Senior Agent Product Manager

About the role

This is a forward‑deployed, customer‑facing position at the intersection of AI automation and enterprise financial services. You will own the end‑to‑end delivery of an AI agent platform into complex customer environments, acting as the primary technical and strategic partner for enterprise clients.

Key responsibilities

• Scope and lead end‑to‑end implementation projects that embed the AI platform into customer operations, driving strategic outcomes.
• Conduct deep‑dive discovery to define customer objectives, technical requirements, and operational landscape for successful deployment.
• Guide customers in tailoring and optimizing AI agent capabilities to solve unique operational challenges and maximize resolution rates.
• Analyze performance data to track AI effectiveness, drive continuous improvement, and ensure measurable value.
• Serve as the primary technical interface during pre‑sales cycles, supporting proof‑of‑concepts, due diligence, and transitions to implementation.
• Act as the voice of the customer internally, collaborating with AI, Engineering, and Sales teams to shape the product roadmap.
• Build scalable onboarding and implementation processes that set customers up for long‑term success.
• Manage project risks and governance related to AI deployment, ensuring compliance, security, and responsible AI standards.

Required profile

• 5+ years in forward‑deployed, customer‑facing technical roles delivering enterprise software or AI platform implementations.
• Track record of owning and delivering complex, multi‑stakeholder technical projects from scoping through implementation.
• Experience supporting pre‑sales cycles, including designing and running proof‑of‑concepts and technical due diligence.
• Experience managing compliance, security, or risk governance in regulated or enterprise technology deployments.
• Background in financial services, banking, or fintech is a strong plus.

Required skills

• Hands‑on experience with APIs, system integrations, and technical solution design.
• Proficiency with analytical tools, SQL, and data warehouses such as BigQuery.
• Familiarity with AI/ML product management, agent‑based automation, and responsible AI governance frameworks.