Engineering Program Manager

Cisco

Confirmed live 2 days ago High trust
Closes in 2 days Hybrid

Quick summary

Work type
Hybrid
Location
Milpitas, CA
Salary
$194,600–$285,700 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live 2 days ago
Closes
Nov 4, 2026 (soon)

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $193k
This role $240k
$128k $303k
below market most similar roles pay here above market

This role pays more than 81% of similar roles. Most pay $166,563–$219,650 — the blue band above. At the midpoint, this role pays about $240k versus about $193k 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 283 open roles on FindRole.

Listed pay typically runs $167,700–$245,200 across 222 roles with salary data.

Most-posted roles

View all roles at Cisco

At a glance

TL;DR · Engineering Program Manager

The Engineering Program Manager joins a platform team developing a unified, AI-native management platform that integrates Networking, Security, Observability, and Collaboration. In this role, you will own end-to-end execution for AI Canvas programs, managing cross-functional initiatives across platform architecture, agent frameworks, UX, data systems, and security. You will translate technical strategies into execution plans, lead agentic AI programs from use-case definition through production, and establish evaluation-driven delivery practices for AI quality, safety, latency, and cost. Key responsibilities include managing high-risk interdependencies, coordinating agent workflows, and communicating technical trade-offs to executive leadership. Required expertise includes cloud platforms, APIs, distributed systems, and modern AI development practices, specifically involving generative AI, LLMs, retrieval-augmented generation, and agent orchestration within an enterprise SaaS context.

What does a Engineering Program Manager earn in California?

Median $219650 from 63 postings across 3 companies.

See salary data

What you'll do

  • Own end-to-end execution of AI Canvas programs across platform architecture, agent frameworks, UX, and data systems.
  • Drive delivery of large, cross-functional AI releases from initial roadmap through general availability and post-launch stabilization.
  • Translate product and technical strategies into clear execution plans, milestones, interdependency tracking, and success metrics.
  • Lead agentic AI programs including use-case definition, model integration, grounding, evaluations, and human oversight.
  • Establish evaluation-driven delivery practices to measure AI quality, safety, latency, cost, and reliability before launch.
  • Manage high-risk programs by bringing structure to ambiguous initiatives and driving timely decisions across multiple teams.
  • Communicate program status, technical trade-offs, and critical-path risks to executive leadership with clear recommendations.
  • Partner with engineering and security teams to define validation, release, observability, and operational-readiness requirements.

What we're looking for

  • Bachelor’s degree with 12+ years of related experience, Master’s with 8+ years, or PhD with 5+ years of related experience.
  • Experience leading complex technical programs for enterprise SaaS products through production launch and ongoing operation.
  • Experience directly leading at least one generative AI, LLM-based, or agentic capability through development and production launch.
  • Previous experience leading cross-functional technical programs across a highly matrixed engineering organization.
  • Technical fluency in cloud platforms, APIs, distributed systems, data systems, and modern AI development and deployment practices.
  • Experience leading multi-team SaaS or AI programs involving cloud-native architecture, API integrations, and AI evaluations (preferred).
  • Experience with agent orchestration, RAG, evaluation frameworks, guardrails, and human-in-the-loop workflows (preferred).
  • Ability to translate complex technical risks and decisions for executive audiences and apply Agile methodologies (preferred).

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