Forward Deployed AI Product Manager

We are hiring a Forward Deployed AI Product Manager (FDPM) to be the connective tissue between our clients and our engineering teams. This is not a traditional PM role. You will live at the intersection of product strategy, technical delivery, and client partnership—spending meaningful time embedded with global retailers, e-commerce brands, hotel chains, and restaurant operators to deeply understand their workflows, then translating those insights into AI-powered solutions that ship.

Think of this as: part Product Manager, part Implementation Consultant, part Pre/Post-Sales Engineer. Whether you have run operations inside a retailer, hotel group, or restaurant brand, implemented enterprise software at an e-commerce, POS, PMS, or loyalty vendor, or advised retail and hospitality clients as a consultant—if you have felt the pull toward product and AI, this role was built for you.

• Trusted Advisory:
  Serve as the primary Product point of contact for a portfolio of retail, e-commerce, and hospitality clients, owning relationships across contact center operations, guest experience, digital commerce, IT, and store operations stakeholders, often working alongside C-suite sponsors.
• Workflow Observation:
  Lead structured discovery engagements—interviews, order journey mapping, queue observation, side-by-sides with agents, and document analysis—to surface automation opportunities and unmet guest, shopper, or operational needs.
• The "Art of the Possible":
  Connect client operational pain points to Talkdesk AI platform capabilities—while respecting brand voice, consumer privacy, and PCI constraints.

• Scope Alignment:
  Review pre-sales Statements of Work drafted by the Solution Architect to confirm scope, feasibility, and design alignment before signature.
• Workflow Translation:
  Translate real-world workflows—WISMO (Where Is My Order?), returns, exchanges, loyalty/rewards inquiries, reservation bookings, cancellations, check-in flows, and VIP guest routing—into structured product and configuration requirements with FDEs, Applied ML, and Solution Engineers.
• Specification Ownership:
  Own the quality and completeness of Autopilot design and specification documents for engineering handoffs, including required brand disclosures, payment verification steps, TCPA consent capture, and agent escalation criteria.
• Success Metrics Definition:
  Define business KPIs with clients (time-to-value, containment/call deflection, self-service completion rate, first-contact resolution, CSAT/NPS, average handle time, order modification cycle time, cost per contact).
• Scope Discipline:
  Enforce scope discipline during UAT—route out-of-scope requests to the Sales/Account team to follow formal change order processes.
• 0-to-1 Executions:
  Own deployments end-to-end (from pilot kickoff through go-live): manage timelines, stakeholder communication, change management, and the iteration cycle to production-ready deployments.
• Validation & Testing:
  Generate test criteria from build artifacts and conduct manual validation (e.g., live call testing, messaging flow validation, authentication paths) before approving client UAT.
• Compliance & Security:
  Partner with client legal, privacy, and security teams to clear control requirements (PCI DSS, TCPA, GDPR/CCPA) gating go-live.
• On-Site Go-Live:
  Drive client UAT to completion efficiently, including on-site travel for strategic accounts to accelerate testing and fine-tuning.
• Post-Launch Observability:
  Monitor deployed Autopilots post-launch using observability tooling, evaluating performance and resolving field issues.
• Value Handoff:
  Ensure clients and Customer Experience Managers (CXMs) can successfully measure business success metrics before…