI/CD practices. Develop guidance, standards and best practices for the responsible use of AI and AI-generated code, covering quality assurance, security, data protection, intellectual property, maintainability and human oversight. Establish and monitor measures of AI effectiveness and impact, including output quality, reliability, usability, developer experience, cycle time, defect rates, deployment frequency, test coverage and rework. Assess the AI maturity of Software Development and Software Quality Assurance teams and recommend practical actions to improve organisational capability. Support cultural change, knowledge-sharing and upskilling through playbooks, prompt libraries, FAQs, onboarding materials, reusable templates, case studies and communities of practice. Collaborate with stakeholders across IT, the Group and other departments to identify and assess AI opportunities aligned with business priorities, roadmaps and projects. Collaborate with AI representatives across the Group to share knowledge and support a coordinated approach to AI adoption. Maintain relationships with vendors, research communities and industry peers, bringing relevant developments and insights back to the organisation. Represent the Group, when requested, at conferences, external events and industry forums, contributing to presentations, demonstrations, articles and other technology-related activities. Main requirements: BSc/MSc in Computer Science, Data Science, Engineering or a related field, or equivalent practical experience. At least 7 years of experience in IT engineering roles, including experience in a managerial or leadership role within a Software Development team. Solid working knowledge of the modern AI landscape, including Large Language Models, AI agents, automation platforms, prompt engineering techniques and practical business applications. Demonstrated experience modernising or transforming software development lifecycles through AI tooling and automation. Deep understanding of modern SDLC practices, including CI/CD, DevOps and platform engineering, combined with hands-on experience with AI-powered development tools. Strong Machine Learning and AI background, with hands-on experience building, prototyping or deploying AI solutions. Experience contributing to governance frameworks covering quality assurance, security review or intellectual property considerations for AI-generated outputs. Solid understanding of IT engineering metrics and data-driven measurement of development performance. Exposure to AI or IT engineering maturity models and experience assessing team capabilities against defined frameworks. Experience evaluating technology vendors and AI tooling through trials, benchmarking and recommendations. Experience presenting to and working directly with senior or C-level stakeholders. Public speaking or conference presentation experience in AI or technology, with the ability to inspire technical and non-technical audiences. Innovative and curious mindset, with the ability to explore emerging technologies, challenge unsupported claims and identify practical applications. Proficiency in written and spoken English. Ability to work independently and collaboratively in fast-paced environments. Strong analytical and problem-solving skills. Strong organisational skills, with the ability to manage multiple initiatives and priorities. Willingness and ability to continuously learn and upskill. The following will be considered an advantage: Experience in fintech, trading or financial services. Experience working with or within an innovation lab or applied research environment. Experience with AI or IT engineering maturity frameworks. Experience representing an organisation at external technology events and industry forums. Benefit from: Attractive remuneration package Intellectually stimulating work environment Continuous personal development and international training opportunities Attractive relocation package and support for a smooth relocation for you and your family The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy Policy and the Confidentiality Undertaking.

Задачи: — Владение полным циклом пользовательских сценариев с AI-агентом Upgrade на чат, голос и email: создание, оптимизация, обработка крайних случаев и рост показателя containment. — Создание сценариев в no-code инструменте Sierra Agent Studio, сотрудничество с продуктовыми группами для интеграции сервисных потоков. — Ответственность за разрешение проблем клиентов AI-агентом без участия человека. — Анализ и улучшение сценариев после запуска, включая чтение транскриптов и повышение качества взаимодействия. — Ведение портфеля сценариев по продуктам (Personal Loans, Card, BNPL, HELOC, Deposits) и установление стандартов разработки AI-опыта. Требования: — 3–5 лет опыта во Frontend Software Engineering или эквивалентный опыт в Solutions Engineering, Conversational AI или технических продуктовых ролях. — Знание поведения LLM-агентов: инструкции, вызовы инструментов, извлечение знаний и типичные ошибки. — Опыт построения оценок для недетерминированных систем: тестовые наборы, симуляции, LLM в роли судьи, регрессионные проверки. — Техническая грамотность для чтения API спецификаций, работы с backend-инженерами по REST и GraphQL, понимание авторизации и прав доступа. — Знание JavaScript/TypeScript для создания и поддержки кодированных сценариев и интеграции API в платформы Conversational AI. — Ориентация на продукт и клиента, умение читать транскрипты, забота о тоне общения и измерение успеха по решению проблем клиента. — Владение процессами выпуска, мониторинга, анализа логов и реагирования на инциденты. — Умение ясно писать и работать с неинженерами из операций, комплаенса и юридического отдела. Плюсы: — Опыт работы с Sierra Agent Studio или аналогичными no-code платформами (Decagon, Ada, Kore.ai, Google CCAI, Amazon Lex/Connect). — Опыт с Voice AI: распознавание речи, синтез речи, настройка задержек, обработка прерываний. — Знание систем контакт-центров, таких как Genesys, и проектирование передачи агентам. — Опыт в финтехе или регулируемых отраслях (UDAAP, FDCPA, TCPA, PCI, SOC 2). — Опыт в дизайне разговоров или UX-писательстве. Условия: — Конкурентная зарплата $140K-$180K CAD и опционный план. — Оплачиваемое медицинское, стоматологическое и офтальмологическое страхование. — Гибкий оплачиваемый отпуск. — Возможности профессионального роста и развития. — Оплачиваемый декретный отпуск. — Инициативы по здоровью и благополучию.

