Principal AI Leader

Position Overview

As the Principal AI Strategy Leader , you will spearhead the strategic and methodological transformation of JD Power’s Product, Technology, and Analytics (PT&A) organization. This high-impact leadership role is designed to transition traditional product development into an Agentic Product Development Methodology .

You will bridge the gap between high-level business objectives—directly impacting EBITDA targets—and technical execution. You will act as the core advisor guiding both technical and non-technical Product Managers, engineering teams, and data scientists through the adoption, integration, and scaling of advanced generative AI and autonomous agentic workflows.

Key Responsibilities

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AI Strategy: Translate corporate growth goals into concrete initiatives, establishing clear business and technical KPIs to measure success across all portfolios.

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Methodological Framework Design: Blueprint and execute the transition from traditional product development to an advanced Agentic Product Development Methodology across 5 core teams.

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Baseline & Data Readiness: Architect and execute data readiness initiatives to define baselines, leveraging consumer insights, analytics, and benchmarking platforms.

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Tool Audit & Integration: Audit current early-adopter tool usage, manage enterprise AI agreements, and establish standard prototyping and usability testing platform integration.

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Infrastructure Optimization: Partner with engineering leaders to optimize cloud setups and manage dedicated compute/GPU resource allocations for localized model training.

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Enablement & Change Management: Drive tool adoption by upskilling non-technical PMs and engineers, turning abstract capabilities into practical, day-to-day development workflows.

PROFESSIONAL EXPERIENCE

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10+ years of experience leading digital or product transformations, with at least 3+ years specifically focused on Enterprise AI strategy, LLM implementations, or Agentic workflow design.

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Technical Literacy: Strong conceptual and practical understanding of generative AI tech stacks, vector databases, model fine-tuning processes, and cloud infrastructure constraints (AWS/Azure/GCP and GPU resource management).

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Product Expertise: Proven track record in product management or technical architecture within data-dense, benchmarking, or consumer insights industries.

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Business Acumen: Demonstrated success aligning technical implementations with hard financial metrics (EBITDA, ROI, and cost-efficiency KPIs).

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Communication: Elite interpersonal and advisory skills; ability to easily communicate technical AI architectures to executive stakeholders and non-technical product teams alike.

Why Join Us

• Engage in high-impact AI modernization efforts across diverse industrial landscapes.
• Bridge functional gaps by partnering with strategy, product, data, and engineering stakeholders.
• Define the standards for ethical, responsible, and effective enterprise AI implementation.
• Acquire premier experience at the critical intersection of applied technology and business strategy.