# Senior MLOps Engineer

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.

As NN scales its agentic AI strategy, it needs to transform Databricks Mosaic AI into a self-service platform that empowers AI engineers across its business units.

As a Senior MLOps Engineer, you will 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 NN’s runtime for models and agentic AI. It runs on Databricks MLflow and Mosaic, deploying models and agents on Databricks Serverless or NN’s Kubernetes environment with Seldon where needed. Mosaic Vector Search provides RAG capabilities for GenAI, while the platform spans Azure and AWS to meet latency and proximity requirements.

Your role will be to standardize the complete build → deploy → serve → monitor lifecycle across these topologies, making production operations audit-ready by design.

# Your impact as Senior MLOps Engineer

You will define the reference MLOps stack for NN’s Agentic Platform, including CI/CD patterns, environment promotion with approvals, serving topologies, evaluation and drift monitoring with MLflow and Mosaic, and SLO-based operations.

You will integrate Unity Catalog lineage and policies into delivery pipelines, allowing teams to meet governance requirements without unnecessary friction and supporting the expansion of the platform.

# Key responsibilities

- Own CI/CD standards and environment promotion for models and agents, including pipelines, approvals, artifact provenance, immutable releases, rollback and canary patterns.

- Standardize serving topologies across Databricks Serverless and Kubernetes/Seldon, with clear decision records, latency and reliability SLOs, and cost/performance guardrails.

- Implement evaluation and monitoring, including MLflow-based offline and online evaluation, drift and quality checks, and telemetry dashboards for model and agent behaviour and costs.

- Ensure security and compliance requirements are built into the platform from the outset.

- Integrate governance by design: enforce Unity Catalog lineage and policies, and capture approvals and evidence in pipelines to support audits and marketplace readiness.

- Operate the Agentic Platform to defined SLOs, including incident response, on-call work, capacity planning, cost optimization, post-mortems and continuous improvement of golden paths.

# What NN offers

- Hybrid work model.

- Financial support to equip your home workspace.

- Allowance and telework subsidies.

- Flexible working hours and two months of intensive summer working hours.

- Life insurance and pension plan.

- Performance-based objectives bonus.

- Free parking for cars, motorcycles, electric cars with chargers and bikes.

- Flexible compensation, including transport card, nursery checks, Sanitas health insurance and training.

- Volunteering opportunities and time for employees to contribute to society.

- Wellness programme.

- An Agile, technology-focused work environment.

# Who you are

- You have 5+ years of experience in MLOps, SRE or platform engineering with production ML/AI workloads.

- You have deep experience with Databricks MLflow and enterprise CI/CD; Databricks expertise is highly preferred.

- You have designed and operated multi-environment releases — development, test and production — with approvals, secrets and identity management.

- You have experience with Infrastructure as Code, such as Terraform or Crossplane, and cloud networking on Azure and/or AWS.

- You are hands-on with evaluation and monitoring for models and agents, and comfortable with SLOs, incident response, capacity management and cost optimization.

- You are familiar with tools such as ArgoCD, Crossplane, Istio, Knative, OpenSearch, Prometheus and Grafana.

# Nice to have

- Experience operating Kubernetes/Seldon for model serving and migrating workloads towards Databricks Mosaic where appropriate.

- Familiarity with agentic AI evaluation patterns, including task success and tool reliability.

- Familiarity with RAG observability and Vector Search health.

- Experience in multi-cloud operations and cross-region latency management.

- Working knowledge of Unity Catalog lineage and policies, including their integration with delivery pipelines and catalogs.

- Ability to produce audit-ready evidence.

If you are a passionate and experienced Senior MLOps Engineer looking for an exciting opportunity in a dynamic and challenging environment, NN would love to hear from you.