-AI Engineer должен находить участки, которые сегодня требуют человека, таблиц, браузера и десятков повторяющихся действий, и превращать их в автоматизированные процессы, сервисы или AI-агентов. -Python и SQL/PostgreSQL.

- 3+ years of experience in web apps or services. - Hands-on experience with n8n or Make.

{COMPANY} is looking for an AI Strategist to deploy its platform, advise financial-services customers, and drive measurable value and commercial growth.

SpAItial is looking for an ML Inference Engineer to build and operate scalable inference services and production APIs.

Synthesia is looking for a Research Scientist Interactive Avatars to develop and evaluate multimodal diffusion models for natural real-time avatar interactions.

Location: San Francisco, CA; 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. _______________________________________________________________________ Docker is looking for a Senior Software Engineer to build AI-powered developer tools and the platform behind them on our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building tools that make Docker's engineers more productive and the platform that lets teams across Docker prototype, deploy, and scale their own AI developer tools. As a Senior Engineer you will design, build, and operate: AI-Powered Developer Tools. AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools, using the patterns and standards the team sets. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal and Staff engineers, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a strong, hands-on engineer who enjoys building at the intersection of AI, developer experience, and platform engineering. You have built software on top of LLMs and AI agents and have a good sense of what works in practice. You care about the people using your tools, and you can tell a tool developers love from one they put up with. You take a feature from a vague request to production: you ask the right questions about requirements, design it sensibly, ship it iteratively, and operate it afterward. You are comfortable in a fast-moving AI landscape and balance quality with pragmatism. You make the engineers around you better through thoughtful code review and by sharing what you learn. RESPONSIBILITIES Building and Operating AI Developer Tools - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools, following the team's patterns and standards - Build systems that help Docker's engineers adopt AI-native development tools - Build integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Instrument your tools so the team can measure adoption, effectiveness, and developer satisfaction Self-Service Platform - Build and improve platform capabilities, including deployment pipelines (ArgoCD/GitOps), observability integration (Grafana), security controls, and cost management, that help teams ship their own AI tools faster - Help reduce time-to-production for new products from weeks to days - Contribute to reliability, security, and performance standards for AI systems, including SLOs, monitoring, and incident response Design and Delivery - Take features and services from requirements to production. Ask about scale, users, and constraints before designing, and write down your assumptions - Write clear design documents for the work you own, and participate in design reviews for the team - Review code thoroughly and share what you learn with the rest of the team - Take part in the team's on-call rotation, and help improve alerts, runbooks, and tooling so the next incident is easier - Follow the AI-assisted engineering practices the team sets: use AI tools critically, validate their output, and stay accountable for what you ship Collaboration and Growth - Work with the Senior Manager and the team's Principal and Staff engineers to understand priorities and shape your work - Partner with Infrastructure, Security, and Data teams on integrations and shared standards - Help newer engineers get up to speed on the team's tools, patterns, and practices - Keep up with emerging AI/LLM technologies and agent frameworks, and bring useful findings back to the team QUALIFICATIONS REQUIRED - 6+ years of software engineering experience building and operating production systems - Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Working knowledge of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Experience building and operating scalable backend services, distributed systems, or developer-facing platforms - Experience with cloud-native infrastructure, including Kubernetes, CI/CD pipelines, and observability systems - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience building developer tools, platform systems, or internal tools that other engineers rely on - Good product judgment: you weigh developer experience and technical trade-offs, and you ask clarifying questions before committing to a design - Clear written and spoken communication suited to a remote, async-first company - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Comfortable working autonomously in a distributed, remote-first team - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience with GitOps deployment patterns (ArgoCD) or Grafana-based observability - Familiarity with security and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Learn Docker's current AI and developer tooling landscape, the team's services, and the architecture decisions made so far - Meet your teammates, including the Principal and Staff engineers, the Senior Manager, and key stakeholders in product engineering - Ship a useful production change in your first weeks, using the team's AI-assisted engineering workflow - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Shadow on-call and learn the operational profile of the team's services FIRST 90 DAYS - Own a feature or service from design to production with measurable impact, such as part of an AI code review agent, a