Principal AI Engineer
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 across products, regions, and regulatory environments; establish target-state architecture, reference patterns, engineering standards, platform capabilities, and implementation guardrails for AI-assisted audit workflows; and remain actively involved in design, prototyping, code review, implementation, and technical decisions while coaching engineering teams. The scope covers Audit & Assurance products across North America and Europe.
Requirements
- 15 or more years of experience in software engineering and architecture.
- 7 or more 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.
- Practical experience with LangGraph.
- Practical experience with Semantic Kernel.
- Practical experience with Microsoft Foundry Agent Service.
- Practical experience with Model Context Protocol (MCP).
- Practical experience with agent orchestration frameworks.
- Experience with 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, knowledge graphs, semantic search, AI-assisted content generation, and AI-supported analytical workflows.
- Create reusable AI platform capabilities for use 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, including manager–executor, planner–executor, blackboard, event-driven agent collaboration, and human-in-the-loop workflows.
- Define frameworks for memory, context, tool usage, routing, evaluation, and safety.
- Lead architecture reviews and design governance, and produce Architecture Decision Records.
- 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 participate in implementation and technical decision-making.
Benefits
- Medical, dental, and vision plans.
- 401(k).
- Flexible spending account and health savings account (FSA/HSA).
- Commuter benefits.
- Tuition Assistance Plan.
- Vacation and sick time.
- Paid parental leave.
- Bonus eligibility.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
