Platform Product Manager (for AI Customer Interactions)

CORE PROFILE

An experienced Platform Product Manager with a proven track record of delivering customer‑facing AI and automation capabilities at scale.

This role is accountable for scaling the company’s customer support capacity by defining, delivering, and continuously improving AI‑powered customer interaction systems—including chatbots, voicebots, and agentic workflows—across the full product portfolio.

The Platform Product Manager drives business and operational impact by identifying improvement opportunities across people, process, tooling, and partners. The role operates at the intersection of conversational AI, customer experience, and support operations, ensuring AI resolves customer issues effectively while escalating seamlessly to human agents when needed.

What You Will Do

The Platform Product Manager is responsible for defining product requirements, specifications, success criteria, and rollout strategy for AI‑powered customer interaction systems across all channels, while working closely with engineering, AI, operations, and product teams.

Product Management, Development \& Support

• Define and own the product roadmap for AI‑powered customer interactions across all channels (chat, voice, in‑app), evolving from context‑enriched automation to agentic AI capabilities.

• Own the end‑to‑end AI customer experience, including conversation flows, persona, tone of voice, error handling, and resolution paths.

• Define requirements for multi‑turn, multi‑step conversation journeys that support complex customer needs.

• Establish the escalation framework—clearly defining when and how AI hands off to human agents, ensuring full context transfer to eliminate customer repetition.

• Define business rules and guardrails for agentic capabilities, including permitted actions, approval thresholds, and human‑in‑the‑loop requirements.

• Set clear automation targets, quality benchmarks, and phase‑based success criteria.

• Continuously integrate customer feedback and conversation data into product enhancements.

Knowledge \& Content Management

• Own the strategy for AI knowledge bases, including content scope, structure, freshness, and discoverability by AI systems.

• Define content governance and maintenance processes to ensure knowledge remains accurate as products, policies, and procedures evolve.

• Partner with operations and product teams to capture and codify tacit agent knowledge into structured, AI‑ready content.

Stakeholder Collaboration

• Partner closely with the Customer Service Group (CSG) to understand agent pain points, identify high‑value automation opportunities, and validate real‑world effectiveness.

• Act as the primary product counterpart for engineering and AI teams, contributing to architecture reviews, sprint planning, and technical trade‑off decisions.

• Coordinate with other product teams to ensure platform APIs expose the data and actions required for AI execution.

• Work with data and analytics teams to prioritize automation candidates, track performance, and quantify business and operational impact.

• Collaborate with compliance, security, and legal teams to ensure responsible AI governance, particularly around automated account actions and data privacy.

Process Optimization

• Analyze end‑to‑end customer interaction journeys to identify friction points, automation opportunities, and escalation reduction levers.

• Continuously refine AI‑to‑human handoff flows to improve efficiency, accuracy, and customer experience.

• Identify opportunities to reduce AI operating costs through improved conversation design, knowledge coverage, and model utilization.

Testing \& Implementation

• Define testing strategies and acceptance criteria, including conversation quality, edge‑case coverage, and regression testing prior to release.

• Monitor live performance to ensure resolution accuracy, customer satisfaction, and compliance objectives are consistently met.

Vendor Coordination

• Evaluate external AI platforms, conversational AI tools, and knowledge management solutions for capability, accuracy, and cost efficiency.

• Define integration requirements and work with engineering to onboard third‑party vendors, including LLMs, speech technologies, and knowledge platforms.

Data‑Driven Decision Making

• Establish continuous improvement loops using conversation logs, failure analysis, resolution metrics, and customer feedback.

• Leverage data insights to drive roadmap prioritization and AI performance optimization.

DISPLAYED SKILL MASTERY

• Deep familiarity with AI‑powered customer interaction systems (chatbots, voicebots, agentic workflows) in production support environments.

• Ability to understand and communicate technical concepts such as LLMs, RAG pipelines, conversational UX, and system design to both technical and non‑technical stakeholders.

• Strong grounding in customer support operations, including ticketing systems, agent workflows, and human‑AI collaboration models.

• Excellent organizational and prioritization skills across multiple workstreams.

• Strong stakeholder management and cross‑functional collaboration capabilities.

• Data‑driven mindset, using conversation data, quality metrics, and customer feedback to guide decisions.

• Proficiency in creating PRDs, user stories, journey maps, and process flow diagrams.

• Strong customer‑centric mindset, ensuring AI interactions solve real customer problems—not just deflect volume.

• Strong analytical and problem‑solving skills to translate operational needs into scalable AI solutions.

• High familiarity with financial services operations, regulatory constraints, and industry‑specific risks.

• Ability to thrive in complex, matrixed environments.

EXPECTED RESULTS

• AI Resolution Rate:

Increase the percentage of customer issues fully resolved by AI without human escalation.

• Customer Satisfaction:

Improve CSAT and NPS for AI‑handled interactions.

• Escalation Reduction:

Decrease overall escalation volumes and cost per interaction.

• AI Coverage:

Expand the range and complexity of issues AI can independently resolve.

• Escalation Quality:

Ensure full context transfer during AI‑to‑human handoffs.

• AI Response Quality \& Safety:

Maintain accurate, compliant, and appropriate AI responses through clear guardrails.

• Roadmap Delivery:

Deliver AI enhancements on time and in alignment with committed milestones.

What You Need to Succeed

• Minimum of 7 years total work as a Product Owner, Product Manager, or equivalent

• 3\+ years working on AI‑powered products, conversational AI, or customer‑facing automation

• Proven ability to communicate complex AI trade‑offs and product decisions to diverse stakeholders

• Experience working in cross‑functional teams (engineering, AI, operations, compliance)

• Demonstrated experience delivering AI customer interaction systems to production at scale (strong advantage)

• Background in FinTech, financial services, or payments (strong advantage)