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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Platform Engineer - **Company:** Kyndryl - **Location:** Hoofddorp, Netherlands - **Salary:** €5,554.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Engineering, Encodings, Continuous Integration, Information Engineering, Data Security, DevOps, Python (Programming Language), SQL Databases, Systems Integration, Microsoft Power Automate, Large Language Models, AI Platforms, Pyspark, Machine Learning Operations, Terraform, Data Pipelines, Serverless Computing, Databricks - **Published:** September 12, 2026 - **Apply:** https://dejobs.org/x/x/A670555EC9484508BD616B3F8F28B9D0/job/ ## About the Role * Proven experience designing and deploying AI/ML and data engineering solutions on Azure. * Deep understanding of Azure Databricks architecture, including serverless compute capabilities. * Hands-on experience with serverless technologies such as Azure Functions, Event Grid, and Logic Apps. * Proficiency in Python, PySpark, and SQL for data engineering and model integration. * Strong knowledge of CI/CD, MLOps, and Infrastructure-as-Code using Azure DevOps and Terraform. * Solid understanding of cloud cost management, scaling strategies, and workload optimization. * Familiarity with enterprise security, data protection, and compliance requirements for AI workloads. * Ability to design and implement observability, monitoring, and alerting for Databricks Serverless environments. * Integrated Mistral AI large language models (LLMs) into a corporate fintech environment ## Description AI/ML Engineer - Azure Platform Modernization As part of a large-scale platform modernization journey, the organization is strengthening its AI and Machine Learning capabilities to deliver intelligent, secure, and scalable digital solutions on Microsoft Azure. This transformation focuses on embedding enterprise-grade AI capabilities within the platform engineering landscape-enabling automation, improving data security, and accelerating outcomes through responsible AI adoption., The AI/ML Engineer will be responsible for: * Designing and assessing serverless compute architectures for AI workloads. * Implementing scalable Azure Databricks Serverless environments. * Developing and maintaining CI/CD pipelines in Azure DevOps for AI and Databricks workloads. * Ensuring reliability, observability, monitoring, and optimization of Databricks and serverless services. * Collaborating closely with Data Science, Cloud Engineering, and DevOps teams as an independent expert-providing consultancy, technical alignment, and best practices for operationalizing AI models efficiently., As part of a large-scale platform modernization journey, the organization is strengthening its AI and Machine Learning capabilities to deliver intelligent, secure, and scalable digital solutions on Microsoft Azure. This transformation focuses on embedding enterprise-grade AI capabilities within the platform engineering landscape-enabling automation, improving data security, and accelerating outcomes through responsible AI adoption. ## Related Videos - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [JSON and Beyond](https://www.wearedevelopers.com/videos/968-json-and-beyond) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)