deployment diagnostic agent, or an on-call assistant - Write the design document for work you own and take part in team design reviews - Contribute to the self-service platform's deployment pipeline, observability integration, or security controls - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be a go-to engineer for one or more of the team's AI tools or platform components - Have shipped multiple production improvements that Docker engineers use every day, with adoption and effectiveness you can point to - Have helped teams outside AI Developer Tools build and run their own tools on the platform - Have taken on larger and more ambiguous work as your scope grows, and helped newer engineers do the same Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $160,900 – $260,700 + equity ______________________________________________________________________ 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; 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. _______________________________________________________________________ Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools. As a Staff Engineer you will own the technical design and delivery for two areas: AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team. RESPONSIBILITIES Technical Leadership and Architecture - Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap - Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions - Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt - Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools - Design reliable, scalable infrastructure for hosting AI agents and developer tools - Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit - Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals Systems Design and Implementation - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days - Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization - Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management - Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling Strategic Impact and Innovation - Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build - Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction - Improve AI tool performance, cost efficiency, and developer experience through architectural improvements - Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them - Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards Leadership and Mentorship - Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices - Lead design reviews and raise the quality of design and code reviews across the team - Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on - Help the team turn good individual AI-assisted engineering practice into shared workflows and controls - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. QUALIFICATIONS REQUIRED - 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale - Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Track record of designing and building scalable distributed systems and developer-facing platforms - Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience designing developer tools, platform systems, or internal tools that other teams rely on - Track record of clarifying requirements and constraints with stakeholders before committing to a design - Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority - Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs - Clear written and spoken communication suited to a remote, async-first company - Track record of mentoring other experienced engineers - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience evolving an internal platform or tool into a widely adopted, production-grade service - Knowledge of security, compliance, and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date - Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Get hands-on with the team's services and ship a useful production change - Shadow on-call and learn the operational profile of the team's services - Work with the Senior Manager to agree on initial technical priorities FIRST 90 DAYS - Lead the technical framing and delivery plan for one significant problem, from requirements through to production - Document the architecture, technology choices, and integration patterns for that work, including ADRs - Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant) - Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management - Lead design reviews for your area of the roadmap and begin mentoring other engineers - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker - Deliver at least one material outcome that spans multiple teams or systems - Have multiple production AI tools demonstrating value across Docker's engineering organization - Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction - Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact - Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people Docker considers sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $170,350 – $275,550 + equity ______________________________________________________________________ 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

Опыт работы от 6 лет, включая Copilot Studio и Azure AI Foundry. Знание архитектуры AI-агентов, паттернов проектирования и промпт-инжиниринга.

• Запуск и развитие канадской версии iGaming-платформы. • Управление AI-агентами и автоматизация процессов.

• Запуск и развитие канадской версии iGaming-платформы. • Управление AI-агентами и автоматизация процессов.

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $310,000 — $360,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - United States What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $225,000 — $265,000 USD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Areta is looking for an AI Engineering Intern Investment Banking to build and maintain internal tools, workflows, automations, and system integrations for deal execution and operations.

