Principal AI Engineer

Wolters Kluwer • Coppell, TX

1d

About The Position

The Principal AI Engineer will define and lead 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 hands-on technical leadership role bridges software architecture, AI engineering, cloud-native platforms, distributed systems, and enterprise governance. The engineer will architect AI-enabled systems for enterprise-scale use across multiple products, regions, and regulatory environments, establishing target-state architecture, reference patterns, engineering standards, platform capabilities, and implementation guardrails for AI-assisted audit workflows.

The role covers Audit & Assurance products across North America and Europe. The Principal AI Engineer will design, build, prototype, review code, set architectural direction, coach engineering teams, and remain engaged in implementation and technical decision-making. The position requires expertise in agentic AI systems, retrieval architectures, knowledge graphs, platform modernization, security-by-design, and large-scale SaaS architecture.

Requirements

• 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, and large-scale platform modernization.
• Strong hands-on software engineering experience with C# .NET, Python, APIs, and distributed systems.
• Demonstrated success designing AI-enabled enterprise applications.

Nice To Haves

• Practical experience with multi-agent architectures.
• Experience with LangGraph, Semantic Kernel, Microsoft Foundry Agent Service, Model Context Protocol (MCP), or agent orchestration frameworks.
• Experience with AI evaluation and safety, including offline evaluations, golden datasets, confidence scoring, hallucination mitigation, and human approval workflows.

Responsibilities

• Define 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, and AI-supported analytical workflows.
• Create reusable AI platform capabilities consumed across multiple products.
• Architect end-to-end solutions for audit engagement lifecycle, planning and risk assessment, evidence collection and validation, compliance and standards interpretation, analytics and anomaly detection, and quality review and sign-off workflows.
• Establish bounded contexts, domain-driven design principles, API strategies, and event contracts.
• Design scalable multi-agent systems using manager–executor, planner–executor, blackboard, event-driven agent collaboration, and human-in-the-loop workflows.
• Define memory, context, tool usage, routing, evaluation, and safety frameworks.
• Lead architecture reviews and design governance.
• Produce Architecture Decision Records (ADRs).
• Coach engineering teams in AI architecture, distributed systems, performance engineering, reliability engineering, and architecture trade-off analysis.
• Act as the technical authority for AI architecture decisions.
• Design, build, prototype, review code, and contribute to implementation and technical decision-making.

Benefits

• Medical, dental, and vision plans.
• 401(k).
• FSA/HSA.
• Commuter benefits.
• Tuition Assistance Plan.
• Vacation and sick time.
• Paid parental leave.
• Bonus eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed