Sr. Staff IT SWE AI

Palo Alto Networks
Santa Clara, United States of America
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 236K

Job location

Santa Clara, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Automation of Tests
Azure
Cloud Computing
Cloud Engineering
Configuration Management
Code Review
Continuous Integration
Custom Software
Distributed Systems
Github
Identity and Access Management
Python
Linux kernel
Machine Learning
Node.js
Performance Tuning
Software Architecture
Reliability Engineering
Cloud Services
Prometheus
Software Engineering
TypeScript
Amazon Web Services (AWS)
Pulumi
Google Cloud Platform
Cloud Platform System
Autoscaling
Delivery Pipeline
Large Language Models
Multi-Agent Systems
Prompt Engineering
Multi-Cloud
Generative AI
Gitlab-ci
Kubernetes
Virtual Agents
Asynchronous Programming
Api Design
Terraform

Job description

As an AI-Native Cloud Software Engineer, you won't just manage environments; you will build the software engines, intelligent pipelines, and autonomous systems that power our cloud presence. We are shifting from rigid configuration management to AI-driven, self-healing software architectures., Multi-Cloud Generative IaC & Software-Defined Infrastructure: Architect and maintain scalable cloud systems across AWS, Azure, and GCP using Pulumi, AWS CDK, or Terraform. Integrate AI development workflows and custom LLM agents to accelerate safe infrastructure compilation, drift detection, and automated cross-cloud refactoring.

Intelligent Automation & Agentic Workflows: Engineer custom software utilities, internal services, and autonomous agents using (TypeScript/Node.js, Go, or Python, alongside frameworks like LangChain or CrewAI) to orchestrate complex provisioning, predictive auto-scaling, and closed-loop self-healing systems.

AI-Driven Cloud Governance & Economics: Leverage predictive machine learning models to analyze multi-cloud spend patterns, autonomously executing real-time resource-optimization strategies via API-driven software actions (e.g., dynamic spot-instance bidding, intelligent right-sizing across AWS, Azure, and GCP).

Cognitive Observability & Infrastructure Security: Implement next-gen observability frameworks (OpenTelemetry, Prometheus) coupled with AI anomaly detection. Embed security directly into the deployment pipeline, utilizing LLMs to automatically audit Cloud IAM policies, scan for vulnerabilities, and generate contextual patches.

Intelligent Container Orchestration: Manage production-grade Kubernetes clusters (EKS, AKS, GKE). Optimize resource allocation, cluster auto-scaling, and service meshes using AI-driven traffic routing and predictive capacity planning.

Autonomous Incident Response: Act as a tier-3 software escalation engineer for complex distributed systems anomalies. Help design and train our internal "On-Call AI Agent" to ingest logs, perform automated Root Cause Analysis (RCA), and submit pre-validated Pull Requests to resolve underlying system defects.

Requirements

  • Software Engineering & AI Orchestration: Strong software engineering fundamentals in TypeScript (Node.js), Go, or Python. Experience interfacing with LLM APIs (OpenAI, Anthropic, Google Vertex AI, AWS Bedrock), vector databases, and prompt engineering for systems-level orchestration.

  • Multi-Cloud & Containers: Deep proficiency in at least two major cloud platforms (AWS, Azure, GCP) with a strong architectural understanding of the third. Expert-level knowledge of Kubernetes (CKA preferred) and cloud-native networking.

  • Next-Gen CI/CD: Experience building intelligent delivery pipelines using GitHub Actions or GitLab CI, featuring integrated automated testing, security gates, and AI-assisted code reviews.

  • Systems Mastery: Deep understanding of Linux internals, distributed systems architecture, asynchronous programming patterns, and performance tuning, + Qualifications6+ years of experience in Cloud Software Engineering, Site Reliability Engineering (SRE), or Distributed Systems Infrastructure.2+ years of hands-on experience integrating AI tools, LLMs, or predictive analytics into deployment workflows, pipelines, or software platforms.Proven track record of architecting and operating large-scale, high-throughput distributed systems.Preferred:Agentic Problem-Solving: A mindset that moves past "how do I automate this task?" to "how do I build an autonomous system that solves this permanently?"Collaborative AI-First Culture: Ability to partner with Core AI/ML teams to bridge the gap between model deployment and high-availability cloud infrastructure.

Benefits & conditions

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 (https://benefits.paloaltonetworks.com/) .

$145,000.00 - $235,500.00/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.

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