Job DescriptionRole 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 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.
QualificationsKey Qualifications- 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.
Preferred / Nice to Have- 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.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.
