Senior Product Manager, Innovation & Deployment

Overview

In this role you will define and steer the AI-focused product strategy for the Clara Innovation & Deployment team, linking auditors, data scientists, engineers, and governance leads to deliver scalable, ethical audit solutions. You will drive adoption of AI-enabled products that enhance audit quality and efficiency, while ensuring responsible design and compliance. You will lead cross-functional delivery in an agile environment and shape the product lifecycle from concept to production. This is your chance to influence how AI transforms audit practice at scale.

Responsibilities

• Define the product vision, roadmap and delivery strategy for AI-enabled audit solutions.
• Translate audit processes and business needs into prioritized product requirements leveraging latest tech.
• Collaborate with data scientists, ML engineers, architects, and governance leads to deliver secure, compliant solutions.
• Ensure ethical and responsible design with Responsible AI frameworks, bias mitigation, transparency, and lifecycle management.
• Track adoption metrics and value delivery, adjusting roadmaps based on feedback and outcomes.
• Engage audit stakeholders to prioritize features and validate solutions for user-centric design.
• Lead cross-functional teams using agile methods, aligning with audit quality, risk, and business outcomes.
• Provide thought leadership on emerging technologies and their application in audit.
• Potentially work at client sites or other KPMG offices.

Key requirements

• Proven product management experience, ideally in AI/ML or data science within regulated or professional services.
• Strong understanding of machine learning, data governance, model lifecycle management, and ethical AI standards.
• Ability to translate technical capabilities into practical audit-focused products and use cases.
• Demonstrated leadership delivering end-to-end solutions including validation, accreditation, and adoption.
• Excellent communication and collaboration with technical and non-technical stakeholders.

• Strategic Thinking
• Stakeholder Management
• Communication & Influence
• AI/ML
• data governance
• model lifecycle management

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