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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Ai Platform / Mlops Engineer - **Company:** Accenture - **Location:** Madrid, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Data Intelligence, Prometheus, Search Technologies, Istio, Delivery Pipeline, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Terraform, Serverless Computing, Databricks - **Published:** July 16, 2026 - **Apply:** https://www.buscojobs.com.es/ai-platform-mlops-engineer-en-madrid-ID-364939259 ## About the Role Hybrid work modelStarting financial aid to equip your home workspaceAllowance and telework subventionsFlexible working hours plus two months of intensive summer hoursLife insurance and pension plan for all employeesPerformance bonus tied to objectivesFree parking for cars, motorbikes, electric cars with chargers, and bikesFlexible retribution facilities: transport card, nursery checks, health insurance with Sanitas, trainings, etc.Volunteer actions and time for all employeesWellness ProgramDigital, technology?centric, agile methodology teamsWho you are:5+ years in MLOps/SRE or platform engineering with production ML/AI workloads; deep experience with Databricks MLflow and enterprise CI/CDDesign/operation of multi?env releases (dev?test?prod) with approvals, secrets, identity; IaC (Terraform/CrossPlane) and cloud networking on Azure and/or AWSHands?on with evaluation/monitoring for models/agents; comfort with SLOs, incident response, and capacity/cost managementFamiliarity with tools like ArgoCD, Crossplane, Istio, Knative, Opensearch, Prometheus, and GrafanaOptional qualifications:Experience operating Kubernetes/Seldon for model serving and migrating toward Databricks Mosaic when appropriateFamiliarity with agentic AI evaluation patterns (task success, tool reliability) and RAG observability (Vector Search health)Experience in multi?cloud operations and cross?region latency managementWorking knowledge of Unity Catalog lineage/policies and how they integrate with delivery pipelines and catalogs; ability to produce audit?ready evidenceIf you are a passionate and experienced Senior MLOps Engineer looking for an exciting opportunity to work in a dynamic and challenging environment, we encourage you to apply for this position. ## Description NN Digital Hub is a subsidiary company of NN Group located in Madrid, Spain.We deliver IT services and solutions for the different international Business Units.Senior MLOps EngineerAs we scale our agentic AI strategy, we need to transform Databricks Mosaic AI into a self?service platform that empowers AI engineers across business units.Your role is to build and productize AI capabilities-from RAG pipelines to model serving-and deliver them as scalable, governed, and developer?friendly services.The Data Intelligence Platform is the runtime for models and agentic AI at NN.It runs on DatabricksMLflowand Mosaic, deploying models and agents on Databricks serverless or NN's Kubernetes (Seldon) where needed.Mosaic Vector Search provides RAG for GenAI; the platform spans Azure and AWS to meet latency and proximity needs.As Senior MLOps Engineer, you will standardize build?deploy?serve?monitor across these topologies and make production operations audit?ready by design.Your Impact as Senior MLOps Engineer: What are you going to doDefine the reference MLOps stack for the Agentic Platform: CI/CD patterns and environment promotion with approvals; serving topologies (Databricks serverless vs Kubernetes/Seldon) with decision records; evaluation & drift monitoring with MLflow/Mosaic; and SLO?based runoperations.Integrate Unity Catalog lineage/policies into pipelines so teams meet governance requirements without friction and support the Run expansion.Key responsibilities include:Own CI/CD standards and environment promotion for models/agents: pipelines, approvals, artifact provenance, immutable releases, and rollback/canary patterns.Standardize serving topologies: Databricks serverless vs Kubernetes/Seldon, with clear decision records, SLOs (latency/reliability), and cost/performance guardrails.Implement evaluation and monitoring: MLflow?based offline/online evaluation, drift/quality checks, and end?to?end telemetry dashboards for model/agent behavior and costs with all security & compliance basics in mind.Integrate governance?by?design: enforce Unity Catalog lineage/policies and capture approvals and evidence in pipelines to support audits and marketplace readiness.Operate the Agentic Platform to SLOs: incident response/on?call, capacity planning, cost optimization, post?mortems, and continuous improvement of golden paths.What do we offer?Hybrid work modelStarting financial aid to equip your home workspaceAllowance and telework subventionsFlexible working hours plus two months of intensive summer hoursLife insurance and pension plan for all employeesPerformance bonus tied to objectivesFree parking for cars, motorbikes, electric cars with chargers, and bikesFlexible retribution facilities: transport card, nursery checks, health insurance with Sanitas, trainings, etc.Volunteer actions and time for all employeesWellness ProgramDigital, technology?centric, agile methodology teamsWho you are:5+ years in MLOps/SRE or platform engineering with production ML/AI workloads; deep experience with Databricks MLflow and enterprise CI/CDDesign/operation of multi?env releases (dev?test?prod) with approvals, secrets, identity; IaC (Terraform/CrossPlane) and cloud networking on Azure and/or AWSHands?on with evaluation/monitoring for models/agents; comfort with SLOs, incident response, and capacity/cost managementFamiliarity with tools like ArgoCD, Crossplane, Istio, Knative, Opensearch, Prometheus, and GrafanaOptional qualifications:Experience operating Kubernetes/Seldon for model serving and migrating toward Databricks Mosaic when appropriateFamiliarity with agentic AI evaluation patterns (task success, tool reliability) and RAG observability (Vector Search health)Experience in multi?cloud operations and cross?region latency managementWorking knowledge of Unity Catalog lineage/policies and how they integrate with delivery pipelines and catalogs; ability to produce audit?ready evidenceIf you are a passionate and experienced Senior MLOps Engineer looking for an exciting opportunity to work in a dynamic and challenging environment, we encourage you to apply for this position.We are waiting for you!Please send your CVs in English language.In Nationale?Nederlanden we are committed to diversity.We are proud to be an inclusive organization and we offer equal opportunities, regardless of race, cultural background, gender, gender identity, religion, national origin, age, disability, marital status, and sexual orientation.One of our core values is taking care of our employees so they can give their best within a respectful environment.#J-*****-Ljbffr ## Related Videos - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Rate-limiting using eBPF and Istio: How to protect your SaaS customers from themselves](https://www.wearedevelopers.com/videos/100220-rate-limiting-using-ebpf-and-istio-how-to-protect-your-saas-customers-from-themselves) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [From A2A to MCP: How AI’s “Brains” are Connecting to “Arms and Legs”](https://www.wearedevelopers.com/videos/1631-from-a2a-to-mcp-how-ai-s-brains-are-connecting-to-arms-and-legs) ## Related Articles - [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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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)