Remote visa sponsorship jobs in the Netherlands

We are building an AI Transformation program that automates real work across the company – support, onboarding, finance, sales operations – with measurable results. As our first AI Data Engineer you build the foundations that make that possible: the data pipelines, integrations, and agentic workflows that turn AI from demos into production systems, plus the measurement layer that proves what they deliver. You report directly to the Director of AI Transformation and work with every department in the company. What you will do Build AI automation (core, ~70%). Design, build, and run agentic workflows and process automations end-to-end: extract and prepare data from source systems (CRM, ticketing, finance, product), orchestrate Azure AI Foundry models in agentic frameworks (durable Azure Functions) with tool-calling and retrieval, write results back into systems of record, and wrap everything in evaluation, monitoring, and guardrails so it keeps working after launch. Own the data plumbing. Build and maintain the pipelines and integrations the AI portfolio depends on – and the baseline/impact measurement data (hours saved, quality metrics) the program reports to the board. Support the analytics estate (~30%). Maintain and extend our Power BI reporting: semantic models, report building, and helping business users answer their own questions. This share is deliberately bounded – the core of the role is building, not servicing tickets. Shape what gets built. Join discovery workshops with departments, assess technical feasibility of automation candidates, and influence the decision per case: build custom, configure Copilot Studio, lean on SaaS-embedded AI, or skip What you bring 4+ years building data pipelines and integrations in production – Python and/or C, SQL, REST APIs; our stack is Azure Data Factory, Azure Functions, Blob Storage, and DuckDB Hands-on experience building agentic solutions with LLM APIs (Azure AI Foundry, OpenAI, Anthropic or similar) – RAG, structured output, tool-calling, agentic frameworks – and testing/evaluating what they produce An AI-native way of working: agentic coding tools (Claude Code, Cursor, Antigravity, GitHub Copilot or similar) are part of your daily workflow, and you can articulate where they accelerate you and where they mislead Working proficiency in Power BI: data modeling, DAX, report design Software engineering discipline: version control, code review, CI/CD, monitoring – you build systems that run unattended Strong communication with non-technical colleagues; comfortable turning a messy process description into a technical design Pragmatism: you ship a working 80% solution and iterate, and you flag when automation is the wrong answer Nice to have Experience in B2B SaaS operations (support, onboarding, CS tooling ecosystems) Copilot Studio / Power Platform, or experience extending SaaS-embedded AI features Familiarity with privacy-aware data handling (GDPR) Dutch language skills (if NL-based) What success looks like 6 months: 2–3 process automations live in production with baselines and measured savings; BI support running through a structured intake with satisfied stakeholders; measurement dashboard feeding the monthly program report. 12 months: A reusable automation platform (shared pipeline patterns, evaluation harness, monitoring) so each new initiative ships faster than the last; contributing technical design to at least one larger process-reengineering initiative. Why this role Ground-floor position in a board-sponsored transformation program with real budget and executive attention. Your work is measured in hours given back to colleagues and results reported at company level – rare visibility for an engineering role. Direct mentorship from a hands-on technical director, and first-hire influence on the tooling, architecture, and standards of everything that follows.

Ready to own it, build it, and grow it? The Mission Publitas turns static, dead PDFs into interactive, shoppable digital content discovery experiences. Our Reach proposition — our consumer portals, including Folders.nl and Promobutler.be in the Benelux and Promozilla portals across ~40 countries — connects millions of shoppers with localized retail deals, flyers, and promotions. It is a core traffic and engagement engine for the company. Your mission as Growth Marketing Manager is to own consumer traffic growth across our portals end to end. You will protect and grow our largest market (Benelux), where the bulk of today's traffic sits, while building a repeatable acquisition playbook to scale our newer Promozilla portals from a standing start. You own every lever that moves consumers to our portals — organic/SEO, social, affiliates and partnerships, paid, and lifecycle/retention. We work ~80% asynchronously and judge you on traffic growth, audience retention, and channel efficiency — not hours on Zoom. What Success Looks Like (Your First 90 Days) We measure outcomes, not tenure. In your first three months: Day 30: You've achieved full campaign continuity with zero disruption to active Benelux flows, and audited traffic sources across the portal network — establishing a clear baseline of what drives volume in each live market and a working relationship with product and development. Day 60: You've identified the highest-yield channel per market and the friction points capping growth (technical, behavioral, or distributional), and shipped your first round of experiments — across organic, paid, social, partnerships, or lifecycle — with early measurable lift. Day 90: Your highest-leverage channels are running predictably in Benelux, and you've drafted and aligned a scalable acquisition playbook to roll out to the nascent Promozilla markets — mapped to the development team's product and UX/UI ETAs for Q3/Q4. Job requirements The DNA of a Growth Marketer at Publitas Founder-Level Ownership: You treat the portal network like your own business. You don't wait for a roadmap to be handed to you — you read the data, uncover the insight, chase down the tracking gap, and make high-impact calls autonomously. A Continuous Growth Mindset: Consumer behavior and search/distribution algorithms shift fast. You treat traffic as a system to be engineered — constantly testing unconventional