Applied AI Product Manager

Applied AI Product Manager

Job Description

We are looking for an experienced Applied AI Product Manager with 8 to 10 years of overall experience to join our team. The Applied AI Product Manager is a senior individual contributor responsible for ensuring a product’s value and viability within a product line. This role involves leading empowered, cross-functional product teams to solve moderate complexity customer problems that align with high value business needs. The Applied AI Product Manager is accountable for the product’s success, from vision to execution, and collaborates closely with various functions and stakeholders to deliver valuable, viable, usable, and feasible solutions.

The Applied AI Product Manager harnesses AI and agentic tools to compress the concept-to-cash learning loop—automating analysis, prototyping, and compliance detail-work so the team can focus on the human judgment AI cannot replace: product sense-making. The role plays a crucial part in ensuring the success of high value, moderately complex products by balancing customer needs with business objectives, requiring a blend of strategic vision, analytical skills, and collaborative teamwork, amplified by the fluent, responsible use of AI to learn faster and earn faster.

Responsibilities

• Product Accountability: Responsible and accountable for the product’s value and viability showcasing a measurable Return on Investment (ROI).

• Drive strategy-aligned solutions to achieve product value objectives.

• Formulate and achieve Key Performance Indicators (KPIs) for identified problems to solve.

• Measure KPIs and analyze outcomes to inform future strategies.

• Leverage AI to harvest outcome evidence early and often, lowering total cost of ownership (TCO).

• Vision and Strategy: Co-create, own, and evangelize the product vision, strategy, and roadmap, using AI to deepen domain knowledge and simulate future scenarios to chart pathways others have not yet seen.

• Align product objectives with the product line and business goals.

• Co-create in collaboration with business stakeholders, engineering, experience, and delivery.

• Use AI to expedite research, gather evidence, bolster domain knowledge, and craft innovative visions backed by compelling strategic rationale.

• Market and User Engagement: Conduct user research and competitive analysis, using AI agents to synthesize research at speed—accelerating the data crunching, ensuring the human connection.

• Engage the team with users and stakeholders through continuous research and direct interactions.

• Collaborate and guide the team toward solutions that address priority user and business needs.

• Apply analytical skills to analyze data and derive actionable insights, shifting from waiting on analysis to working on insights.

• Adopt innovative and experimental approaches to solving complex problems, including AI-built, disposable prototypes that validate solutions quickly and retire bad ideas just as fast.

• Collaboration and Teamwork: Work side-by-side with cross-functional (business, engineering, experience, and delivery) team members to achieve KPI outcomes.

• Promote a product operating model that emphasizes outcomes over output (minimize overproduction while maximizing value).

• Build empowered teams and product communities who exhibit collective product ownership and level-up their outcome potential through AI and agentic tools.

• Continuous Improvement: Promote and drive rapid, emergent, and ongoing learning and adaptation to meet objectives.

• Drive innovation and improvement of the process to drive out waste and accelerate value achievement, using AI as a force-multiplier to offload the repetitive, speed up the sluggish, and automate the mundane.

• Remove obstacles for the team and ensure smooth flow of continuous value achievement.

• Spread knowledge and best practices within the product vertical community.

• Applied AI Ways of Working: Amplify innovation by using AI to rapidly deepen domain knowledge, surface untapped market and user potential, and simulate future scenarios—charting new pathways for the business.

• Amplify learning: use AI agents to synthesize research and validate ideas before they enter the backlog—compressing lead time by accelerating the data crunching, ensuring the human connection.

• Amplify focus: act as Editor-in-Chief—using AI to rigorously test assumptions and retire ideas that do not genuinely serve the user’s workflow in a way that works for the business.

• Amplify experimentation: use AI to build early, functional, disposable prototypes that validate the architecture and the solution, playing a key role in the Agentic Secure Software Development Life Cycle that paves a clear path to productionize early and often.

Requirements

• Bachelor’s degree in Business, Marketing, Engineering, or a related field.

• 8 to 10 years of proven experience in lean product management or related roles.

• 3+ years enterprise scale experience across multiple business areas.

• 1+ years of building AI based intelligent products.

• 1+ years of experience using GenAI tools to perform product management tasks such as idea research, shaping, synthesis, roadmaps, requirements, prototyping, and testing.

• Limited immigration sponsorship may be available.

• Ability to travel 0-20%, on average, based on the work you do and the clients and industries/sectors you serve.

• Ability to work in your local office at a minimum of 3 days per week.

• Candidates must be located within a commutable distance to one of the select locations available for this role.

• Preferred: MBA or related advanced degree.

• Demonstrated experience in modern product craft of delivering the right thing, in the right way, at the right time. Significant experience in lean product management craft and domain (tools, methods, and practices). Seen as a leader in this space.

• Proven accountability for value, viability and P&L objectives for a product and for an empowered product team.

• Customer-Centricity: Deep understanding of customer needs and engagement patterns, driving teams to deliver solutions that customers love and that work for the business. Expertise in applying customer-centric methods and practices.

• Strategic Thinking: Ability to develop and execute a strategic vision for the product, aligning it with broader business objectives.

• Exceptional analytical and problem-solving skills.

• Learning-forward, experimental, and value-oriented mindset.

• Ability to navigate complexity and uncertainty.

• AI Agentic Fluency: Comfortable orchestrating multiple AI agents across the concept-to-cash flow (research, insight, prototyping, specification, coding, and compliance), with guardrails at each hand-off—assumptions, confidence levels, and links to sources of truth.

• AI Realism and Eval Fluency: Understands the difference between deterministic logic and probabilistic generation; designs guardrails for hallucination, bias, and drift; uses evaluation harnesses before launch and monitors drift after, with a kill-switch mentality—and knows when not to use AI.

• Experience with modern agentic AI tools such as Claude Code, Claude Co-work, OpenAI Codex, Cursor, and Visual Studio Code.

• The successful candidate will possess the ability to work independently and collaborate as part of a team.

• Effective written and verbal communication skills.

• Meticulous attention to detail and quality of work product.

• Ability to build and sustain professional relationships.

• Ability to lead projects or workstreams.

• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.

• Strong interpersonal skills and professional demeanor.

• Ability to meet deadlines.

• Ability to mentor and provide clear guidance to others.