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# Technical Product Manager - Support / TAC

- **Company:** Cisco Systems, Inc.
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $154,900.0 - $225,300.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Process Model and Notation, Software Product Management, Multi-Agent Systems, Agentic-AI, Information Technology, Cisco
- **Published:** November 8, 2026
- **Apply:** https://www.sanjosejobsite.com/job.asp?id=3505219986&tx=DT11303UTI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Business, or related field
 * 5+ years of product management experience owning technical support, service-request, or customer-success platforms end to end
 * Hands-on experience with agentic AI, autonomous AI agents, or multi-agent orchestration frameworks
 * Proven expertise in support/ticketing lifecycle design including intake, entitlement, classification, assignment, and resolution flows
 * Experience defining governance for automated workflows, including autonomy tiers, confidence gating, and RACI accountability, * Background in technical support, TAC, or managed services, especially in networking or infrastructure
 * Familiarity with Cisco IQ, AgenticOps platform, AI Canvas, and lifecycle-risk concepts
 * Experience with event-driven or state-machine-based workflow design (e.g., CMMN, BPMN)
 * Knowledge of upsell/attach motions and converting support insights into cross-sell pipeline
 * Prior experience in AI/ML product strategy, AI product management, or applied AI engineering roles

## Description

Own the end-to-end product roadmap for AI-native Support/TAC capabilities, balancing immediate wins in deflection and entitlement accuracy with long-term domain ontology development. Define and optimize the pre-case intake experience, ensuring fast self-serve resolution while accurately admitting cases that require human intervention. Lead the design and governance of the SR Case lifecycle, improving classification, assignment, and resolution processes to drive measurable support efficiency. Partner across Product, Engineering, and Support leadership to codify domain events, confidence rules, and escalation policies that enable autonomous agent workflows. Success means delivering faster, smarter support outcomes that increase deflection rates, entitlement accuracy, and Professional Services pipeline conversion.