platform software engineer

Insify

<div>
 
 About Insify
 
 
 We are a high-growth scale-up backed by &euro;43M in total funding from world-class investors like Accel, Munich Re Ventures, and Formula 1 champion Nico Rosberg. While we started our journey five years ago in the Netherlands, we have since expanded into France and Germany, and we&rsquo;re just getting started. Our mission is to dominate the European market and become a global leader in AI-powered SME insurance.
 
 
 We aren't just building a company; we&rsquo;re leading a revolution. Our culture is intense, high-stakes, and mission-driven. We hire smart, ambitious "owners" who possess a relentless drive to win. This is an environment for those who thrive on challenges, value intellectual honesty, and share our mindset of becoming a global category leader.
 
 
 Our founding team consists of seasoned entrepreneurs who have previously built iconic businesses like HelloFresh, Bloomon, and SumUp. We combine that deep fintech and e-commerce expertise with cutting-edge AI to stay ahead of the curve.
 
 
 In this role, your mission is simple but demanding: to take ownership of a meaningful part of Insify&rsquo;s journey and deliver results that move the company forward.
 
 
 We're looking for a Software Engineer with 3+ years of experience to join the Billing team. You'll help design and build a scalable, multi-country billing platform: payment scheduling, invoicing, dunning, fees, taxes and reconciliation across legal entities, products and markets. You'll work shoulder-to-shoulder with product, finance, legal and our insurance carriers (Axeria, Hiscox, HDI, iptiQ, Chubb, Wakam). You'll own systems end-to-end, from the data model to production behaviour, and you'll be the engineer the rest of the company trusts when money is involved.
 
 
 
 What you'll be doing:
 
 
 
 <ul>
 <li>
 Build a billing platform that scales from two countries to six. Make the right abstractions now so adding a new market is a config change, not a rewrite
 </li>
 <li>
 Design and ship core billing capabilities: annual and monthly payment schedules, the Insify platform fee, VAT logic across jurisdictions, fee waiver rules, pro-rata refunds and renewals
 </li>
 <li>
 Own our dunning flow across Adyen (credit card) and Twikey (SEPA): failure classification, retries, settling checks, partial payments and country-specific legal compliance (NL 14-day statutory warning, FR mise en demeure, and whatever comes next)
 </li>
 <li>
 Build resilient integrations with payment, banking and tax providers, and keep them observable, secure and easy to swap out
 </li>
 <li>
 Handle multi-entity invoicing across Insify B.V., Insify Holding B.V., Insify NLD Agent B.V. and the entities we will add as we expand
 </li>
 <li>
 Partner with finance, legal and compliance to turn regulatory and accounting requirements into clean, testable systems. Be the engineer in the room who can credibly push back when something doesn't make sense
 </li>
 <li>
 Set the bar for engineering quality in the billing domain: idempotency, correctness, observability, recoverability. This is a domain where bugs cost real money
 </li>
 <li>
 Own incidents and operational health. When something breaks in billing, the business notices, and you'll be one of the people who fixes it
 
 
 
 
 </li>
 </ul>
 
 What you'll need:
 
 
 
 <ul>
 <li>
 3+ years of professional software engineering experience, ideally with TypeScript and AWS (Lambda, DynamoDB, event-driven architectures)
 </li>
 <li>
 A serious bar for correctness. You think in terms of edge cases, idempotency, consistency, retries, partial states and audit trails. You understand that "mostly works" is not acceptable when money moves
 </li>
 <li>
 Strong fundamentals in distributed systems, data modelling and API design. You can spot the abstraction that will hold up across five countries and four payment providers
 </li>
 <li>
 Comfort with complexity and ambiguity. Billing sits at the intersection of code, accounting, tax and law. You enjoy that instead of running from it
 </li>
 <li>
 Ownership instinct. You think of the system as yours, not as someone else's ticket queue
 </li>
 <li>
 Clear communicator. You can sit with finance, legal or a carrier and translate fuzzy requirements into a working system
 </li>
 <li>
 AI in your workflow. You actively use AI for coding, debugging and tooling to move faster
 
 
 
 
 </li>
 </ul>
 
 Nice to have:
 
 
 
