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Senior AI Software Engineer

  • CA, United States

$129,200.00 - $209,000.00/yr Our Commitment

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Job details

Pay
$129,200.00 - $209,000.00/yr Our Commitment
Experience
Experience: 2–4 years of professional software engineering experience (or 1–3 years with a Master’s degree).
Posting language
English
Posted

Original job description

Our Mission

At Palo Alto Networks®, we’re united by a shared mission - to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place.

Who We Are

In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us!

We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary

Key Responsibilities

AI Solutions & Application Development Full-Stack & Microservices Engineering: Design, build, test, and deploy scalable services and web applications using Python (FastAPI/Django), React, and modern microservice patterns.

GenAI & Workflow Automation: Implement GenAI tools, multi-step agentic workflows, RAG systems, and API integrations to automate GTM logic across sales, support, and business applications.

Architecture Support: Collaborate with lead engineers and architects on solution designs, contributing to proxy-first AI setups and unified API endpoints to streamline LLM integration.

Quality, Observability & Production Operations AI Observability & Monitoring: Instrument tracing and logging for LLM inputs/outputs, model latency, prompt performance, and cost tracking using modern observability platforms.

Testing & Quality Assurance: Participate in setting up evaluation frameworks ("LLM as a Judge") and feedback loops to identify model drift, fix bottlenecks, and maintain high output quality.

Security & Guardrails: Implement foundational input/output guardrails to protect against prompt injection, guard sensitive data (PII), and ensure reliable error handling and system resilience.

Delivery & Collaboration Agile Execution: Own user stories end-to-end from code implementation through CI/CD deployment and production support.

Cross-Functional Collaboration: Partner with product managers and business stakeholders to clarify technical requirements and resolve complex issue root causes in production environments.

Qualifications

  • Experience: 2–4 years of professional software engineering experience (or 1–3 years with a Master’s degree).
  • Education: Bachelor’s degree in Computer Science, Information Technology, or equivalent practical experience.
  • Backend Mastery: Strong proficiency in Python, including frameworks like FastAPI or Django, for building APIs and microservices.
  • GenAI / AI Stack: Hands-on experience building applications using modern LLMs (e.g., OpenAI, Anthropic Claude, Llama) and orchestration tools (e.g., LangChain, LangGraph, or LlamaIndex).
  • Frontend Basics: Hands-on experience with modern JavaScript/TypeScript and React.
  • Core Engineering Foundations: Good understanding of RESTful API design, relational/NoSQL databases, version control (Git), CI/CD pipelines, and Agile practices.

Preferred

  • Containers & Cloud: Hands-on experience with Docker, Kubernetes, and major cloud platforms (GCP, AWS, or Azure).
  • AI Tracing & Observability: Familiarity with tools like LangSmith, Arize, HoneyHive, or OpenTelemetry.
  • Enterprise Integration: Exposure to enterprise application lifecycles (CRM, GTM, or Lead-to-Cash processes).

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

$129,200.00 - $209,000.00/yr Our Commitment

We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together.

We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at accommodations@paloaltonetworks.com.

Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics.

All your information will be kept confidential according to EEO guidelines.

Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

More about this job

Skills

  • Microservices
  • Python
  • Django
  • React
  • Workflow
  • Sales
  • Quality assurance
  • Collaboration
  • CI/CD
  • Computer science
  • Computer technology
  • JavaScript
  • TypeScript
  • RESTful API
  • NoSQL
  • Git
  • Agile
  • Docker
  • Kubernetes
  • Google Cloud
  • AWS
  • Microsoft Azure

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