Senior Manager-Digital Product Management

American ExpressPhoenix, AZ

About The Position

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.

Requirements

  • Bachelor's degree in Information Systems, Computer Science, Information Technology, Engineering, Business, or comparable experience; advanced degree preferred.
  • 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.
  • Demonstrated 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/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; hybrid infrastructure, automation, DevOps, or SRE experience preferred.
  • Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

Nice To Haves

  • 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 are pluses.
  • DevOps knowledge for highly available IT infrastructure preferred.

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 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 AI Ops capabilities from concept through production adoption.
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