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Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.

Key Responsibilities:

• Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
• Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
• Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
• Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
• Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
• Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
• Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
• Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
• Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.

Required Qualifications:

• 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
• 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
• 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
• 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
• Limited immigration sponsorship may be available
• Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred:

• Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
• Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
• Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
• Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
• Proven ability to manage multiple products with competing priorities and shared platform dependencies.
• Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
• Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
• Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.

Key Deliverables

• Product strategy and 12-18 month roadmap with measurable outcomes.
• PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
• Use-case catalog and prioritization model (value, feasibility, risk, readiness).
• MVP/pilot plans with success metrics, rollout phases, and scale criteria.
• Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
• Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
• Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.

How success will be measured (example outcomes)

• Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
• Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
• Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
• Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
• Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
• Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).

Working model & stakeholders 

• Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
• Core stakeholders:
• Engineering (platform + product squads)
• Data Science / Applied AI (models, evaluation, tuning)
• Design / Research (UX, workflow design, prototyping)
• Cybersecurity & Privacy (security controls, data protection)
• Risk, Legal, Compliance (AI governance, auditability, policy alignment)
• Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
• Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
• Customer/Client stakeholders (product owners, process owners, IT, operations)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113100 - $232300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#EA_ExpHire 

Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.

Key Responsibilities:

• Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
• Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
• Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
• Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
• Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
• Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
• Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
• Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
• Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.

Required Qualifications:

• 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
• 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
• 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
• 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
• Limited immigration sponsorship may be available
• Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred:

• Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
• Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
• Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
• Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
• Proven ability to manage multiple products with competing priorities and shared platform dependencies.
• Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
• Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
• Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.

Key Deliverables

• Product strategy and 12-18 month roadmap with measurable outcomes.
• PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
• Use-case catalog and prioritization model (value, feasibility, risk, readiness).
• MVP/pilot plans with success metrics, rollout phases, and scale criteria.
• Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
• Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
• Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.

How success will be measured (example outcomes)

• Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
• Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
• Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
• Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
• Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
• Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).

Working model & stakeholders 

• Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
• Core stakeholders:
• Engineering (platform + product squads)
• Data Science / Applied AI (models, evaluation, tuning)
• Design / Research (UX, workflow design, prototyping)
• Cybersecurity & Privacy (security controls, data protection)
• Risk, Legal, Compliance (AI governance, auditability, policy alignment)
• Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
• Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
• Customer/Client stakeholders (product owners, process owners, IT, operations)

The wage range for this role takes into ...