Principal AI Engineer

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 DoAI 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