Location: Vladivostok Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.   For more information, visit xsolla.com.   ABOUT YOU We are looking for a Junior Developer (AI Engineering) to join the Xsolla Partner Network (XPN) team, a platform that connects game studios and publishers with content creators. The position involves participation in all stages of work on an automated content generation system: from stabilising the existing vertical video pipeline for YouTube Shorts, TikTok and Instagram Reels to developing the agentic architecture, launching the virtual AI creator direction and building analytics on the results. Working with the team means applying cutting-edge generative models and agentic tools to a real production product every day, seeing the direct effect of your work in content metrics, and learning from the inside how the games industry, the creator economy and content-driven game promotion work. The developer will work with a live system that has a real audience and measurable results, make technical decisions independently, build expertise in generative AI and take on the role of the project's technical owner as it grows. Responsibilities Take over the existing vertical video generation pipeline (script → voiceover → visuals → subtitles → editing → auto-posting → tracking links) for YouTube Shorts, TikTok and Instagram Reels, understand it from the docs and code, and bring it to stable operation. Grow the pipeline: improve content quality and virality, scale up generation volume, reduce cost and turnaround time per video. Keep track of new generation models and services (video, image, voice, LLM), test them quickly and replace outdated parts of the pipeline with better or cheaper ones. Launch and develop the virtual AI creator direction: a consistent character, voice, style and content plan. Design and improve agents: write and debug prompts and sub-agent roles, validation between phases, context and cost control. Build a dashboard for running generation and tracking content analytics (views, clicks, conversions, cost per video). Automate publishing: platform integrations, posting from mobile devices, scaling channels. Write clean, testable, documented code, including unit and integration tests. Requirements Solid Python, basic bash. Hands-on experience with LLM APIs (Claude, OpenAI, etc.) and agentic pipelines: a real project, pet project or hackathon entry you can show and talk through. Experience using Claude Code, Cursor or similar tools as a working environment, not just as autocomplete. Understanding of prompt engineering basics: defining an agent's role, limiting context, getting stable structured output. Understanding of Git, team development and Docker basics. Ability to work with REST APIs and webhooks, basic understanding of databases (SQL). Understanding of vertical content: games, creators, streams, TikToks, Shorts, how video discovery works, what shadowbans are, how mobile posting farms are set up. A big plus if this is your hobby: your own channel, editing, streaming, experiments with AI generation. Ownership: the ability to take a task end to end and deliver a result without external supervision. Initiative: your own proposals on improving the pipeline, new models and automation, and the readiness to implement them yourself. Ability to figure out someone else's system from code and documentation, reconstruct the logic and ask the right questions. Independence in technical decisions and openness in communication: flag problems immediately. Product thinking: measuring results by content metrics (views, retention, clicks) and cost per video. Ability to explain the system's capabilities and limitations to non-technical colleagues. Experimental mindset: fast hypothesis testing and the willingness to drop what did not work. Desire to grow with the project: from stabilising the current pipeline to becoming its technical owner. English at the level of reading technical documentation (Intermediate+). Nice to have Experience with video and image generation via API ( fal.ai , Kling, Runway, Seedance, Nano Banana, etc.), TTS and speech recognition (Whisper and similar). ffmpeg: assembly, normalisation, subtitles, overlays. Experience building reliable calls to paid APIs: retries, idempotency, cost tracking. n8n or other workflow tools. Telegram bots, YouTube / TikTok / Instagram / Discord APIs. Android / mobile device automation. Supabase or PostgreSQL. Experience with GCP, Docker, Kubernetes. Observability and monitoring (Datadog, OpenTelemetry). Your own channel, pet projects, open-source experience or hackathon participation. Benefits   Convenient working tools: New Mac laptop and any other necessary equipment for your efficient work. Google Workspace, Atlassian, Jira, Slack   Professional growth: Exchange of experience between employees within the company Opportunity for professional growth within the company and department Obtaining expertise in various areas and products of the company   More perks Possibility of flexibility working Access to the corporate library No dress code Comfortable and new office environment The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

