Staff Engineering Product Manager
C
CiscoCloud computing, Observability
This position is fully remote and can be performed from any location within the United States.Full-TimeStaff
Salary171,600 - 245,000 USD per year
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Job Details
- Experience
- Bachelor’s degree with 8 years of related experience, master’s degree with 6 years of related experience, PhD with 3 years of related experience, or equivalent practical experience.
- Required Skills
- Artificial IntelligenceCloud ComputingKubernetesProduct ManagementDevOpsMicroservices
Requirements
- Bachelor’s degree with 8 years of related experience, master’s degree with 6 years of related experience, PhD with 3 years of related experience, or equivalent practical experience.
- Experience managing technically complex products in enterprise software, cloud computing, data platforms, infrastructure, observability, or artificial intelligence.
- Experience defining product strategy, roadmaps, requirements, milestones, and measurable success criteria for software products.
- Experience conducting customer research and using qualitative and quantitative evidence to prioritize product opportunities.
- Experience partnering with engineering and design teams throughout product discovery, development, launch, adoption, and improvement.
- Experience building or managing AI-powered, generative AI, or agentic products.
- Working knowledge of observability, Kubernetes, microservices, distributed systems, and DevOps or site reliability engineering practices.
- Familiarity with metrics, logs, traces, alerts, incident response, root-cause analysis, and production operations.
- Experience using AI-assisted development tools, such as Codex or Claude, to create prototypes, demonstrations, or proofs of concept.
- Ability to evaluate technical trade-offs, align cross-functional teams around measurable outcomes, and represent products with customers, advisory councils, internal stakeholders, and senior leaders.
Responsibilities
- Lead the strategy and roadmap for AI agents spanning detection, troubleshooting, and remediation.
- Set 12–18-month goals, milestones, and success measures aligned with customer and business needs.
- Discover high-value problems through customer interviews, product data, field feedback, market research, and competitive analysis.
- Prototype concepts with tools such as Codex, Claude, and similar AI development platforms to test workflows, gather feedback, and accelerate product decisions.
- Define requirements and evaluation methods for agent accuracy, reliability, explainability, safety, and user trust.
- Prioritize new capabilities, platform investments, customer requests, technical debt, and quality improvements.
- Partner with engineering and design from discovery through delivery, then measure adoption and refine the product.
- Represent the product with customers, advisory councils, internal teams, and company leaders.
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