 <ul>
 <li>
 Experience with payment providers (Adyen, Stripe, Mollie, Twikey or similar), SEPA and card payment flows
 </li>
 <li>
 Background in fintech, insurtech, billing, subscriptions or accounting systems at scale
 </li>
 <li>
 Experience expanding a product or platform into new countries, including localisation of payments, tax and invoicing
 </li>
 <li>
 Familiarity with VAT and multi-entity invoicing across EU markets
 </li>
 <li>
 Strong observability instincts (Sentry, Datadog) and a track record of operating
 
 
 
 
 </li>
 </ul>
 
 We offer:
 
 
 
 <ul>
 <li>
 Competitive compensation that reflects responsibility and impact. For mid-level engineer we have a range between 65-85k per year.
 </li>
 <li>
 Trust and autonomy: you&rsquo;ll have real ownership and room to make decisions Space to grow and shape your role as Insify evolves
 </li>
 <li>
 A steep learning curve, with support from experienced teammates
 </li>
 <li>
 The opportunity to share in what we&rsquo;re building, with equity for eligible roles once there&rsquo;s mutual conviction on fit and impact
 </li>
 <li>
 A welcoming, central Amsterdam HQ where we work closely together: shared lunches, dogs in the office, whiteboards, and fun end-of-week drinks
 </li>
 <li>
 An international, ambitious team that enjoys building meaningful things together
 
 
 </li>
 </ul>
</div>

Software Engineer, Payments Platform

Adyen

<div>
 
 This is Adyen
 
 
 
 Adyen provides payments, data, and financial products in a single solution for customers like Facebook, Uber, H&amp;M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
 
 
 For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. The people of Adyen are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
 
 
 
 Unified Platform
 
 
 
 The Unified Platform Is At The Heart Of Adyen&rsquo;s Infrastructure, Bringing Together Accounting, Reporting, Billing, Pricing, Reconciliation, And Configuration Into One Streamlined Experience. It Enables Us To Stay Agile And Innovative While Running a Scalable, Efficient Business. As Part Of This Initiative, We&rsquo;re Rethinking Five Core Product Areas
 
 
 <ul>
 <li>
 Platform experience &ndash; Creating a unified and intuitive backend experience across Adyen products
 </li>
 <li>
 Accounting systems &ndash; Defining a cohesive and high-performing financial architecture
 </li>
 <li>
 Reporting &amp; reconciliation &ndash; Making financial data more accurate, accessible, and satisfying for customers and regulators
 </li>
 <li>
 Billing &amp; pricing infrastructure &ndash; Simplifying pricing and automating invoicing at scale
 </li>
 <li>
 Observability &amp; tooling &ndash; Strengthening visibility and control of money movement through advanced tooling
 
 
 </li>
 </ul>
 We&rsquo;re hiring Software Engineers at both Mid and Senior levels, and have several teams actively looking for new colleagues. While all roles share a strong technical foundation, each team brings a unique focus in scaling our unified platform, We'll explore the best team fit together throughout the interview process.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Work on complex technical projects from requirements analysis through design, implementation, testing and launch into production.
 </li>
 <li>
 Be hands-on and contribute to the implementation.
 </li>
 <li>
 Identify and improve parts of the platform to make it more robust and scalable.
 </li>
 <li>
 Bring your own point of view on best engineering practices.
 </li>
 <li>
 Your code will be used at scale and you are expected to think in that mindset when building features.
 </li>
 <li>
 We launch fast and iterate often. Concretely, this means that within your first few weeks, you will bring live functionalities that impact many merchants and shoppers.
 </li>
 <li>
 Build APIs and tooling according to quality principles such as performance and code quality.
 </li>
 <li>
 Collaborate across teams and time zones to get projects over the finish line.
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Familiar with complex large scale distributed systems.
 </li>
 <li>
 You have experience with Java, Web Services, REST Apis, Webhooks and SQL/PostgreSql.
 </li>
 <li>
 You have a good understanding of Software Engineering practices and interest in product knowledge.
 </li>
 <li>
 You enjoy working in a cross-functional team with roles like Data Science, Frontend, and Product.
 </li>
 <li>
 You value involving other people to hear different perspectives.
 </li>
 <li>
 You have an experimental mindset with a launch fast and iterate mentality.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 5+ years of experience in software development industry in a fast paced tech environment
 </li>
 <li>
 Full professional proficiency in English
 </li>
 <li>
 This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.
 
 
 </li>
 </ul>
 
 Our Diversity, Equity and Inclusion commitments
 
 
 
 Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you&rsquo;re from, we welcome you to be your true self at Adyen.
 
