# Principal AI Engineer at Wolters Kluwer

Wolters Kluwer is hiring a Principal AI Engineer. It pays $108k-$188k a year and Level rates it Builds AI ●●●●; you can [apply on Wolters Kluwer](https://jobsbylevel.com/go/7a0986ea-96df-42ff-bac9-9bfcb41d0a0a?utm_medium=ai-agent).

AI Level 4, AI centrality 88 out of 100. USA - Coppell, TX.

## Details

- Company: [Wolters Kluwer](https://jobsbylevel.com/companies/wolters-kluwer)
- AI level: AI Level 4 (score 88 out of 100)
- Location: USA - Coppell, TX
- Salary: $108k-$188k
- Posted: October 26, 2026
- Apply: https://jobsbylevel.com/go/7a0986ea-96df-42ff-bac9-9bfcb41d0a0a?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=principal-ai-engineer-at-wolters-kluwer-047f51

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/principal-ai-engineer-at-wolters-kluwer-047f51

## Description

Role Summary We are seeking a Principal AI Engineer to define and lead the AI architecture for a large-scale Audit & Assurance application portfolio spanning engagement workflows, evidence management, analytics, content intelligence, risk assessment, compliance, and review automation. This is a highly hands-on technical leadership role for an individual who can bridge modern software architecture, AI engineering, cloud-native platforms, distributed systems, and enterprise governance. You will architect AI-enabled systems that operate at enterprise scale across multiple products, regions, and regulatory environments. You will be responsible for establishing the target-state AI architecture, reference patterns, engineering standards, platform capabilities, and implementation guardrails for AI-assisted audit workflows. The role requires deep expertise in agentic AI systems, retrieval architectures, knowledge graphs, platform modernization, security-by-design, and large-scale SaaS architecture. You are expected to design, build, prototype, review code, establish architectural direction, and coach engineering teams while remaining actively engaged in implementation and technical decision-making. The scope spans all Audit & Assurance products across North America and Europe. What You'll Do AI Platform Architecture Define the enterprise AI architecture strategy across the Audit & Assurance portfolio. Establish reference architectures for: Agentic workflows Multi-agent orchestration Retrieval-augmented generation (RAG) Knowledge graphs Semantic search AI-assisted content generation AI-supported analytical workflows Create reusable AI platform capabilities consumed across multiple products. Product & Domain Architecture Architect end-to-end solutions across: Audit engagement lifecycle Planning and risk assessment Evidence collection and validation Compliance and standards interpretation Analytics and anomaly detection Quality review and sign-off workflows Establish bounded contexts, domain-driven design principles, API strategies, and event contracts. AI Systems & Agent Engineering Design scalable multi-agent systems using: Manager–Executor Planner–Executor Blackboard Event-driven agent collaboration Human-in-the-loop workflows Define memory, context, tool usage, routing, evaluation, and safety frameworks. Technical Leadership Lead architecture reviews and design governance. Produce Architecture Decision Records (ADRs). Coach engineering teams in: AI architecture Distributed systems Performance engineering Reliability engineering Architecture trade-off analysis Act as the technical authority for AI architecture decisions. Required Qualifications 15+ years in software engineering and architecture. 7+ years designing large-scale SaaS and distributed systems. Proven experience architecting enterprise AI systems in production. Deep expertise in: Azure Kubernetes/AKS Distributed systems Microservices Event-driven architectures Large-scale platform modernization Strong hands-on software engineering experience with: C# .NET Python APIs Distributed systems Demonstrated success designing AI-enabled enterprise applications. Preferred Qualifications AI & Agentic Systems Practical experience with: Multi-agent architectures LangGraph Semantic Kernel Microsoft Foundry Agent Service Model Context Protocol (MCP) Agent orchestration frameworks AI Evaluation & Safety Offline evaluations Golden datasets Confidence scoring Hallucination mitigation Human approval workflows 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

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