Applied AI Lead Product Manager
$130.9k - $268.7kDeloitte LLP
The Applied AI Lead Product Manager plays a crucial role in ensuring the success of our most strategic, complex products by balancing customer needs with business objectives. This role requires a blend of strategic vision, analytical skills, and collaborative teamwork to deliver valuable, viable, usable, and feasible solutions. It demands a high degree of experience and expertise in the modern product management craft and a drive for continuous improvement-amplified by the fluent, responsible use of AI to learn faster and earn faster.
Work you'll do- Product Accountability
- Responsible and accountable for the product's value and viability showcasing a measurable Return on Investments (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.
- 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.
- 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.
- Continuous Improvement
- Remove obstacles for the team and ensure smooth flow of continuous value achievement.
- 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.
- Spread knowledge and best practices within the product vertical community.
- Applied AI Ways of Working
- Amplify innovation: use AI to rapidly deepen domain knowledge, surface untapped market and user potential, and simulate future scenarios-charting new pathways for the business rather than only collecting requirements.
- 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: orchestrate AI agents 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 for engineering to productionize.
- 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
- Bachelor's degree in Business, Marketing, Engineering, or a related field.
- 10+ years of proven experience in product management or related roles.
- 1+ year of building AI based intelligent products
- 1+ year experience in using GenAI tools to perform product management tasks like conduct idea research, shaping, synthesis, roadmaps, requirements, prototyping, 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 location available for this role
- An MBA or related advanced degree
- Experience being accountable for value and viability results for an empowered product team.
- Demonstrated experience in modern product craft of delivering the right thing, in the right way, at the right time.
- Experience with lean solutions and rapid, inexpensive experimentation to emerge the right thing, in the right way, at the right time.
- Proven accountability for value, viability and P&L objectives for a product.
- Quick to reach expert-level knowledge within the product domain being served.
- Expert analytical and problem-solving skills.
- Ability to influence at all organizational levels through inclusion and leadership.
- Expert in modern product management craft and domain (tools, methods, and practices).
- Ability to navigate complexity and uncertainty.
- Favors small step action and evidence over detailed upfront planning and precision aiming.
- High levels of continuous customer and user engagement.
- Treats taste and judgment as the un-automatable moat-using AI to amplify, never replace, product sense-making.
- Ability to analyze data and derive actionable insights.
- Innovative and experimental approach to solving complex problems.
- Customer-Centricity: Deep understanding of customer needs and engagement patterns, driving teams to deliver solutions that customers love and that work for the business.
- Strategic Thinking: Ability to develop and execute a strategic vision for the product, aligning it with broader business objectives.
- 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.
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