 
 Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application.
 
 
 
 What&rsquo;s next?
 
 
 
 Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don&rsquo;t be afraid to let us know if you need more flexibility.
</div>

Software Engineer (Java) - Unified Platform

kaiko.ai

<div>
 
 About Kaiko.ai
 
 
 
 Kaiko is building a next-generation agentic clinical AI assistant that helps clinicians reason across patient data, guidelines, and diagnostics.
 
 
 Healthcare decisions are rarely made by a single person or from a single data source. kaiko's assistant maintains longitudinal patient context across encounters, clinicians, and institutions, enabling collaboration, second opinions, and complex diagnostic workflows. The system is designed to operate safely in real clinical environments, with human oversight, auditability, and regulatory alignment at its core.
 
 
 Our assistant core supports broadly applicable clinical tasks such as patient data navigation, guideline interaction, multimodal interaction (chat and voice), and care coordination. On top of this foundation, we are developing specialized diagnostic agents in areas such as oncology, radiology, and pathology.
 
 
 We build in close collaboration with leading hospitals and research centers, including the Netherlands Cancer Institute (NKI). kaiko is a well-funded company with a growing international team, operating from Zurich and Amsterdam.
 
 
 
 About The Role
 
 
 
 As an ML Platform Engineer, you'll help architect, scale, and evolve the infrastructure that powers kaiko's foundation-model training and serving across the full ML lifecycle: from compute orchestration that runs large-scale training jobs, through experiment tracking and model registry, to GPU-backed serving in production.
 
 
 The Data &amp; AI Platform team owns the foundation underneath kaiko's training and serving workloads: the orchestration and distributed compute layer (Dagster + Ray on Kubernetes), the storage layer (Hammerspace), and the observability that keeps them reliable. We support both research, with large-scale training workloads on open-weight MoE models in the hundreds-of-billions to trillion-parameter range, and product, with the engineering teams building kaiko's clinical applications.
 
 
 Today, our platform is built around large-scale training. The next frontier is closing the loop: building the model lifecycle layer (experiment tracking, registry, versioning, and GPU-backed serving) that lets our trained models move reliably into product. You'll be part of the team that gets us there.
 
 
 You'll work closely with both research and product engineering to understand what the platform needs to deliver, and own the engineering of how. You'll contribute to the platform's evolution across both training and serving dimensions, helping translate team needs into reliable, scalable infrastructure.
 
 
 You will be based in either The Netherlands or Switzerland, with the expectation of spending at least 50% of your time at the office.
 
 
 
 Some areas of responsibility
 
 
 
 <ul>
 <li>
 Build and evolve the infrastructure that makes ML development fast, reliable, and observable: from IaC to CI/CD to Kubernetes-based workload orchestration.
 </li>
 <li>
 Contribute to the compute orchestration layer: help scale GPU workloads across heterogeneous on-prem and cloud clusters using Kubernetes, Ray, and advanced GPU scheduling technologies such as KAI-Scheduler.
 </li>
 <li>
 Support hybrid and multi-cloud strategies that balance performance, compliance, and cost, including the Hammerspace storage rollout.
 </li>
 <li>
 Own and evolve parts of the AI Factory: the Dagster-based orchestrator and its Ray integration that training jobs depend on.
 </li>
 <li>
 Build and maintain the model lifecycle layer: experiment tracking, model registry, versioning, and GPU-backed serving infrastructure, so models trained on our clusters move reliably into production.
 </li>
 <li>
 Partner with both research and product engineering to understand platform requirements and translate them into shared infrastructure that works across use cases.
 </li>
 <li>
 Bring engineering rigour to a fast-moving stack: lineage, reproducibility, ownership boundaries, and documentation that lets the team move quickly without losing track.
 
