Principal Software Engineer, Prisma Access

As a Principal Engineer on the Prisma Access team, you'll design and build the distributed backend services that form the backbone of our platform. You'll think broadly about all system components, weigh trade-offs for every design decision, and work with cutting-edge cloud technologies - integrating service APIs across multiple cloud providers (AWS, GCP, Azure, OCI) to deliver an optimal customer experience.

This is an AI-native engineering role. You won't just use AI as a productivity tool - you'll build LLM-powered and agentic features directly into the product, design systems that detect and defend against AI-era threats, and operate with AI-assisted development workflows (Cursor, Claude Code, Copilot, internal agents) as a daily standard. You'll also shape our monitoring infrastructure, optimize data collection pipelines, analyze system disruptions, and develop solutions that drive measurable improvements in reliability.

This is a rare opportunity to take ownership of a new product architecture and build it from the ground up, defining how AI changes what a cloud security platform can do.

Your Impact

Platform & Distributed Systems

• Analyze requirements, design, develop, and support highly scalable software features and infrastructure on our next-generation security platform - taking features from inception to production, ready for cloud-native deployment

• Architect and build distributed microservices that process traffic and configuration at scale for thousands of enterprise customers

• Write clean, testable, readable, and maintainable code that performs reliably under production load

• Build and automate monitoring, observability, and alerting infrastructure to ensure platform reliability and rapid incident response

• Participate in on-call rotations for production services and contribute to a culture of operational excellence

AI-Native Engineering

• Design and ship LLM-powered and agentic product features - including policy authoring assistants, intelligent troubleshooting agents, automated RCA, anomaly detection, and natural-language admin experiences

• Build production-grade RAG pipelines, tool-using agents, and multi-agent workflows over security telemetry, configuration data, and threat intelligence

• Develop evaluation harnesses, golden traces, and CI/CD quality gates for AI features - measuring accuracy, latency, cost, and safety with the same rigor applied to traditional services

• Implement guardrails, grounding, and human-in-the-loop controls to minimize hallucinations and ensure trustworthy behavior in security-critical contexts

• Apply ML/AI techniques to networking and orchestration problems: traffic classification, capacity prediction, smart routing, drift detection, and zero-day anomaly identification

Collaboration & Leadership

• Collaborate cross-functionally with Product Management, Development, QA, SRE, and Customer Support to deliver the roadmap and improve customer outcomes

• Actively guide testing strategy for critical components - including AI-powered test generation and autonomous QA workflows - balancing performance, supportability, and maintainability

• Mentor junior engineers, lead design reviews, and contribute to engineering best practices, including responsible adoption of AI-assisted development workflows

• Drive a results-oriented culture with a strong focus on execution, quality, and speed

• B.S. or M.S. in Computer Science, Electrical Engineering, or a related technical field - or equivalent practical experience

• 5+ years of professional software engineering experience building production-grade backend systems

• Proficiency in one or more of: Go, Python, Java, or C+* Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed systems

• Hands-on experience architecting services on at least one major public cloud - AWS, GCP, Azure, or OCI

• Working knowledge of networking protocols (TCP/IP, HTTP/HTTPS, TLS) and cloud network architectures (VPCs, load balancers, firewalls, NAT, peering)

• Proven experience developing and scaling complex distributed systems, including large-scale distributed databases (e.g., Cassandra, DynamoDB, Spanner, CockroachDB) and messaging/streaming systems (e.g., Kafka, Pub/Sub, SQS, NATS)

• Hands-on experience integrating LLMs into production services - API-based (OpenAI, Anthropic, Gemini) or self-hosted - including prompt engineering, structured outputs, function/tool calling, and basic eval design

• Fluency with AI-assisted development workflows - daily use of tools like Cursor, Claude Code, GitHub Copilot, or similar; able to apply them effectively without over-trusting them

• Strong written and verbal communication - able to author technical proposals, design specs, and architecture diagrams, and present them to both technical and non-technical audiences

Preferred Qualifications

• Production experience with agentic AI frameworks - LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, or equivalents

• Experience designing RAG architectures over enterprise data, including chunking strategies, embedding models, and vector databases (Pinecone, Weaviate, pgvector, Milvus, OpenSearch k-NN)

• Familiarity with the Model Context Protocol (MCP) and patterns for exposing internal systems as tools to LLMs and agents

• Experience building evaluation pipelines for LLM systems - offline evals, A/B testing, golden datasets, regression suites, LLM-as-judge patterns

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/) .

$147,000.00 - $237,500.00/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.