Location: Berlin Office; Norway; Latvia; Netherlands; Hungary; Portugal; Poland; Serbia; Germany; Austria; Lithuania; Ireland; United Kingdom; Spain Workplace: Remote The AI orchestration of your wildest imagination. n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact. Since our founding in 2019, we’ve grown into a diverse team of over 260 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve: - Cultivated a community of more than 650,000 active developers and builders - Earned 190K+ GitHub stars, making us one of the world’s Top 40 most popular projects - Backed by top investors, from Sequoia’s first German seed to our SAP's recent strategic investment - bringing us to a $5.2bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register http://app.n8n.cloud/register. We’re in a defining moment of an incredible journey. Come and build with us. 🎯 YOUR MAIN GOAL WILL BE TO TURN N8N’S INTERNAL AI AND AUTOMATION CAPABILITIES INTO SOMETHING EVERY FUNCTION CAN CONFIDENTLY USE, BUILD WITH, AND LEARN FROM. To make that happen, you’ll create the programs, experiences, and foundations that help teams across n8n build their AI and automation fluency: DRIVE HANDS-ON ENABLEMENT - Run weekly, role-specific workshops, prioritizing less-technical functions such as Legal and Customer Support. - Lead hands-on sessions where you build live alongside teams, helping them turn real workflows and challenges into working automations. - Run Build Along Office Hours and Bounty Hunts that give teams regular opportunities to learn, experiment, and solve problems together. - Help teams identify useful automation opportunities, understand the process they are changing, and decide when to reuse an existing solution, build themselves, or involve the Automation team. OWN DOGFOODING & EXPERIMENTATION - Own our monthly Dogfooding Day end-to-end, from planning and coordination through execution and follow-up. - Design and run hackathons and other experimentation initiatives that encourage teams to explore new ways of working with AI and automation. - Turn learnings and outputs from these initiatives into reusable assets that help other teams move faster. SCALE AI FLUENCY & COMMUNITY - Own periodic AI fluency survey cycles alongside the People team and help calibrate what fluency means across different functions. - Build visibility around internal wins and reusable solutions so teams can learn from what others have already created. - Identify and support champions across functions, informally leading the emerging Guild and helping automation knowledge spread across the company. ENABLE SAFE, REUSABLE AUTOMATION - Act as product owner for our internal “safe playground,” partnering with IT, Security, Data, and Solutions Engineering on access, credentials, environments, and requirements. - Turn outputs from workshops and office hours into reusable templates and resources that teams can easily discover and adopt. - Actively help teams reuse existing solutions rather than reinventing them, making automation more accessible and scalable across n8n. - Check whether the things built are still in use four weeks later; provide evidence that teams reuse existing assets and can make routine changes without handing everything back to the Automation team. REQUIREMENTS MUST-HAVES - 🛠️ Practitioner-level n8n fluency: You’ve built real, meaningful automations in n8n and are comfortable building live alongside others. - 🎓 Technical enablement experience: You’ve run structured, recurring enablement programs such as workshops, office hours, or build-alongs. - 🤝 Non-technical audience expertise: You have a strong track record of helping non-technical teams understand, adopt, and confidently use technical tools. - 🏗️ Cross-functional ownership: You’re comfortable partnering with IT, Security, and Data teams to define and own requirements around access, credentials, and environments without needing to implement the infrastructure yourself. - 🌍 CET overlap: You’re based in a time zone that gives you strong overlap with Central European working hours, within a couple of hours of Berlin. - 💬 English fluency: You have fluent or near-native English and can communicate clearly and confidently with audiences ranging from individual contributors to senior stakeholders. NICE-TO-HAVES - 🌱 Champion programs: You’ve helped build or run an internal ambassador, champion, or community program. - 📊 Fluency measurement: You have experience running capability, fluency, or adoption surveys and turning the results into actionable programs. - 🔐 Access & governance: You’re familiar with access or governance models and have worked with stakeholders responsible for secure environments and tooling. Why join us? At n8n, you’ll have the opportunity to build a brand-new enablement function from the ground up and shape how AI and automation become part of everyday work across the company. You’ll have a direct line to the Head of AI & Automation, high visibility across functions, and genuine autonomy to design an enablement model rather than inherit one. As n8n scales, you’ll become a key connector between the people building our internal automation capabilities and the teams putting them to work. You’ll help create a culture where teams don’t just learn about automation — they confidently build, experiment, share what works, and help others do the same. You’ll join a fast-growing, remote-first company that values autonomy, experimentation, and builder culture, with the opportunity to influence how we scale AI fluency across the organization. Sound like a challenge you’re excited to take on? Apply now — and help us build the future of automation. n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status. We can sponsor visas to Germany; for any other country, you need to have existing right to work. Our company language is English. You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n https://www.notion.so/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35?pvs=21 (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35). Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. BENEFITS - Competitive compensation 💸 – We offer fair and attractive pay. - Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity. - Work/life balance 🏖️ – We work hard but ensure you have time to recharge: - Europe: 30 days of vacation, plus public holidays wherever you are. - US: 20 vacation days, 8 sick days, plus public holidays wherever you are. - Health & wellness 🩺 – - Europe: We provide benefits according to local country norms.* - US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage. - Future planning 💰 – - Europe: We provide pension contributions according to local country norms.* - US: 401(k) retirement plan with a 4% employer match. - Financial security 🛡️ – - Europe: We provide benefits according to local country norms.* - US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones. - Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills. - A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it! - Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description. - Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about. - Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang. *Country and/or State specific details provided in your employment agreement.