 
 </li>
 </ul>
 
 About You
 
 
 
 <ul>
 <li>
 2-5 years of experience in production ML platform engineering or ML Ops role.
 </li>
 <li>
 Hands-on experience with Kubernetes, Helm, Terraform, Docker, and CI/CD tooling (ArgoCD, GitHub Actions, or comparable). Comfortable with modern observability stacks (Grafana, Prometheus, Loki, or similar).
 </li>
 <li>
 Compute orchestration at scale. Production experience scheduling GPU workloads on Kubernetes, Ray, or comparable, or strong motivation to grow into this quickly.
 </li>
 <li>
 ML infrastructure exposure. Hands-on experience with Linux and NVIDIA GPU environments, including multi-node training stacks and the networking that connects them (InfiniBand or comparable). You have a feel for how researchers and engineers use the platform, not just how it's built.
 </li>
 <li>
 Familiarity with the full ML workflow: training runs, experiment tracking, model registry and versioning (MLflow or equivalent), and model serving. You understand how models move from training to production.
 </li>
 <li>
 Solid software engineering. Python as a baseline; openness to picking up Go or other programming languages where the platform demands it.
 </li>
 <li>
 Collaborative by default. You work across team boundaries (research, product, data engineering) and design interfaces that serve multiple stakeholders without requiring everyone to understand the underlying plumbing.
 
 
 </li>
 </ul>
 
 Nice to have:
 
 
 
 <ul>
 <li>
 Direct experience supporting large-scale foundation-model training or inference, with a working sense of how a run behaves from the platform's perspective: MFU, GPU utilisation, communication overhead, and dataloader stalls on the training side; serving frameworks (vLLM, Triton, TorchServe), KV cache management, and batching strategies on the inference side.
 </li>
 <li>
 Familiarity with lower-level GPU communication and I/O concepts: RDMA, GPUDirect Storage (GDS), GPUDirect RDMA, NCCL, and how these affect training throughput and cluster design.
 </li>
 <li>
 Experience with Kubernetes-native scheduling stacks for accelerator-heavy workloads, such as Volcano, KAI Scheduler, YuniKorn, or similar, so scheduler tradeoffs are understood rather than defaulted to.
 </li>
 <li>
 High performance (parallel) filesystems that feed GPU's with high throughput and low latency (Hammerspace, CEPH, WEKA, VAST).
 </li>
 <li>
 On-prem and hybrid GPU environments, especially in regulated settings (healthcare, finance, public sector).
 </li>
 <li>
 Exposure to MoE architectures or large-scale distributed training, useful for anticipating what future workloads will demand of the platform.
 
 
 </li>
 </ul>
 We are excited to gather a broad range of perspectives in our team, as we believe it will help us build better products to support a broader set of people. If you&rsquo;re excited about us but don&rsquo;t fit every single qualification, we still encourage you to apply: we&rsquo;ve had incredible team members join us who didn&rsquo;t check every box!
 
 
 
 Why kaiko
 
 
 
 At kaiko, we believe the best ideas come from collaboration, ownership and ambition. We&rsquo;ve built a team of international experts where your work has direct impact. Here&rsquo;s what we value:
 
 
 <ul>
 <li>
 Ownership: You&rsquo;ll have the autonomy to set your own goals, make critical decisions, and see the direct impact of your work.
 </li>
 <li>
 Collaboration: You&rsquo;ll have to approach disagreement with curiosity, build on common ground and create solutions together.
 </li>
 <li>
 Ambition: You&rsquo;ll be surrounded by people who set high standards for themselves and others, who see obstacles as opportunities, and who are relentless in their work to create better outcomes for patients.
 
 
 </li>
 </ul>
 
 
 
 In addition, we offer:
 
 
 
 <ul>
 <li>
 An attractive and competitive salary, a good pension plan and 25 vacation days per year.
 </li>
 <li>
 Great offsites and team events to strengthen the team and celebrate successes together.
 </li>
 <li>
 A EUR 1000 learning and development budget to help you grow.
 </li>
 <li>
 Autonomy to do your work the way that works best for you, whether you have a kid or prefer early mornings.
 </li>
 <li>
 An annual commuting subsidy.
 
 
 </li>
 </ul>
 
 Our interview process
 
 
 
 Our interview process is designed to assess mutual fit across skills, motivation, and values. It typically includes the following steps:
 
 
 <ul>
 <li>
 Screening call: A short conversation to align on your motivation, career goals, and initial fit for the role.
 </li>
 <li>
 Coding assessment &amp; debrief: You'll complete a time-limited coding exercise, started at a time of your choosing. Afterwards, you'll join a live session with members of our team to walk through your solution, explain your reasoning, and discuss any trade-offs you made.
 </li>
 <li>
 Technical interview: A deep dive into your problem-solving approach through a technical challenge, case study, or role-specific scenario.
 </li>
 <li>
 Onsite meeting (optional): You&rsquo;ll meet team members across functions to explore collaboration dynamics, team fit, and day-to-day context.
 </li>
 <li>
 Final executive conversation: A discussion with a member of the executive team focused on long-term alignment, cultural fit, and shared expectations for impact.
 </li>
 </ul>
</div>

