Lead Enterprise Software Engineer - DevOps

We are seeking a talented, collaborative, high-energy engineering professional with extensive technical expertise and a passion for automating infrastructure and deployment processes to help build, test, and release the next generation of our cloud-based AI-enabled Expert Solutions as part of the LR AppOps Service Operations & Delivery Team.

The Team provides the DevOps and SRE services which are critical to Wolters Kluwer and our Expert Solutions in the Legal & Regulatory division.

As a Lead DevOps Engineer, you will be responsible for leading the design and implementation of the infrastructure and deployment pipelines for our applications, as well as maintaining and improving reliability of our existing systems. You will work alongside the Wolters Kluwer Product Teams to successfully implementing and bring any learnings through continuous improvements. You will work closely with the Application Development Teams to ensure that our services and solutions are delivered efficiently and with the highest level of quality. In addition, you will be responsible for mentoring a team of DevOps engineers, fostering a culture of collaboration with continuous improvement and learning.

Essential Duties And Responsibilities :

As a Lead DevOPS Engineer :

• Design, implement, and automate cloud infrastructure across Azure and AWS using Infrastructure as Code (Terraform, Ansible), enabling scalable, secure, and repeatable environments
• Drive and scale the adoption of AI capabilities across the portfolio, enabling Teams to leverage AI-powered services to improve productivity, operational efficiency, and service reliability, while ensuring alignment with enterprise security, data protection, and governance standards
• Lead the adoption of DevSecOps and Infrastructure as Code practices across Service Operations, Delivery, and the wider organisation
• Drive the design and evolution of containerised and serverless architectures (AKS, EKS, Docker, Azure Functions)
• Define, build, and maintain CI/CD pipelines to improve deployment frequency, reliability, and lead time
• Implement observability standards, including SLIs/SLOs, monitoring, logging, and alerting to ensure proactive issue detection and reduced MTTR
• Apply SRE principles to improve resilience, scalability, and reduce operational TOILs
• Ensure solutions align with enterprise DevOps, security, and compliance standards
• Embed security-by-design across the SDLC, including vulnerability management and secure configuration practices
• Mentor and lead DevOps engineers, fostering a high-performing and learning-oriented culture
• Act as a technical authority, contributing to architecture decisions and engineering standards
• Enable platform capabilities and reusable automation patterns to support scalable delivery across Teams
• Lead incident resolution, root cause analysis, and continuous improvement initiatives
• Drive continuous improvement by identifying engineering inefficiencies and proposing modernisation strategies

Job Qualifications : Hold at least two Azure &/or AWS Certifications

Education :  Bachelor’s in Engineering or Master’s degree in Computer Science

Required Experience : 

• 10+ years (or equivalent senior experience) in DevOps, SRE, Release Engineering, or Software Engineering, with exposure to production-critical systems
• Strong hands-on experience with cloud platforms (Azure and/or AWS), including designing and operating scalable and secure solutions
• Proven experience in maintaining and deploying highly available, fault-tolerant cloud-native systems at scale using Infrastructure as Code automation, particularly Terraform (preferred) or CloudFormation
• Experience using AI-assisted tools (e.g. GitHub Copilot, ChatGPT, or similar) to improve productivity
• Experience automating operational tasks using AI-assisted scripting or intelligent automation approaches
• Familiarity with prompt engineering and AI usage patterns in engineering workflows
• Solid experience building and managing CI/CD pipelines, using tools such as Azure DevOps, Jenkins, GitHub
• Experience building or operating AI-enabled pipelines (e.g. integrating ML/AI services into CI/CD workflows)
• Strong scripting/automation skills using Python, Bash or PowerShell
• Experience working in both Linux and Windows environments, including troubleshooting and automation
• Solid Experience with Kubernetes (AKS/EKS) and containerised environments
• Experience with observability practices, including Monitoring, Logging, Alerting (e.g. Datadog, Prometheus, Grafana, CloudWatch)
• Practical application of SRE principles, including Incident Management, Relaiability and Resilience, Toil Reduction
• Experience applying DORA metrics to improve delivery performances
• Familiarity with enterprise tooling ecosystem (e.g. ServiceNow)
• Proven ability to lead or mentor engineers and work across multiple Teams
• Strong communication skills, with the ability to explain complex technical topics to non-technical stakeholders
• Strong attention to details with excellent problem-solving skills
• Experience driving DevOps transformation initiatives or cultural change

Preferred Experience : 

• Experience with configuration management tools (Ansible, Puppet, Chef)
• Experience with serverless architectures (Azure Functions, AWS Lambda)
• Exposure to cost optimisation and cloud financial management (FinOps)
• Experience with AI observability / monitoring (tracking model performance, usage, cost)
• Experience with Open Telekom Cloud (OTC) as public cloud provider

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.