Senior Cloud Software Engineer with ML

Job Description- Senior Cloud Software Engineer (T3)

Company Overview:

Wolters Kluwer Global Business Services is designed to provide services to business units in the areas of technology, sourcing, procurement, legal, finance, and accounting, including our North American Accounting Center. These global centers promote team collaboration using best practices around a specific focus area to drive results and enhance operational efficiencies. There is a constant endeavor to benchmark against best-in-class industry standards to improve the quality of deliverables, increase cost savings, enhance productivity, and reduce time to market for products and applications

Position Overview:

The IT Infrastructure and Operations Team is a part of Wolters Kluwer Global Business Services (GBS). GBS is designed to provide services to business units in the areas of technology, sourcing, procurement, legal, finance, and accounting, including our North American Accounting Center. These global centers promote team collaboration using best practices around a specific focus area to drive results and enhance operational efficiencies. There is a constant endeavor to benchmark against best-in-class industry standards to improve the quality of deliverables, increase cost savings, enhance productivity, and reduce time to market for products and applications.

We are seeking a Senior Cloud Software Engineer with strong expertise in cloud platform engineering, automation-first operations, and intelligent CloudOps, capable of designing, governing, and optimizing large-scale AWS and Azure environments. This role requires deep technical ownership, architectural thinking, and mentoring capability, along with the ability to drive AI-assisted, policy-driven, and self-healing cloud operations.

Key Responsibilities:

Cloud Software Development

·       Deep hands-on expertise in Microsoft Azure and AWS, operating at enterprise scale.

·       Design, develop, test, and maintain cloud-native services and internal platforms using Python (FastAPI, Django, Flask).

·       Build secure, scalable RESTful and event-driven APIs using Azure and AWS SDKs, serverless services, and managed cloud platforms.

·       Develop reusable libraries, internal frameworks, and shared services that standardize cloud consumption and accelerate engineering teams.

·       Apply clean architecture, SOLID principles, and enterprise design patterns to ensure maintainable and resilient solutions.

·       Develop cloud services and tooling supporting large-scale Azure and AWS environments.

·       Design solutions with observability, resilience, scalability, security, and cost optimization as core requirements.

AI, Generative AI & Agentic Engineering

·       Design and implement AI-enabled cloud services, including intelligent automation, decision-support systems, and AI-assisted operational tooling.

·       Build and integrate Generative AI and LLM-based solutions using enterprise-approved AI platforms, including retrieval-augmented generation (RAG), embeddings, vector search, and prompt/context engineering.

·       Design, build, and orchestrate AI agents and multi-agent workflows that automate cloud operations, remediation, and engineering tasks.

·       Integrate AI agents with enterprise systems, data sources, and tooling using the Model Context Protocol (MCP) and function/tool-calling patterns.

·       Implement evaluations, guardrails, observability, cost/token controls, and human-in-the-loop feedback mechanisms to ensure reliable and secure AI usage.

·       Apply Responsible AI and AI governance practices, including bias mitigation, data privacy, and protection against prompt injection and data leakage.

Intelligent CloudOps & AIOps

·       Design and operate AI-driven CloudOps capabilities, including anomaly detection, predictive scaling, intelligent alerting, and alert noise reduction.

·       Build self-healing and auto-remediation workflows that detect, diagnose, and resolve incidents with minimal human intervention.

·       Drive incident, problem, and change management with automated runbooks, observability dashboards, and post-incident learning.

Infrastructure as Code, DevOps & Automation

·       Own the end-to-end infrastructure lifecycle: design, build, operate, optimize, and decommission.

·       Design and enhance Infrastructure-as-Code using Terraform with modular, reusable, organization-wide standards.

·      …