Applied AI Product Manager

Applied AI Product Manager

Job Description

We arelooking for an experienced Applied AI Product Manager with 8 to 10 years ofoverall experience to join our team. The Applied AI Product Manager is a seniorindividual contributor responsible for ensuring a product’s value and viabilitywithin a product line. This role involves leading empowered, cross-functionalproduct teams to solve moderate complexity customer problems that align withhigh value business needs. The Applied AI Product Manager is accountable forthe product’s success, from vision to execution, and collaborates closely withvarious functions and stakeholders to deliver valuable, viable, usable, andfeasible solutions.

The AppliedAI Product Manager harnesses AI and agentic tools to compress theconcept-to-cash learning loop—automating analysis, prototyping, and compliancedetail-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 ofhigh value, moderately complex products by balancing customer needs withbusiness objectives, requiring a blend of strategic vision, analytical skills,and collaborative teamwork, amplified by the fluent, responsible use of AI tolearn faster and earn faster.

Responsibilities

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

•        Drive strategy-aligned solutions to achieveproduct value objectives.

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

•        Measure KPIs and analyze outcomes to informfuture strategies.

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

•        Vision and Strategy: Co-create, own, andevangelize the product vision, strategy, and roadmap, using AI to deepen domainknowledge and simulate future scenarios to chart pathways others have not yetseen.

•        Align product objectives with the product lineand business goals.

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

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

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

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

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

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

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

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

•        Promote a product operating model thatemphasizes outcomes over output (minimize overproduction while maximizingvalue).

•        Build empowered teams and product communitieswho exhibit collective product ownership and level-up their outcome potentialthrough AI and agentic tools.

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

•        Drive innovation and improvement of theprocess to drive out waste and accelerate value achievement, using AI as aforce-multiplier to offload the repetitive, speed up the sluggish, and automatethe mundane.

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

•        Spread knowledge and best practices within theproduct vertical community.

•        Applied AI Ways of Working: Amplify innovationby using AI to rapidly deepen domain knowledge, surface untapped market anduser potential, and simulate future scenarios—charting new pathways for thebusiness.

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

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

•        Amplify experimentation: use AI to buildearly, functional, disposable prototypes that validate the architecture and thesolution, playing a key role in the Agentic Secure Software Development LifeCycle 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 leanproduct management or related roles.

•        3+ years enterprise scale experience acrossmultiple business areas.

•        1+ years of building AI based intelligentproducts.

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

•        Limited immigration sponsorship may beavailable.

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

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

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

•        Preferred: MBA or related advanced degree.

•        Demonstrated experience in modern productcraft 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 andP&L objectives for a product and for an empowered product team.

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

•        Strategic Thinking: Ability to develop andexecute a strategic vision for the product, aligning it with broader businessobjectives.

•        Exceptional analytical and problem-solvingskills.

•        Learning-forward, experimental, andvalue-oriented mindset.

•        Ability to navigate complexity anduncertainty.

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

•        AI Realism and Eval Fluency: Understands thedifference between deterministic logic and probabilistic generation; designsguardrails for hallucination, bias, and drift; uses evaluation harnesses beforelaunch and monitors drift after, with a kill-switch mentality—and knows whennot to use AI.

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

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

•        Effective written and verbal communicationskills.

•        Meticulous attention to detail and quality ofwork product.

•        Ability to build and sustain professionalrelationships.

•        Ability to lead projects or workstreams.

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

•        Strong interpersonal skills and professionaldemeanor.

•        Ability to meet deadlines.

•        Ability to mentor and provide clear guidanceto others.