ML Platform Engineer

Check

<div><h1 class="jobSectionHeader">In a nutshell.</h1>
As our Security Engineer, you make sure our platform, infrastructure and data stay secure as we grow. You identify vulnerabilities before they become problems, and you build the processes and safeguards that keep security top of mind across the entire Product team.
You're on the Product team, contributing your security expertise. This role is for someone who stays sharp on emerging threats and knows how to get engineers to build securely without slowing them down.<h3 class="jobSectionHeader">
Our Tech Stack.</h3>
The iOS application is built 100% with Swift, with a mix of SwiftUI and UIKit. We use REST APIs to connect to our backend. The CI/CD pipelines run using Bitrise.
Android is built natively with Kotlin. Next to the customer application, we have two internally facing applications. One mobile React Native application and one web-based, built in Typescript and Next.JS.
Our backend stack is heavily based around Python, with our main API written in that language, as well as several microservices. For updating our fleet in real-time, we use a microservice which is written in Rust. This is all hosted and managed in-house, by running two Kubernetes clusters with Helm as our package manager.<h1 class="jobSectionHeader">
The role.</h1><ul><li>
Make sure our APIs are secure and that no data is exposed where it shouldn't be.</li><li>
Keep our infrastructure secure, including how we deploy and run software on Kubernetes.</li><li>
Run security audits, penetration tests, and vulnerability assessments across our platform.</li><li>
Work day-to-day with our software engineers, picking up your own tickets and improving security together with the people building the product.</li><li>
Own data governance and make sure we stay GDPR and are legally compliant.</li><li>
Define and maintain security policies and training that apply company-wide.</li><li>
Respond to and lead investigations on security incidents when they occur.</li><li>
Stay on top of emerging threats and vulnerabilities relevant to our stack and industry.</li></ul><h1 class="jobSectionHeader">
Requirements.</h1><ul><li>
HBO or higher in software engineering, computer science, security, or a related field.</li><li>
2+ years of experience in a security engineering or similar role.</li><li>
Hands-on experience with Kubernetes and securing modern cloud infrastructure.</li><li>
Basic knowledge of Python and TypeScript - you don't need to be an expert, but you should be able to read and understand code.</li><li>
Experience with GitHub Actions or similar CI/CD tooling.</li><li>
Experience with databases and SQL.</li><li>
Fluent English; Dutch is a plus.</li></ul><h3 class="jobSectionHeader">
Ready to join the ride?</h3>
If you're excited about staying one step ahead and keeping our platform secure, we'd love to hear from you.</div>

Security Engineer

Workato

<div>
 
 About Workato
 
 
 
 Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato&rsquo;s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com
 
 
 
 Why join us?
 
 
 
 Ultimately, Workato believes in fostering a
 
 flexible, trust-oriented culture that empowers everyone to take full ownership of their roles
 
 . We are driven by
 
 innovation
 
 and looking for
 
 team players
 
 who want to actively build our company.
 
 
 But, we also believe in
 
 balancing productivity with self-care
 
 . That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
 
 
 If this sounds right up your alley, please submit an application. We look forward to getting to know you!
 
 
 
 Also, Feel Free To Check Out Why
 
 
 
 <ul>
 <li>
 Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;
 </li>
 <li>
 Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world
 </li>
 <li>
 Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
 </li>
 <li>
 Quartz ranked us the #1 best company for remote workers
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 We are looking for a
 
 Staff AI Engineer
 
 to play a key role in building the core of our AI platform. In this position, you will design and develop production-grade systems that power intelligent automation, agentic workflows, and large-scale retrieval services. This is a highly technical, hands-on role that involves close collaboration with product and platform teams to transform advanced AI concepts into reliable, scalable, and secure solutions used across our enterprise ecosystem. You will also be responsible to:
 
