Applied AI Product Manager - Financial Services/Audit

Deloitte • Jersey City, NJ

33d • $113,100 - $232,300 • Hybrid

About The Position

The Applied AI Product Manager is a senior individual contributor accountable for the value and viability of a moderately complex product within a product line. The role leads empowered, cross-functional teams in solving customer problems aligned with high-value business needs, from product vision through execution. It balances customer needs and business objectives and is responsible for delivering valuable, viable, usable, and feasible solutions with measurable ROI and KPIs.

The role uses AI and agentic tools to accelerate the concept-to-cash learning loop, including research, analysis, prototyping, experimentation, and compliance work, while applying human judgment to product decisions. The Product Manager co-creates and communicates product vision, strategy, and roadmaps; conducts user and competitive research; guides teams toward priority user and business needs; and promotes continuous learning, experimentation, and outcome-focused product practices.

The position is part of Deloitte Product Engineering (PxE), which develops agentic AI-enabled solutions for Deloitte and global clients. Candidates must be commutable to one of the listed locations and work from their local office at least three days per week. Travel may average 0–20%, depending on work and clients. Preferred locations are Hermitage and Tampa; other listed locations are New York, Dallas, Jersey City, and Morristown.

Requirements

• Bachelor’s degree in business, marketing, engineering, or a related field.
• At least 6 years of experience in lean product management or related roles, including translating product concepts and opportunities into measurable, value-based features and user stories/intents with clear acceptance criteria.
• At least 3 years of enterprise-scale experience across multiple business areas.
• At least 1 year of experience building AI-based intelligent products.
• At least 1 year of experience using GenAI tools for product management tasks such as idea research, shaping, synthesis, roadmaps, requirements, prototyping, and testing.
• At least 1 year of experience in financial services or an audit firm.
• At least 1 year of hands-on experience with a major cloud platform (Azure, AWS, or GCP), including working proficiency with observability tools to debug issues from logs and metrics and the ability to write basic log queries such as KQL or SQL.
• Experience with product delivery tools such as Azure DevOps (ADO) or Jira.
• Ability to work independently and collaboratively as part of a team.
• Effective written and verbal communication skills, meticulous attention to detail, and quality-focused work.
• Ability to build and sustain professional relationships and maintain a professional demeanor.
• Ability to lead projects or workstreams, mentor others, and provide clear guidance.
• Ability to prioritize multiple tasks in a fast-paced, dynamic environment and meet deadlines.
• Ability to travel an average of 0–20%, depending on work and clients.
• Ability to work in a local office at least 3 days per week and reside within commuting distance of a listed location.

Nice To Haves

• MBA or a related advanced degree.
• Significant expertise and leadership in modern, lean product management practices, including delivering the right solution in the right way at the right time.
• Proven accountability for product and empowered-team value, viability, and P&L objectives.
• Deep understanding of customer needs and engagement patterns, with expertise in customer-centric methods and practices.
• Ability to develop and execute product strategy aligned with broader business objectives.
• Exceptional analytical and problem-solving skills.
• Learning-forward, experimental, and value-oriented mindset; ability to navigate complexity and uncertainty.
• Fluency orchestrating multiple AI agents across research, insight, prototyping, specification, coding, and compliance workflows, with guardrails that capture assumptions, confidence levels, and sources of truth.
• Understanding of deterministic logic versus probabilistic generation, and ability to design safeguards for hallucination, bias, and drift; use evaluation harnesses before launch and monitor drift afterward.
• Experience with modern agentic AI tools such as Claude Code, Claude Co-work, OpenAI Codex, Cursor, and Visual Studio Code.

Responsibilities

• Be accountable for product value and viability, including demonstrating measurable ROI.
• Drive strategy-aligned solutions and establish, measure, and analyze KPIs to guide future strategy.
• Use AI to gather outcome evidence early and often and lower total cost of ownership.
• Co-create, own, and evangelize product vision, strategy, and roadmap in alignment with product-line and business goals.
• Collaborate with business stakeholders, engineering, experience, and delivery teams to shape product direction.
• Use AI to expedite research, gather evidence, deepen domain knowledge, simulate future scenarios, and develop strategic product visions.
• Conduct user research and competitive analysis, using AI agents to synthesize research while maintaining direct engagement with users and stakeholders.
• Guide teams toward solutions that address priority user and business needs, and analyze data to derive actionable insights.
• Use experimental approaches, including disposable AI-built prototypes, to validate solutions quickly.
• Work side by side with cross-functional teams to achieve KPI outcomes and promote outcome-focused product practices.
• Build empowered teams and product communities with collective product ownership, using AI and agentic tools to improve outcomes.
• Promote rapid, ongoing learning and adaptation; improve processes to reduce waste and accelerate value delivery.
• Remove obstacles to maintain continuous value flow and share knowledge and best practices within the product vertical community.
• Use AI to test assumptions, validate ideas before they enter the backlog, and build early prototypes that validate architecture and solutions.
• Apply guardrails across agentic workflows, evaluate AI risks and performance, and determine when AI should not be used.

Benefits

• Discretionary annual incentive program, subject to program rules and individual and organizational performance.
• Broad range of employee benefits.
• Opportunities for professional development, including on-the-job learning, formal development programs, leadership opportunities, mentorship, and skill building.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior