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Open nowPosted yesterday

Principal AI Engineer

Wolters Kluwer326 open roles

Where
USA - Coppell, TX
Work mode
Hybrid
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Your applicationOpen nowPrincipal AI EngineerWolters Kluwer · USA - Coppell, TX

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Wolters Kluwer postings stay open a median of 40 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted yesterday

Wolters Kluwer median: 40 days open

The posting

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 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:

$107,500.00 - $188,400.00 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.

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