Senior Principal Engineer, Developer Productivity

Palo Alto Networks

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$243,000–$335,000 / yr
Posted
1 day ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $203k
This role $289k
$120k most similar roles pay here $358k

This role pays more than 92% of similar roles. Most pay $174,600–$231,000 — the shaded band above. At the midpoint, this role pays about $289k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Palo Alto Networks

Palo Alto Networks is a global cybersecurity company offering network security, cloud security, and endpoint protection solutions.

Palo Alto Networks currently has 40 open roles on FindRole.

Listed pay typically runs $164,000–$266,000 across 38 roles with salary data.

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View all roles at Palo Alto Networks

At a glance

TL;DR · Senior Principal Engineer, Developer Productivity

As a Senior Principal Engineer, Developer Productivity, you will join the team to design, prototype, and productionize AI agents and workflows across the software development lifecycle. You will build reusable agent skills, evaluation harnesses, and integration points while modernizing critical systems by using AI-assisted analysis to uncover undocumented behaviors and technical debt. Your daily work involves integrating approved AI capabilities into developer platforms, CI/CD pipelines, and IDEs while establishing secure, observable, and cost-effective workflows. You will utilize large language model APIs, agent orchestration, context engineering, and evaluation frameworks to improve delivery speed and quality. The role requires expertise in distributed systems, cloud infrastructure, and event-driven architectures to solve complex problems involving the automation of coding, testing, and deployment tasks within a high-scale enterprise environment while ensuring security and compliance standards are met.

What does a Engineer earn in California?

Median $209800 from 89 postings across 25 companies.

See salary data

What you'll do

  • Design and productionize AI agents and workflows for the entire software development lifecycle including coding, testing, and deployment.
  • Build reusable agent skills, evaluation harnesses, and reference implementations for internal developer platforms and CI/CD pipelines.
  • Use AI-assisted analysis to uncover undocumented code behavior and create modernization plans for critical legacy systems.
  • Implement security controls such as sandboxing, least-privilege access, and audit trails for all agentic workflows.
  • Develop "golden paths" and reusable patterns to scale AI adoption across multiple engineering teams.
  • Establish measurement frameworks to track engineering outcomes like lead time, test effectiveness, and operational costs.
  • Mentor engineers through architecture reviews, technical demonstrations, and workshops on AI-enabled development.
  • Represent the organization in industry forums and publish technical content regarding AI engineering practices.

What we're looking for

  • Must have a Bachelor’s degree with 15 years of experience, a Master’s with 12 years, or a PhD with 8 years in software engineering.
  • Experience operating at Senior Principal, Principal, or equivalent scope across multiple teams or domains.
  • Strong hands-on software engineering skills and a record of building and operating production systems.
  • Practical experience with LLM APIs, tool-using agents, agent orchestration, context engineering, evaluation frameworks, and AI observability.
  • Experience integrating AI capabilities into developer workflows, engineering platforms, or enterprise applications.
  • Strong knowledge of distributed systems, APIs, event-driven architectures, CI/CD, cloud infrastructure, testing, and production operations.
  • Experience modernizing complex, business-critical, or poorly documented systems.
  • Demonstrated ability to influence technical direction across organizations and communicate clearly with executive and non-technical audiences.
  • Experience introducing AI-assisted workflows in large/regulated enterprises (preferred).
  • Experience with enterprise platforms like ERP, CRM, HRIS, or finance systems (preferred).
  • Experience implementing AI security controls for data protection and prompt-injection defenses (preferred).
  • Familiarity with developer-productivity frameworks such as DORA and SPACE (preferred).
  • Evidence of external engineering leadership through publications, open-source contributions, or conference presentations (preferred).

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