AI Software Engineer

Position: Staff AI Software Engineer
** 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*
* We are seeking a dynamic Staff IT Software Engineer to lead the design and delivery of our next-generation scalable services. Leveraging Python, Django, FastAPI, React, and GraphQL within Google Cloud Platform, you will evolve our core architecture and drive our transition into AI-native engineering. As a technical leader, you will ensure our systems-including traditional microservices and emerging agentic workflows-are resilient, scalable, and innovative.

Key Responsibilities

+ Drive the strategic architectural vision and deployment of high-quality, scalable software assets using Python and React, ensuring long-term alignment with enterprise architecture.

+ Architect and govern advanced agentic systems using the Vertex AI Agent SDK (or alternative frameworks such as Lang Chain / Lang Graph) and A2A protocols to enable seamless interoperability among autonomous enterprise services.

+ Establish enterprise-wide AI Evaluation (Evals) frameworks and automated benchmarking pipelines to rigorously measure, monitor, and optimize LLM/agent performance across metrics like accuracy, safety, latency, and cost.

+ Define the organizational strategy and architecture for data retrieval pipelines, ensuring scalable and optimized utilization of vector embeddings, semantic search, and similarity-based retrieval patterns.

+ Establish enterprise-wide prompt-engineering standards and LLM security frameworks to safeguard applications against vulnerabilities such as prompt injection through robust input/output validation models.

+ Standardize and scale Model Context Protocol (MCP) servers to effectively bridge core enterprise IT data with LLM-driven applications across business units.

+ Partner closely with technical executives, product management, and cross-functional engineering teams to align AI initiatives with overarching business objectives and drive high-impact results.

+ Mentor and cultivate technical leaders and engineers across the organization, fostering a culture of excellence, applied learning, and accountability in full-stack and AI domains.

+ Take ultimate accountability for cross-team project outcomes, ensuring AI and software solutions meet rigorous enterprise-grade standards for security, quality, and performance.

** Qualifications*
* + Minimum of 9 years of related experience with a Bachelor's degree in Computer Science or a related field, or equivalent military experience.

+ 9+ years of professional experience in backend development with Python, utilizing frameworks like Django or FastAPI to design and build fault-tolerant microservice architectures.

+ Proven track record of architecting, deploying, and scaling production-grade Generative AI and LLM-powered applications.

+ Hands-on experience with LLM orchestration and agentic frameworks (e.g., Lang Chain, Lang Graph, or native cloud Agent SDKs).

+ Deep technical expertise in RAG architectures, including vector embeddings, semantic search, and working with vector databases.

+ Demonstrated experience implementing LLM guardrails, prompt injection defenses, and robust AI evaluation (Evals) workflows.

+ Demonstrated expertise in frontend development with JavaScript, Type Script, and React.

+ Expert-level proficiency in containerization and orchestration using Docker and Kubernetes (GKE).

+ Proven track record of architecting and delivering enterprise-grade software solutions from concept to production at scale.

Preferred Qualifications

+ Deep, hands-on experience with Google Cloud Platform, particularly Google Vertex AI.

+ Production-level knowledge of Agent SDK, Lang Chain, or Lang Graph frameworks, as well as A2A protocols and the implementation of MCP servers.

+ Experience integrating and scaling Agentic IDEs (e.g., Cursor, Windsurf) within professional development…