Applied AI Product Leader – Group Product Manager

Job Description

Overview

The Applied AI Group Product Manager is a senior leadership role responsible for the overall product strategy, profit and loss (P&L), product team development, product operating model effectiveness, and objective attainment within a product area. This role focuses on creating the conditions that enable empowered product teams to solve complex customer problems that align with and solve for business needs. The Group Product Manager also performs product management individual contribution to one product in a product area. As an Applied AI leader, this role builds an operating model in which empowered teams harness AI and agentic accelerators—governed by eval guardrails—to compress concept-to-cash lead times. Applied AI leaders keep strategic decision-making firmly human and harness AI to enable rapid emergence of the right product, in the right way, at the right time.

Key Responsibilities

1. Strategy Development and Execution
• Own and evolve the product area strategy, vision, and roadmap in alignment with business objectives, using AI to deepen domain insight and simulate future scenarios.
• Engage cross-functional teams in co-creating and evolving the strategy based on emergent insights from measured results and evidence.
• Champion the product area strategy and keep the organization informed of progress.
2. Product Team Development
• Recruit, staff, coach, and develop Product Managers who can solve complex problems through rapid experimentation.
• Foster a learning-forward, customer-centric, and value-oriented mindset within product teams.
• Coach Product Managers to harness AI and orchestrate agents responsibly, building AI agentic fluency across the product area.
• Ensure safety for experimentation and learning within product teams.
• Builds empowered teams and product communities who exhibit collective product ownership and level-up their outcome potential through AI and agentic tools.
3. System Improvement
• Actively engage with product teams to identify and remove impediments slowing value achievement.
• Continuously improve and streamline the product operating model to enhance market value delivery and achievement, embedding agentic accelerators and AI eval guardrails so teams can ship safely every few days.
• Form effective team topologies to align with objectives and remove obstacles.
4. Outcome-Oriented Transformation
• Evangelize the shift from output to outcomes within the organization.
• Educate and include stakeholders in the new product operating model.
• Demonstrate the value of empowered product teams through action and evidence.
5. Product Management Individual Contributor
• Value and viability accountability, KPI formulation, profit and loss stewardship.
• Vision and strategy cross-functional co-creation and product solution alignment.
• Continuous user engagement to deliver the right thing at the right time in the right way.
• Collaboration with a cross-functional team across business, engineering, experience, and delivery to achieve outcomes and impact.
• Continuous improvement of concept-to-cash flow of value.
6. Applied AI Ways of Working
• Amplify innovation: harness AI to deepen domain insight across the product area and simulate future scenarios—helping teams chart pathways others have not yet seen.
• Amplify learning: enable teams to use AI agents to synthesize evidence and validate ideas fast—compressing concept-to-cash lead times by accelerating the data crunching, ensuring the human connection.
• Amplify focus: champion AI-assisted assumption testing so teams ruthlessly retire ideas that do not serve the user’s workflow in a way that works for the business.
• Amplify experimentation: embed agentic accelerators and the Agentic Secure Software Development Life Cycle into the operating model, with eval guardrails that keep early, frequent shipping safe.

Required Qualifications

1. Bachelor’s degree in Business, Marketing, Engineering, or a related field.
2. 15+ years of proven experience in product management or related roles.
3. 8+ years enterprise scale experience across multiple business areas.
4. 1+ years of building AI based intelligent products
5. 1+ year’s experience in using GenAI tools to perform product management tasks like conduct idea research, shaping, synthesis, roadmaps, requirements, prototyping, testing

Preferred Qualifications

1. Education
• An MBA or related advanced degree is preferred.
2. Experience
• Demonstrated expertise in modern product craft of delivering the right thing, in the right way, at the right time.
• Extensive experience leading and transforming modern product management organizations.
• Proven accountability for value, viability, and P&L for a product organization.
3. Skills
• Visionary and strategic thinker.
• Strong leadership and team development skills.
• Deep expertise in modern product management practices and craft.
• Exceptional communication and ability to influence through inclusion and leadership.
• Learning-forward and value-oriented mindset.
• Ability to navigate complexity and uncertainty.
• Ability to formulate novel solutions to novel problems.
4. Tools and Process
• Expert in modern, learning-oriented product management tools and methods.
• Experience with modern agentic AI tools such as Claude Code, Claude Co-work, Open AI Codex Cursor, and Visual Studio Code.
• Ability to customize tools and methods to specific contexts.
• Ability to simplify process to achieve outcomes and impact.
5. Domain Knowledge
• Broad knowledge across multiple business areas.
• Quick to learn the product domains served in the product area.
6. Personal Traits
• Proven ability to work as an individual contributor in a collaborative, cross-functional team.
• Strong leadership capabilities and a customer-centric mindset.
• Ability to coach Product Managers and lead through influence and experience-driven expertise.
7. Beliefs and Methods
• Humble, curious, and learning-forward mindset.
• Favor action and evidence over detailed upfront planning and precision aiming.
• Experience with lean solutions and rapid, inexpensive experimentation.
• High levels of customer and user engagement to drive the right solution to the right need.
• An approach that emerges the right product, in the right way, at the right time through small steps and rapid learning.
• Believes taste and judgment are the un-automatable moat—using AI to amplify, never replace, product sense-making.

Core Competencies

• Strategic Vision: Develop, execute, and continually evolve a strategic vision for the product area.
• Leadership: Lead and inspire cross-functional teams, fostering collaboration and collective movement toward product goals.
• Customer-Centricity: Deep understanding of customer needs and engagement patterns, driving teams to deliver solutions that customers love and that work for the business.
• Continuous Improvement: Drive continuous improvement in product management practices and the product engineering operating model to enhance market value realization.
• Outcome Orientation: Focus on achieving outcomes over outputs and demonstrate the value of this approach through action and evidence.
• AI Agentic Fluency: Orchestrates and coaches the responsible use of AI agents across the concept-to-cash flow, with guardrails at each hand-off—assumptions, confidence levels, and links to sources of truth.
• AI Realism and Eval Fluency: Champions an evaluation harness across the product area—evals before launch, drift monitoring after, and a kill-switch mentality; knows the difference between deterministic logic and probabilistic generation, and when not to use AI.

Conclusion

The Applied AI Group Product Manager is a pivotal role in driving the success of a product area by balancing customer needs with business objectives. This role requires a blend of strategic vision, leadership, and a collaborative approach to deliver valuable, viable, and feasible solutions. It demands an expert-level degree of experience and expertise in the modern product management craft and a drive for continuous improvement—amplified by building an Applied AI operating model where teams learn faster and earn faster.