# Senior Platform Engineer - Azure Data & AI Platform

**Company**: Howden
**Work arrangement**: remote
**Experience**: senior
**Category**: Engineering
**Industry**: Insurance

**Apply**: https://hyperiongrp.wd3.myworkdayjobs.com/en-US/hyperion_external/job/London/Senior-Platform-Engineer---Azure-Data---AI-Platform_R0018598-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_5af0c7ca-664

## Description

We are looking for senior platform engineers to build and operate our Azure-based data and AI platform. This is hands-on infrastructure and platform work - you'll be writing Terraform, designing network architecture, implementing MLOps (AI model) pipelines, and establishing DevSecOps patterns that engineering teams can use.

**Azure Platform Engineering (40%)**

- Design and implement Azure landing zones, management groups, and subscription architecture

- Build and maintain hub-spoke network topologies with proper segmentation and security controls

- Implement Azure Policy, RBAC, and governance frameworks that balance security with developer productivity

- Manage identity and access using Entra ID, service principals, managed identities

- Establish monitoring, logging, and alerting with Azure Monitor, Log Analytics, and Application Insights

- Cost management and FinOps practices - keeping cloud spend under control without hamstringing teams

**Databricks & Data Platform (30%)**

- Deploy and configure Azure Databricks workspaces with Unity Catalog for data governance

- Assisting both data and AI teams with pipeline development

- Establish Databricks best practices: cluster policies, job scheduling, notebook standards, workspace organization

- Integrate Databricks with ADLS Gen2, Azure SQL, Synapse, and other data services

- Set up and maintain CI/CD for Databricks notebooks, jobs, and infrastructure

- Work with data engineers on performance optimization, cost control, and platform capabilities

**MLOps & AI Platform (20%)**

- Build ML model deployment pipelines using Azure ML, Databricks MLflow, or both

- Implement model versioning, experiment tracking, and model registry patterns

- Establish inference endpoints (batch and real-time) with proper monitoring and governance

- Create reusable ML pipeline templates and infrastructure-as-code modules

- Integrate AI services (Azure OpenAI, Cognitive Services) into platform offerings

- Implement responsible AI guardrails: model monitoring, bias detection, explainability

**DevSecOps & Platform Enablement (10%)**

- Creation of tools, features and dashboards for the developer platform

- Build CI/CD pipelines in Azure DevOps or GitHub Actions with proper security scanning

- Implement shift-left security: SAST/DAST, dependency scanning, infrastructure scanning, secrets management

- Establish infrastructure-as-code standards with Terraform (or Bicep), including modules and policy enforcement

- Create self-service tooling and automation for common platform tasks

- Write documentation that engineers will read and use

- Participate in on-call rotation for platform incidents

**What We Need From You**

- 5+ years platform/infrastructure engineering

- Deep Azure knowledge - networking, IAM, storage, compute, PaaS services

- Databricks experience - you've deployed workspaces, configured Unity Catalog, optimized Spark jobs, managed costs

- Infrastructure as Code - Terraform (preferred) or Bicep

- CI/CD pipelines - Azure DevOps or GitHub Actions

- Containerization experience – you know best practices when building and working with both application-based containers and containers holding ML/ AI models

- Security-first mindset - you understand defense in depth, least privilege, network segmentation

- MLOps fundamentals - model training vs inference, experiment tracking, model versioning, deployment patterns

- Python and/or PowerShell - for automation, tooling, and platform utilities

- Observability stack beyond basic metrics (distributed tracing, log aggregation patterns)

**What We Offer**

- Actual flexibility: Remote-first with occasional in-office travel for workshops/planning

- Real learning budget: for conferences, training, certifications

- Tooling: You'll get the equipment and licenses you need to do the job properly

- Grown-up engineering culture

## Skills

### Required
- Azure
- Terraform
- Databricks
- MLOps
- DevSecOps
- Python
- PowerShell

### Nice to have
- Azure landing zones
- CAF (Cloud Adoption Framework)
- Microsoft Purview
- Delta Lake
- Spark optimization
- data quality frameworks
- Azure networking certifications
- container orchestration (AKS)
- API design and management

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Source: [Apply at hyperiongrp.wd3.myworkdayjobs.com](https://hyperiongrp.wd3.myworkdayjobs.com/en-US/hyperion_external/job/London/Senior-Platform-Engineer---Azure-Data---AI-Platform_R0018598-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)