Engineering Product Manager

Cisco

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CASan Francisco, CANew York, NY
Salary
$194,600–$285,700 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today
Closes
Nov 30, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $198k
This role $240k
$133k $302k
below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $172,300–$224,475 — the blue band above. At the midpoint, this role pays about $240k versus about $198k for comparable roles.

Based on 240 similar postings.

Employer

About Cisco

Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity

Cisco currently has 284 open roles on FindRole.

Listed pay typically runs $167,700–$245,200 across 210 roles with salary data.

Most-posted roles

View all roles at Cisco

At a glance

TL;DR · Engineering Product Manager

Engineering Product Manager This senior individual contributor role sits within a small team building a new product in the full-stack AI infrastructure space. You will own a major product area from customer discovery and strategy through delivery, launch, and ongoing improvement. Your daily responsibilities include defining multi-quarter roadmaps, translating customer needs into measurable outcomes, and leading build, partner, buy, and open-source decisions. You will manage complex requirements for APIs, platform services, and lifecycle management while aligning engineering, security, and marketing teams. The role requires deep expertise in Kubernetes, networking, storage, or security to solve problems for cloud operators and enterprise platform teams. You will specifically address the challenge of turning fragmented infrastructure into secure, governed, self-service token factories while managing capacity, policy, reliability, and lifecycle complexity.

What you'll do

  • Define the product vision, strategy, and multi-quarter roadmap for a major product domain.
  • Conduct direct customer discovery with cloud operators and AI developers to identify core needs.
  • Translate customer problems into clear product requirements, acceptance criteria, and phased release plans.
  • Lead build, partner, buy, and open-source decisions in collaboration with engineering and security teams.
  • Define and track operational metrics such as onboarding time, service reliability, and customer adoption.
  • Own market and competitive analysis, business cases, pricing, and go-to-market readiness.
  • Represent the product to customers, partners, and executives by translating technical capabilities into business outcomes.

What we're looking for

  • Bachelor's degree plus 12 years, master's degree plus 8 years, or equivalent practical experience in product management, engineering, or a related technical field.
  • Experience owning an enterprise infrastructure, cloud, or platform product through discovery, definition, delivery, launch, and operation.
  • Deep expertise in at least one of Kubernetes, networking, storage, or security, with working fluency across at least two of the remaining domains.
  • Experience defining technically complex requirements, including APIs, platform services, lifecycle management, or observability.
  • Demonstrated experience creating a product from the ground up, including turning open-ended problems into phased releases and measurable outcomes.
  • Proven ability to influence engineering and business leaders, resolve competing priorities, and communicate effectively with various stakeholders.
  • Direct experience operating production cloud or Kubernetes environments, including SLOs, incidents, upgrades, capacity management, observability, security, and cost management (preferred).
  • Fluency in AI infrastructure topics such as GPU clusters, accelerator scheduling, workload placement, high-performance network and storage paths, model serving, inference, and infrastructure telemetry (preferred).

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