loops, optimizing channel mix, and treating every performance drop as a data point to dissect and iterate on. High Autonomy, Low Ego: In a remote-first, async environment, the work speaks for itself. You're motivated by solving hard distribution problems, not by synchronous cheerleading, and you're comfortable being judged on the real health of portal traffic and retention. The Non-Negotiables Multi-Channel Traffic Mastery: A proven track record driving consumer traffic at scale across the full mix — organic/SEO (including programmatic/technical SEO), paid social and search, affiliates and partnerships, and lifecycle/retention. You understand B2C shopper psychology and how audiences hunt for promotions. High-Volume B2C / Platform Background: Experience in app-first consumer marketplaces, coupon/deal platforms, news/media publishers, or large-scale e-commerce/affiliate networks. Programmatic & Multi-Market Scaling: You've scaled traffic across many markets or properties and understand how to standardize a playbook and localize it efficiently — rather than rebuilding from scratch per market. AI-First Execution: We do not scale headcount to solve manual problems. A demonstrable track record of using generative AI and automation to scale campaign copy and localization, build programmatic reporting loops, and trigger automated workflows. We are not looking for "AI-curious" — we look for people already using AI to do better work, with tangible impact to show. Flawless Professional English: You collaborate with the global Publitas team in English; your written communication must be exceptional for an async-first team. Dutch — strong plus. What We Offer You to Win Transparent Compensation: A competitive entry-level base salary of €40 000 - €60 000 (geo-bracketed to your location in the EU) with a clear, performance-based path for career progression. True Remote Autonomy: We work 80% asynchronously using Notion and Slack. We don't monitor your screen or count your hours—we trust you to own your delivery targets and manage your day. Global Team Retreats: Working remotely shouldn't mean working isolated. We gather the entire company in inspiring cities across the globe once a year to connect, strategize, and celebrate in person. Premium Workspace & Gear: A top-tier MacBook, high-end remote work accessories, and co-working allowance if you prefer an office environment. Personal Growth Budget: A monthly wellness allowance, an education/course budget to sharpen your SaaS skills, and free access to Kindle and Audible books. Time Off: 25 days of paid vacation plus your local national holidays. At Publitas, we see AI as a core lever for performance, efficiency, and innovation. We expect all team members to actively use AI in their daily work to improve quality, speed, and output. Depending on the role, this ranges from effectively using AI tools in day-to-day workflows to designing and scaling AI-driven systems. We are not looking for candidates who are “AI-curious”; we look for people who already use AI to do better work and can demonstrate tangible impact.

GitLab’s Forward Deployed Engineering team is a field-situated product engineering function focused on strategic customer outcomes, artificial intelligence (AI) adoption, and direct contributions to GitLab’s product. This isn't a traditional field engineering, solutions architecture, or professional services role. As a Staff Forward Deployed Engineer, you'll work closely with customers while maintaining the technical standards and contribution discipline of a Staff-level product engineer. You'll work where strategic customer urgency, complex technical ambiguity, and GitLab product execution intersect. You'll partner directly with strategic customers and teams across Product, Engineering, Support, Site Reliability Engineering (SRE), Solutions Architecture (SA), Customer Success Architecture (CSA), Customer Success Management (CSM), and Professional Services. You'll diagnose and resolve high-impact adoption blockers, contribute production-quality fixes and features, and turn what you learn into repeatable patterns for GitLab and its customers. Why this role exists Strategic customers sometimes encounter challenges that are too broad, deep, urgent, or cross-functional for any single team to own from start to finish. These challenges may involve product gaps, performance degradation, scale bottlenecks, AI governance, adoption blockers, architectural constraints, Git usage patterns, continuous integration and continuous delivery (CI/CD) complexity, application programming interface (API) automation, security requirements, or operational instability. Forward Deployed Engineering provides technical stewardship in these moments. The team doesn't simply observe, report, or escalate. You'll engage directly, diagnose the underlying technical problem, collaborate with the right teams, contribute code or technical solutions where appropriate, and transition the outcome into normal ownership once the customer is stable and the learning can be reused. What you’ll do Product contribution Contribute production-quality code to GitLab’s product and adjacent systems. Develop bug fixes, features, integrations, tooling, and performance improvements when strategic customer outcomes require direct engineering work. Work within GitLab’s product and engineering processes, including issue discovery, merge request creation, testing, review, documentation, and maintainability. Partner with Product and Engineering so customer-driven solutions support long-term product direction rather than becoming one-off customizations. Turn blockers discovered in the field into durable product improvements, reference architectures, documentation, and repeatable implementation patterns. Strategic technical stewardship Engage with strategically important customers when adoption, retention, executive confidence, or public trust is materially at risk. Diagnose complex problems across GitLab product behavior, customer architecture, Git internals, CI/CD workflows, API usage, observability, infrastructure, networking, and cloud environments. Coordinate across Product, Engineering, SRE, Support, SA, CSA, CSM, Professional Services, and customer technical teams to drive resolution from discovery through handoff. Provide recommendations grounded