Mgr, Product Management – (genai/ai Product Experience)

Product Manager for Deloitte's Zora AI agent platform, focusing on defining vision, roadmap, requirements, and delivery for role-/function-specific AI agent-enabled products. The role involves owning product strategy, translating needs into outcomes, leading discovery and delivery, defining product requirements for agent behaviors and integrations, driving data and integration requirements, managing trustworthy AI and risk, and supporting go-to-market efforts.

What you'd actually do

  1. Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
  2. 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.
  3. Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
  4. Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
  5. Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.

Skills

Required

  • Product Management experience (enterprise software, SaaS, platforms, or data products)
  • shipping products from concept to GA
  • delivering products involving AI/ML (GenAI preferred)
  • evaluation, monitoring, and iteration loops
  • product discovery (research, hypothesis testing, experimentation)
  • product delivery (requirements, backlog, release management)
  • enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines)

Nice to have

  • agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns)
  • 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)
  • manage multiple products with competing priorities and shared platform dependencies
  • launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces
  • stakeholder management and executive communication
  • partnering with engineering, design, data science, and risk/compliance teams
  • regulated or high-stakes environments

What the JD emphasized

  • shipping products from concept to GA
  • AI/ML
  • product discovery
  • product delivery
  • enterprise integration patterns
  • agentic architectures
  • LLM evaluation
  • regulated or high-stakes environments

Other signals

  • AI agent platform
  • enterprise users
  • product strategy and roadmap
  • agent behaviors
  • tool integrations
  • agent capabilities
  • trustworthy AI
  • GenAI