 
 <ul>
 <li>
 Design, build, and maintain AI-powered services and APIs, leveraging LLMs (OpenAI, Anthropic, Qwen, OSS models) and custom ML models.
 </li>
 <li>
 Develop an enterprise-grade agentic framework that enables orchestration, retrieval, and collaboration between multiple AI agents.
 </li>
 <li>
 Implement and optimize knowledge retrieval systems and agentic search capabilities using vector databases such as Qdrant and ElasticSearch.
 </li>
 <li>
 Write well-structured, efficient, and testable Python code for production services, experimentation, and internal developer tools.
 </li>
 <li>
 Build and maintain shared Python libraries and SDKs used across multiple applications and microservices.
 </li>
 <li>
 Collaborate with cross-functional teams on architecture, internal protocols, and API standards to ensure consistency and reliability across the platform.
 </li>
 <li>
 Develop and enhance monitoring, validation, and observability for production-grade AI solutions.
 </li>
 <li>
 Drive the full software development lifecycle - from design and implementation to deployment, monitoring, and continuous improvement.
 </li>
 <li>
 Identify and resolve performance bottlenecks, reliability issues, and scaling challenges in complex, data-intensive environments.
 </li>
 <li>
 Participate in code reviews and technical discussions, mentoring other engineers and contributing to a culture of excellence.
 
 
 </li>
 </ul>
 
 Example Projects
 
 
 
 <ul>
 <li>
 Building an evaluation and observability framework for AI model performance and reliability.
 </li>
 <li>
 Developing an agentic orchestration platform that enables collaboration among multiple AI agents and tools.
 </li>
 <li>
 Implementing semantic retrieval and agentic search capabilities over large enterprise knowledge bases.
 </li>
 <li>
 Designing AI services that process and reason over high-volume real-world data at scale.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Qualifications / Experience / Technical Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
 </li>
 <li>
 5+ years of experience as a Software Engineer, with strong proficiency in Python.
 </li>
 <li>
 Proven track record of building and maintaining production-grade systems using Python.
 </li>
 <li>
 Strong understanding of distributed systems, API design, and data-driven architectures.
 </li>
 <li>
 Experience with relational and non-relational databases (PostgreSQL, Elastic, Qdrant, or similar).
 </li>
 <li>
 Familiarity with AI/ML system design, including LLM integration and evaluation pipelines.
 </li>
 <li>
 Knowledge of DevOps and observability practices (CI/CD, monitoring, metrics, and model validation).
 </li>
 <li>
 Python
 </li>
 <li>
 FastAPI
 </li>
 <li>
 LLM APIs (OpenAI, Anthropic, Qwen, OSS)
 </li>
 <li>
 LiteLLM
 </li>
 <li>
 Qdrant
 </li>
 <li>
 PostgreSQL
 </li>
 <li>
 ElasticSearch
 </li>
 <li>
 Langfuse
 </li>
 <li>
 Kubernetes
 </li>
 <li>
 GitHub Actions
 </li>
 <li>
 ArgoCD
 
 
 </li>
 </ul>
 
 Preferred Skills
 
 
 
 <ul>
 <li>
 Experience working with multiple LLM providers (OpenAI, Anthropic, Qwen, open-source models).
 </li>
 <li>
 Background in developer platforms or AI infrastructure services.
 </li>
 <li>
 Familiarity with vector databases, semantic retrieval, and knowledge graph architectures.
 </li>
 <li>
 Exposure to Langfuse, LiteLLM, LangChain, or similar frameworks.
 </li>
 <li>
 Experience developing enterprise-scale SaaS or distributed backend systems.
 </li>
 <li>
 Contributions to open-source projects in Python, AI, or infrastructure engineering.
 
 
 </li>
 </ul>
 
 Soft Skills / Personal Characteristics
 
 
 
 <ul>
 <li>
 Excellent communication skills, with the ability to convey complex technical ideas clearly to both technical and non-technical audiences.
 </li>
 <li>
 Collaborative and proactive approach, comfortable working across teams in a dynamic environment.
 </li>
 <li>
 Strong analytical and problem-solving abilities, with a focus on continuous improvement and innovation.
 </li>
 <li>
 Curiosity and a genuine interest in emerging AI technologies and modern backend architectures.
 
 
 </li>
 </ul>
 
 (REQ ID: 2460)
 
</div>

Staff AI Engineer

Xccelerated | Part of Xebia

<div>
 
 Data Engineer
 
 
 
 
 
 
 Location:
 
 Netherlands (hybrid)
 
 
 
 Language:
 
 English-speaking environment
 
 
 
 
 
 Are you a
 
 Data Engineer based in Europe
 
 who wants to take the next step in your career?
 
