Wolters Kluwer - Senior Enterprise Cloud Software Engineer

Description :

We are seeking a Senior Enterprise Cloud Software Engineer skilled in automation engineering, artificial intelligence, and cloud operations.

This role represents a strategic evolution of two traditionally separate disciplines - Enterprise Cloud Software Development and Cloud Operations Engineering - into a single, high impact engineering role that designs, builds, and operates intelligent, automation first cloud platforms at enterprise scale.

The Senior Enterprise Cloud Platform Engineer role redefines operations as software, embedding reliability, governance, security, and resilience directly into cloud services through code, automation, and AI assisted intelligence.

You will help drive the future of cloud operations by creating programmable platforms, self healing systems, and AI augmented operational workflows across AWS and Azure, replacing manual toil with scalable, policy driven execution.

Mission of the Role :

Transform Cloud Operations from reactive support into proactive, software defined platforms.

Fuse software engineering rigor with operational ownership.

Leverage automation, Infrastructure as Code, and AI to eliminate manual work at scale.

Design systems that are secure, observable, resilient, and self optimizing by default.

Act as a technical bridge between Engineering, Cloud Operations, Security, and Architecture.

Technical Skills & Competencies :

Enterprise Cloud Software Engineering :

- Design and build enterprise grade cloud services, APIs, and automation platforms using a Python first stack (FastAPI/Django/Flask), with UI components where needed.

- Develop cloud native tooling and services using Azure and AWS SDKs to standardize provisioning, lifecycle management, and operational workflows.

- Apply modern software engineering practices : clean architecture, SOLID principles, automated testing, and CI/CD driven delivery.

- Design contract first APIs (REST/GraphQL) and event driven services to enable platform extensibility and integration.

Cloud Operations Engineering (Software Defined) :

- Own the full lifecycle of cloud platforms : design, build, operate, optimize, and decommission.

- Engineer automation first infrastructure operations, eliminating manual provisioning,

patching, scaling, and recovery.

- Implement Infrastructure as Code frameworks using Terraform (modules, state management, drift detection) and supporting tools (Ansible, ARM/Bicep, CloudFormation).

- Build and operate high availability, fault tolerant, and disaster resilient architectures across hybrid and multi cloud environments.

- Lead L3/L4 troubleshooting, root cause analysis, and reliability improvements for complex cloud incidents.

AI Driven & Intelligent Operations :

- Apply AI assisted CloudOps practices including anomaly detection, predictive insights, event correlation, and automated remediation.

- Design and operate intelligent runbooks and AI agents that execute operational decisions safely and audibly.

- Integrate approved GenAI and ML services into operational workflows while adhering to governance and responsible AI standards.

- Use AI tools to accelerate development, testing, documentation, and operational analysis.

DevOps, CI/CD & Governance :

- Design and maintain CI/CD pipelines for infrastructure and platform automation using Azure DevOps, GitHub Actions, or GitLab.

- Implement policy as code, security guardrails, tagging standards, and cost optimization controls.

- Embed observability, APM, logging, and SLO/SLA practices into platforms from day one.

- Ensure platforms are built to be operable by design, not retrofitted for operations.

Leadership & Engineering Influence :

- Serve as a technical leader and mentor, elevating engineering and CloudOps maturity.

- Collaborate closely with Architecture, Security, Compliance, and Product teams.

- Establish standards, patterns, documentation, and reusable frameworks used across the

enterprise.

- Drive continuous improvement, reliability engineering, and operational excellence.

Required Qualifications :

Education :

Required : Bachelor's degree in Computer Science, or a related field.

Experience :

- More than 5 years of Cloud Operations, DevOps, or Infrastructure Engineering.

- Hands-on experience in AI-based automation is highly desirable.

- Proven experience operating large-scale AWS and Azure environments.

Certifications :

- Advanced certification in AWS and Azure will be preferred.

- Terraform Associate.

- AI or ML Certification.

Core Technical Expertise :

- Deep hands on experience in AWS and Azure at enterprise scale.

- Strong proficiency in Python and scripting for automation and platform development.

- Advanced Terraform expertise with modular, reusable, enterprise grade designs.

- Experience with containers and orchestration (Docker, Kubernetes, AKS, EKS).

- Strong understanding of networking, identity, security, and cloud governance.

- Experience with CI/CD, release management, and platform operationalization.

AI & Advanced Automation :

- Practical experience applying AI to operational workflows.

- Understanding of AI fundamentals, safe usage, and lifecycle governance.

- Ability to design AI assisted automation without compromising reliability or compliance.

Engineering Mindset :

- Strong architectural thinking and systems design skills.

- Passion for eliminating toil through code.

- Ability to operate independently while influencing across teams.

- Excellent communication and documentation skills.