in data, traces, and systems analysis to improve GitLab usage, workflows, automation, and architecture. Create durable outcomes without establishing permanent dependency on Forward Deployed Engineering. AI adoption and agentic software development lifecycle Drive governed, measurable, and production-oriented adoption of GitLab Duo Agent Platform with strategic customers. Identify and resolve AI adoption blockers involving governance, usage controls, auditability, security, compliance, operating models, workflow design, and integrations. Develop customer-safe adoption patterns for the agentic software development lifecycle (SDLC), AI-assisted development, intent-based review, AI governance, and human-in-the-loop software delivery. Partner with Product, Engineering, Field, and Customer Success teams to turn AI adoption learning into reusable guidance and product improvements. Thought leadership Create technical narratives grounded in customer experience and product reality that can help shape the industry’s approach. Contribute to Well-Architected Frameworks, whitepapers, webinars, reference architectures, technical strategy memos, and adoption frameworks. Guide ideas through discovery, formulation, validation, amplification, and adoption across GitLab. Partner with SA, CSA, Product, Engineering, Marketing, Product Marketing Management, CSM, Support, and executive stakeholders to make technical thought leadership a shared company capability. What you’ll bring Staff-level experience building, operating, or improving complex production software systems. Experience contributing to large, mature product codebases with high standards for testing, maintainability, performance, and security. Strong Ruby on Rails or Go experience and the ability to contribute directly to GitLab’s product and adjacent systems. Experience with AI-assisted software development, agentic workflows, AI governance, model evaluation, context management, prompt and workflow design, or AI adoption in enterprise environments. Experience diagnosing complex system behavior across application code, data stores, infrastructure, observability, networking, APIs, and customer usage patterns. Deep knowledge of modern DevSecOps workflows, including Git, merge requests, CI/CD, security controls, compliance needs, and enterprise software delivery. Experience working with strategic customers or senior technical stakeholders in ambiguous, high-impact situations. The ability to coordinate across product, engineering, field, and customer teams without formal authority. Strong written communication and sound judgment, including the ability to create technical narratives and distinguish reusable product work from customer-specific customization. Strongly preferred qualifications Direct experience with GitLab as a platform, including GitLab.com, GitLab Dedicated, or GitLab Self-Managed. Production experience with Ruby on Rails, Go, PostgreSQL, Redis, Sidekiq, Vue, TypeScript, Kubernetes, Docker, Linux, or observability tools. Deep familiarity with Git internals, repository performance, large-scale Git usage patterns, or GitLab Runner behavior. Experience creating technical thought-leadership materials, such as whitepapers, technical talks, architecture frameworks, requests for comments, public technical writing, or internal strategy documents. A background in performance engineering, site reliability engineering, platform engineering, infrastructure engineering, or distributed systems. Experience working in open source or highly asynchronous engineering environments. Technologies and domains Directly relevant technologies and domains include: Ruby on Rails Go AI-assisted development and the agentic SDLC PostgreSQL Redis and Sidekiq Git internals GitLab CI/CD and Runner architecture Kubernetes and containers Terraform Linux, networking, observability, and performance analysis Vue and TypeScript APIs and automation DevSecOps governance, security, and compliance What this role is not This role isn't: A generic field engineering role. A proof-of-concept factory. A replacement for Solutions Architecture, Customer Success Architecture, Customer Success Management, Professional Services, Support, SRE, Product, or Engineering. A customer-specific customization function. Unbilled Professional Services. A requirements-gathering role that only escalates to Product. An AI evangelism role disconnected from product execution. Success measures Success in this role may include: Stabilizing strategic customer adoption or retention risks. Fixing product bugs or contributing features. Removing AI adoption blockers for strategic accounts. Creating reusable implementation patterns and transitioning them to long-term owners. Producing or enabling Well-Architected Frameworks, whitepapers, webinars, or technical narratives. Resolving cross-functional customer challenges without creating permanent dependency on Forward Deployed Engineering. Equipping Product, Engineering, Support, CSA, CSM, Professional Services, and SA teams with better guidance based on learning from the field. Increasing adoption and effective use of GitLab capabilities, especially GitLab Duo and GitLab Duo Agent Platform, in targeted accounts. About the team The Forward Deployed Engineering team connects strategic customer needs with GitLab product execution. The team works directly with customers and across GitLab to resolve complex adoption challenges, contribute durable product improvements, and create reusable technical guidance. Its goal is to stabilize urgent situations, improve the product, and transition ongoing ownership to the appropriate team rather than create a permanent dependency. Ideal candidate profile You're a Staff-level product or platform engineer who can operate in the field without becoming field-only. You're comfortable reading traces, writing production code, debugging architecture, discussing AI governance, leading a customer technical session, opening a merge request, outlining a whitepaper, and coordinating across teams to achieve a strategic customer outcome. You're not simply a strong communicator with technical awareness. You're a credible engineer with the judgment, presence, and narrative ability to turn customer reality into product contributions, adoption guidance, and company-level thought leadership.