 
 Would you like to
 
 relocate to the Netherlands
 
 and work on a modern cloud-based data platform while accelerating your growth through structured, high-level training?
 
 
 
 
 
 At
 
 Xccelerated
 
 , we are looking for
 
 Medior Data Engineers
 
 to help build a
 
 state-of-the-art data platform on Google Cloud Platform (GCP)
 
 . You&rsquo;ll work alongside experienced consultants and follow an intensive training program designed to rapidly strengthen your technical and professional skills.
 
 
 
 
 
 💡 Why join Xccelerated?
 
 <ul>
 <li>
 Build a
 
 modern data platform from scratch
 
 on Google Cloud Platform
 </li>
 <li>
 Work on real client projects while continuously improving your skills
 </li>
 <li>
 Receive
 
 60+ days of structured technical training
 
 led by experienced Tech Leads
 </li>
 <li>
 Collaborate with international engineering and analytics teams
 </li>
 <li>
 After one year, transition to a
 
 direct contract with the client organization
 
 </li>
 </ul>
 
 
 
 
 🚀 Your role as a Data Engineer
 
 
 As a Data Engineer at Xccelerated, you will help lay the foundation for data-driven decision making.
 
 
 You will:
 
 <ul>
 <li>
 Design, build and maintain
 
 scalable data pipelines
 
 on GCP
 </li>
 <li>
 Develop components of a modern data platform supporting analytics and machine learning use cases
 </li>
 <li>
 Ensure reliable integration between data sources, pipelines and data models
 </li>
 <li>
 Work closely with engineering, analytics and cloud teams on architecture and implementation
 </li>
 <li>
 Continuously improve data quality, reliability and performance
 </li>
 </ul>
 
 
 
 
 👩 💻 Who we&rsquo;re looking for
 
 
 You&rsquo;re a hands-on engineer who enjoys learning by doing and working on meaningful data challenges.
 
 
 You bring:
 
 <ul>
 <li>
 A Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data, Cloud or a related field
 </li>
 <li>
 
 3&ndash;4 years of experience
 
 as a Data Engineer (or similar role)
 </li>
 <li>
 Strong skills in
 
 Python
 
 and
 
 SQL
 
 </li>
 <li>
 Experience with at least one public cloud:
 
 GCP, AWS or Azure
 
 </li>
 <li>
 Familiarity with modern data tools such as
 
 Spark, Databricks or Airflow
 
 </li>
 <li>
 A proactive mindset and willingness to
 
 relocate to the Netherlands
 
 </li>
 </ul>
 
 
 
 
 🎁 What we offer
 
 
 At Xccelerated, we offer more than just a job &mdash; we offer a
 
 career accelerator in Data &amp; Cloud
 
 .
 
 <ul>
 <li>
 Competitive salary based on experience
 </li>
 <li>
 
 Relocation support
 
 for candidates moving to the Netherlands
 </li>
 <li>
 25 vacation days
 </li>
 <li>
 Intensive onboarding with a hands-on technical bootcamp
 </li>
 <li>
 Weekly technical training, mentoring and innovation days
 </li>
 <li>
 Company laptop and modern tooling
 </li>
 <li>
 Great lunches, excellent coffee and a well-stocked snack bar
 </li>
 <li>
 Hybrid working model and an international team
 </li>
 </ul>
 
 
 
 
 🌍 About Xccelerated
 
 
 Xccelerated (part of the
 
 Xebia Group
 
 ) is a tech accelerator focused on developing the next generation of Data &amp; Cloud professionals.
 
 
 You&rsquo;ll work
 
 four days per week
 
 on real client projects and spend
 
 one day per week
 
 on structured training, coaching and innovation. After one year, you&rsquo;ll have the opportunity to join one of our partner companies directly.
 
 
 
 
 
 📩 Interested in relocating to the Netherlands?
 
 
 We&rsquo;d love to hear from you.
 
 
 📧 Contact:
 
 Samantha Goncalves
 
 &ndash; sgoncalves@xccelerated.io
 
 
 📞 Phone: +31 6 13889770
 
 
 
 
 
 📋 Application process
 
 <ol>
 <li>
 Introductory interview with one of our recruiters
 </li>
 <li>
 Technical assessment &amp; presentation with one of our Tech Leads (remote)
 </li>
 </ol>
 
 We aim to complete the process within
 
 1&ndash;3 weeks
 
 , depending on availability.
 
