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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Platform Engineer - Azure Data & AI Platform - **Company:** Howden Group Ltd - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Application Performance Management, Microsoft Azure, Continuous Integration, Data as a Services, Data Governance, Data Infrastructure, Github, Network Topologies, Identity and Access Management, Job Scheduling, Python (Programming Language), Key Management, Log Analysis, Machine Learning, SQL Azure, Network Architecture, Network Segmentation, Performance Tuning, Windows PowerShell, Role-Based Access Control, OpenAI, Azure Machine Learning, Azure Data Lake, Data Logging, Azure Data Factory, Cloud Monitoring, Apache Spark, Git, Containerization, Data Lakes, AI Platforms, Kubernetes, Bicep, Machine Learning Operations, Cloud Migration, Api Design, Model Registry, Elastic Beanstalk, Terraform, Azure Synapse Analytics, Software Version Control, Data Pipelines, Dynatrace, Devsecops, Api Management, Static Application Security Testing, Databricks, Vulnerability Analysis, Dynamic Application Security Testing - **Published:** October 6, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4f7af23a645388d2 ## About the Role * 5+ years platform/infrastructure engineering - you've built production platforms, not just prototypes * Deep Azure knowledge - networking, IAM, storage, compute, PaaS services. You know the difference between service endpoints and private endpoints and when to use each * Databricks experience - you've deployed workspaces, configured Unity Catalog, optimized Spark jobs, managed costs * Infrastructure as Code - Terraform (preferred) or Bicep. You write modules, understand state management, know how to structure large IaC projects * CI/CD pipelines - Azure DevOps or GitHub Actions. You've built multi-stage pipelines with gates, approvals, and security scanning * 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, and don't treat security as an afterthought * 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) Strongly Preferred * Experience with Azure landing zones and CAF (Cloud Adoption Framework) * Microsoft Purview for data governance and cataloging * Experience with Delta Lake, Spark optimization, data quality frameworks * Azure networking certifications or equivalent deep knowledge * Container orchestration (AKS) * API design and management (API Management, App Gateway, Front Door) What Actually Matters * Pragmatism over purity - you choose the right tool for the job, not the coolest one * Documentation discipline - you document as you build because you know future-you will thank today-you * Automation mindset - if you do it twice, you automate it * Everything-as-code - if it's not in git, it doesn't exist to you * Collaboration skills - you can translate between data scientists, engineers, and business stakeholders * Ownership mentality - you build it, you run it, you support it * Intellectual honesty - you say "I don't know" when you don't, and then you figure it out ## 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. This isn't a "thought leadership" or "strategy" role. You'll be in the code, in the CLI, and in the infrastructure daily. What You'll Actually Do 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, A career that you define. At Howden, we value diversity - there is no one Howden type. Instead, we're looking for individuals who share the same values as us: * Our successes have all come from someone brave enough to try something new * We support each other in the small everyday moments and the bigger challenges * We are determined to make a positive difference at work and beyond Reasonable adjustments We're committed to providing reasonable accommodations at Howden to ensure that our positions align well with your needs. Besides the usual adjustments such as software, IT, and office setups, we can also accommodate other changes such as flexible hours* or hybrid working*. If you're excited by this role but have some doubts about whether it's the right fit for you, send us your application - if your profile fits the role's criteria, we will be in touch to assist in helping to get you set up with any reasonable adjustments you may require. * Not all positions can accommodate changes to working hours or locations. Reach out to your Recruitment Partner if you want to know more.