Group Product Manager - AI Product Lead - Signals Engineering

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Regular or Temporary:

Regular

Language Fluency:
English (Required)

Work Shift:

1st shift (United States of America)

Please review the following job description:

The Group Product Manager - AI Signals Engineering owns the product strategy, roadmap, delivery alignment, and stakeholder engagement for the Signals Engineering domain. This role is responsible for translating enterprise signal and telemetry data - spanning system behavior, user interaction, agent execution, and workflow performance - into actionable product capabilities that drive AI quality, safety, and operational intelligence.

This is a hybrid product and domain leadership role. The Product Lead sets product vision for signals infrastructure, defines what gets built and why, drives cross-functional delivery alignment, and ensures the observability and intelligence layer needed to operate AI systems with confidence, improve continuously, and meet governance and audit requirements.

Daily work includes owning the signals product roadmap, writing product requirements and acceptance criteria, partnering with engineering to deliver telemetry and analytics capabilities, translating enterprise stakeholder needs into product priorities, and ensuring signal outputs are usable, trusted, and integrated into the AI delivery lifecycle.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

* Own the product vision, strategy, and roadmap for Signals Engineering, defining what telemetry, behavioral analytics, and AI observability capabilities get built, sequenced, and delivered.

* Translate enterprise stakeholder needs - from AI engineering, security, governance, QA, and business operations - into clear product requirements, prioritized backlogs, and delivery-ready specifications.

* Partner with engineering leads to define signals infrastructure, data capture patterns, telemetry pipelines, event schemas, and analytics delivery that serve AI quality and operational intelligence goals.

* Define what "good" looks like for AI signal coverage: what agent behaviors, prompt patterns, tool invocations, workflow outcomes, and system events must be captured, stored, and analyzed.

* Drive cross-functional delivery alignment across signals engineering, AI engineering, security, QA, data, and platform teams to ensure the observability layer is production-ready, trusted, and integrated.

* Own stakeholder engagement for Signals Engineering - communicating roadmap direction, delivery status, and signal-derived insights to engineering leaders, governance partners, and senior stakeholders.

* Establish product metrics and success criteria for signals capabilities, including signal coverage, data latency, analytics usability, and the degree to which signals drive measurable AI quality or risk improvements.

* Identify gaps in current signal coverage and prioritize the highest-value observability investments that improve AI safety, reliability, auditability, and continuous improvement velocity.

* Partner with AI security and adversarial testing teams to ensure signals infrastructure supports detection, investigation, and remediation of AI-specific risk patterns.

* Contribute to the Forge governance and audit readiness posture by ensuring signal data is complete, traceable, retained appropriately, and accessible for compliance and review purposes.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the…