Senior Manager - Digital Product Management

Job d:

Location:

Phoenix, AZ, United States;
New York, NY, United States Salary: $123000 - $215250 annually + bonus + benefits

Job Function:
Product

Schedule:

Full time

Shift: Day Workplace:
Hybrid Career Area:
Product Company:
American Express Description Joining  Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success.

Because Amex Tech is powered by our technology, our culture, and our colleagues.

The Technology organization enables and accelerates the company’s growth strategies, delivering global capabilities and services in support of Amex’s customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights.

Role focus:
Lead product strategy and execution for AI-powered operations capabilities that move Technology Operations from reactive incident response toward AI-assisted, AI-augmented, and safely automated operations.

As a Senior Manager, Digital Product Management for AI Ops, you will lead product strategy and execution for a portfolio of AI-powered operations capabilities that help transform Technology Operations from manual, reactive incident response to AI-assisted, AI-augmented, and increasingly autonomous operations. You will define and manage product roadmaps across agentic root-cause analysis, event correlation and noise reduction, operational copilots, knowledge and skills management, guided remediation, and safe self-healing workflows.

This role sits at the intersection of product management, SRE, observability, ITSM, automation, data platforms, and responsible AI. You will translate operational pain points into AI-enabled product capabilities, define success metrics, prioritize the backlog, and partner closely with engineering, SRE, application support, infrastructure, risk, compliance, and vendor partners to deliver production-grade AI Ops products at enterprise scale.

The ideal candidate is a product leader who can combine strong customer discovery and roadmap discipline with the technical fluency to reason about AI/ML systems, GenAI and agentic workflows, observability data, knowledge quality, model evaluation, human-in-the-loop controls, and governed automation in a regulated environment. Responsibilities Own the product vision, roadmap, backlog, and success metrics for AI Ops products across incident detection, triage, RCA, proactive risk detection, guided remediation, and self-healing automation.

Translate customer and operational needs from SRE, Application Support, Mission Control, infrastructure, and platform teams into product requirements, user journeys, acceptance criteria, and measurable outcomes.

Define AI-enabled workflows that use observability data, ITSM data, knowledge sources, dependency maps, automation catalogs, and operational feedback to improve detection, diagnosis, remediation, and post-incident learning.

Partner with engineering and architecture teams to shape agentic product capabilities, including agent orchestration, skills, tools, prompts, knowledge retrieval, memory, evaluation, feedback loops, and governance controls.

Prioritize features based on customer value, operational impact, risk reduction, adoption, cost-to-serve, and alignment to the broader AI Ops / Zero Ops roadmap.

Drive adoption of AI Ops capabilities through enablement plans, self-service onboarding journeys, product documentation, stakeholder communications, demos, feedback channels, and value realization tracking.

Establish and track product KPIs such as MTTR, MTTD, alert-noise reduction, incident-volume reduction, manual-effort reduction, AI-assisted resolution rate, user adoption, recommendation helpfulness, and automation execution.

Partner with risk, security, privacy, compliance, and governance stakeholders to ensure AI Ops capabilities are auditable, explainable, permissioned, human-governed where appropriate, and safe for production use.

Evaluate internal and external AIOps, observability, automation, and agentic AI solutions; inform…