</div>

Data Engineer (Relocation to the Netherlands)

Optics11

<div>We are expanding our team with a Data &amp; ML Infrastructure Engineer who will take ownership of the platform that enables data ingestion, processing, storage, and machine learning workflows across multiple products. Operating at the intersection of data science, software engineering, and cloud infrastructure, you will build the foundations and ensure that our ML systems are scalable, reproducible, and production ready.
In this role, you will design, implement, and continuously improve a cloud-agnostic data and ML platform that supports multiple products and teams. You will be responsible for platform reliability, scalability, and cost-efficiency, while providing data scientists and ML engineers with the tools and infrastructure to efficiently develop, train, validate, and deploy machine learning models. You will serve as a technical bridge between the data science and IT/infrastructure teams, translating requirements into robust and maintainable systems.
This role includes ownership of an existing vendor-delivered platform and its evolution into a fully automated, reproducible, and multi-product ML platform.<h4 class="jobSectionHeader">
Key Responsibilities:</h4><ul><li>
Design, implement, and maintain the data and ML platform infrastructure, including systems for data ingestion, storage, processing, and training.</li><li>
Ensure high availability, reliability, and uptime of the platform, as it is critical to the business value proposition.</li><li>
Maintain and evolve vendor-delivered platform components and ensure long-term maintainability and independence.</li><li>
Build and maintain data workflows, including tools for dataset versioning, experiment tracking, and model lifecycle management across multiple products.</li><li>
Enforce DevOps / MLOps practices, including CI/CD pipelines, Infrastructure-as-Code, and automated workflows.</li><li>
Develop cloud-agnostic and containerized solutions that can run across public and private cloud environments within EU constraints.</li><li>
Optimize data storage, lifecycle policies, and cost efficiency, including tiered storage and retention strategies.</li><li>
Implement and maintain monitoring and alerting systems (e.g., Prometheus, Grafana) for pipelines, infrastructure, and resource usage.</li><li>
Ensure data governance, security, and compliance, including access control, audit logging, and anonymization requirements.</li><li>
Collaborate closely with data scientists, ML engineers, and IT teams to deliver infrastructure that meets operational needs.</li><li>
Manage resource and cost controls, including budgets, approvals, and tracking.</li><li>
Contribute to documentation, operational runbooks, and onboarding materials for the platform.</li></ul><h4 class="jobSectionHeader">
Why Join Us?</h4><ul><li>
Join one of Europe&rsquo;s most promising deep-tech scale-ups.</li><li>
Shape the future of a rapidly growing multidisciplinary R&amp;D organization.</li><li>
Competitive salary and benefits package.</li><li>
Enjoy regular team activities and company events.</li><li>
Fresh team lunches provided3 times/ week.</li></ul><h4 class="jobSectionHeader"> 
Required Qualifications:</h4><ul><li>
MSc or equivalent with 5+ years&rsquo; industry experience in Computer Science, Data Engineering, Machine Learning, or a related field.</li><li>
Strong experience with data platforms, cloud infrastructure, and distributed systems (AWS, GCP, Azure).</li><li>
Proven experience with Infrastructure-as-Code (e.g., Terraform) and automated deployments.</li><li>
Experience with ML platforms and tools (MLflow, Feast, DVC, DataHub or equivalent).</li><li>
Experience with AWS Sagemaker or Google Vertex AI platforms.</li><li>
Experience with databases (MongoDB, PostgreSQL, InfluxDB or equivalent).</li><li>
Experience with message brokers and streaming systems (Kafka, RabbitMQ or equivalent).</li><li>
Hands-on experience with containerization (Docker/OCI) and orchestration (Kubernetes or similar).</li><li>
Experience with CI/CD systems (e.g., GitLab CI).</li><li>
Programming skills in Python.</li><li>
Experience with monitoring and observability tools (Prometheus, Grafana).</li><li>
Understanding of DevOps and MLOps practices.</li><li>
Ability to work across teams and translate requirements into scalable infrastructure solutions.</li></ul>
Nice to Have:<ul><li>
Knowledge of data governance, IAM, and security frameworks.</li><li>
Experience with cost optimization and resource management in cloud environments.</li><li>
Familiarity with multi-tenant or multi-product platform architectures.</li><li>
Experience working with EU data compliance constraints in energy, maritime or defense.</li></ul>
Security &amp; Compliance:
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.</div>

Data & ML Infrastructure Engineer

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