Senior Manager - Digital Product Management

American Express•Phoenix, AZ

About The Position

The Senior Manager, Digital Product Management for AI Ops leads product strategy and execution for a portfolio of AI-powered operations capabilities designed to move Technology Operations from manual, reactive incident response toward AI-assisted, AI-augmented, and increasingly autonomous operations. The role defines and manages roadmaps across capabilities such as agentic root-cause analysis, event correlation and noise reduction, operational copilots, knowledge and skills management, guided remediation, and safe self-healing workflows. Working at the intersection of product management, SRE, observability, ITSM, automation, data platforms, and responsible AI, this product leader translates operational pain points into AI-enabled capabilities, defines success metrics, prioritizes backlogs, and partners with engineering, SRE, application support, infrastructure, risk, compliance, and vendors to deliver production-grade products at enterprise scale. The role requires customer discovery and roadmap discipline, alongside technical fluency in 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.

Requirements

Bachelor's degree in Information Systems, Computer Science, Information Technology, Engineering, Business, or comparable experience.
At least 8 years of successful product management, engineering, deployment, or operations experience in enterprise-grade technology environments.
Experience product-managing AI, ML, GenAI, automation, observability, IT operations, SRE, or platform products.
Strong understanding of incident management, problem management, change management, ITSM workflows, and production operations.
Familiarity with AIOps capabilities such as event correlation, anomaly detection, root-cause analysis, predictive operations, automated remediation, and self-healing.
Ability to translate ambiguous operational problems into product strategy, roadmaps, user stories, requirements, and measurable outcomes.
Experience defining success metrics for AI or data-driven products, including adoption, quality, accuracy or helpfulness, operational efficiency, and risk outcomes.
Proven ability in Agile methodologies, communication management, product strategy, road mapping, requirements management, and feature prioritization.
Experience collaborating with senior stakeholders across technology, operations, risk, compliance, security, and vendor organizations to drive software solutions and innovation.
Technical fluency with cloud platforms such as AWS, Azure, or Google Cloud.
Employment eligibility to work with American Express in the United States; the company will not pursue visa sponsorship for these positions.

Nice To Haves

An advanced degree.
Experience with observability platforms, logging/metrics/tracing, ServiceNow or equivalent ITSM platforms, automation/orchestration tools, and enterprise cloud environments.
Familiarity with GenAI/LLM concepts, RAG, prompt engineering, agentic workflows, model evaluation, feedback loops, and responsible AI controls.
Experience with enterprise AI governance, auditability, RBAC, human-in-the-loop workflows, and risk-managed automation.
Certifications such as CompTIA A+, Network+, Security+, public cloud certification, product management certification, or Agile/SAFe certification.
DevOps knowledge for highly available IT infrastructure.
Experience with hybrid infrastructure, automation, DevOps, or SRE.

Responsibilities

Own the product vision, roadmap, backlog, and success metrics for AI Ops products spanning incident detection, triage, root-cause analysis, 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 using 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 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 with the broader AI Ops / Zero Ops roadmap.
Drive adoption through enablement plans, self-service onboarding journeys, product documentation, stakeholder communications, demos, feedback channels, and value realization tracking.
Establish and track product KPIs, including 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 capabilities are auditable, explainable, permissioned, appropriately human-governed, and safe for production use.
Evaluate internal and external AIOps, observability, automation, and agentic AI solutions; inform buy/build/partner decisions and ensure vendor capabilities integrate into the enterprise AI Ops ecosystem.
Lead cross-functional planning and operating routines across Product, Engineering, SRE, Application Support, Infrastructure, Program Management, and vendor partners to deliver capabilities from concept through production adoption.