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Wolters Kluwer

Enterprise Software Engineer

Wolters Kluwer is hiring an Enterprise Software Engineer. It pays $83k-$142k a year and Level rates it ; you can apply on Wolters Kluwer.

Level's read on this job

  • Level rates this software engineer role Little AI ●○○○: aI is not part of the work.
  • Level lists 469 other open roles at Wolters Kluwer.
  • The role was posted in the last few days.

AI in this role

Wolters Kluwer Health is seeking an Enterprise Software Engineer – Cloud Systems to help build, automate, monitor, and improve the cloud infrastructure and engineering platforms that support our software products.


You will work alongside experienced engineers and gain hands-on exposure to site reliability engineering, cloud computing, infrastructure as code, container technologies, monitoring and observability, and continuous integration and delivery. You will contribute to solutions that improve the reliability, scalability, security, and performance of development, testing, and production environments.


This position provides an opportunity to learn how enterprise software and cloud platforms operate at scale while contributing to reliable technology used by healthcare professionals and internal engineering teams.


What You'll Do

· Assist with designing, implementing, and supporting cloud and on-premises infrastructure.

· Develop automation that improves the reliability and consistency of development, testing, and production environments.

· Contribute to cloud-native solutions using Microsoft Azure, Amazon Web Services, or similar cloud platforms.

· Help create and maintain infrastructure using infrastructure-as-code and configuration-management practices.

· Support containerized applications and container-orchestration platforms.

· Contribute to continuous integration and continuous delivery pipelines.

· Help improve monitoring, logging, alerting, and observability across applications and infrastructure.

· Use system metrics and key performance indicators to evaluate platform health, performance, and stability.

· Troubleshoot software, infrastructure, deployment, and performance issues using logs, metrics, alerts, and other technical evidence.

· Collaborate with software engineers, cloud engineers, quality teams, and other technical partners to resolve issues and improve system reliability.

· Compare possible technical solutions, identify advantages and trade-offs, and contribute to team decisions.

· Participate in code reviews, iterative planning, and agile development practices.

· Document technical solutions, operating procedures, and engineering best practices.

· Follow secure engineering practices for cloud access, authentication, authorization, and secrets management.

· Learn and apply new cloud technologies, programming languages, automation tools, and reliability-engineering practices.


Qualifications

Required Qualifications

· Currently pursuing a bachelor's or master's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, Information Systems, or a related technical field.

· Academic, personal, or professional experience with software development, scripting, system administration, cloud computing, or infrastructure automation.

· Experience with at least one programming or scripting language, such as Python, Go, Groovy, PowerShell, Bash, or another shell-scripting language.

· Foundational understanding of operating systems, networks, software applications, or cloud infrastructure.

· Strong analytical and problem-solving skills.

· Ability to investigate technical issues using logs, metrics, test results, and other available evidence.

· Interest in learning cloud technologies, automation tools, container platforms, and site reliability engineering practices.

· Ability to communicate clearly and collaborate effectively in a team environment.

· Commitment to system reliability, security, accountability, and continuous learning.


Preferred Qualifications

· Exposure to Microsoft Azure, Amazon Web Services, or another cloud platform.

· Familiarity with Linux, Unix, or Windows operating systems.

· Experience with Git or another source-control platform.

· Exposure to infrastructure-as-code tools such as Terraform, Azure Resource Manager, or AWS CloudFormation.

· Familiarity with Docker, Podman, Kubernetes, or another container and orchestration platform.

· Exposure to configuration-management tools such as Ansible.

· Familiarity with CI/CD technologies such as Jenkins, Azure DevOps, or GitHub Actions.

· Exposure to monitoring or observability technologies such as Datadog, Splunk, the Elastic Stack, or OpenTelemetry.

· Familiarity with APIs, microservices, or enterprise API-management concepts.

· Understanding of cloud authentication, authorization, role-based access control, identity and access management, or secrets management.

· Exposure to agile practices or collaboration tools such as Scrum, Kanban, Jira, or Confluence.

· Interest in site reliability engineering, DevOps, platform engineering, cloud engineering, or release engineering.


What You'll Gain

· Hands-on experience with enterprise cloud infrastructure and site reliability engineering.

· Exposure to Microsoft Azure, Amazon Web Services, infrastructure as code, containers, and CI/CD.

· Experience using monitoring, logging, and observability data to assess system health and troubleshoot issues.

· Opportunities to learn from experienced cloud, software, DevOps, security, and site reliability engineers.

· Experience supporting development, testing, and production environments.

· An understanding of how automation, observability, security, and engineering best practices contribute to dependable enterprise software.

· The opportunity to contribute to infrastructure and platforms that help Wolters Kluwer Health teams deliver reliable software to customers.


About Wolters Kluwer

Wolters Kluwer is a global leader in professional information, software solutions, and services for healthcare, tax and accounting, financial and corporate compliance, legal and regulatory, and corporate performance professionals. We combine deep domain knowledge with technology to help customers make critical decisions with confidence.

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.

Compensation:

$82,700.00 - $141,650.00 USD

This role is eligible for Bonus.

Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.

Additional Information:

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.

How we rate this

Enterprise Software Engineer at Wolters Kluwer rates 37 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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