Distinguished AI Engineer (Office of the CTO)
Role details
Job location
Tech stack
Job description
As a Distinguished AI Engineer in the Office of the CTO (OCTO), you will shape the next of AI-powered security and developer-productivity solutions. You will lead exploratory research, rapid prototyping, and cross-functional pilots that fuse state-of-the-art foundation models with Palo Alto Networks' security platforms.
Your Impact
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Drive end-to-end AI integrations with industry-leading foundation models (e.g., current frontier LLMs) across text, code, image, and multimodal domains.
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Prototype and benchmark MCP and A2A protocols to enable dynamic orchestration of multiple agents and tools
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Lead context engineering & prompt design for RAG and agentic workflows; create evaluation harnesses to measure accuracy, latency, and cost
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Build proof-of-concepts that embed AI throughout the software-development life-cycle (SDLC)-planning, coding, code review, testing, and release-to quantify productivity gains
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Research and validate AI-driven cybersecurity use-cases (e.g., threat-hunting copilots, real-time anomaly triage) and partner with product groups to harden prototypes for production.
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Instrument metrics pipelines that track developer and security-analyst outcomes to demonstrate ROI of AI initiatives
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Craft executive-level narratives, demos, and visualizations that clearly communicate innovation roadmaps, technical trade-offs, and business impact
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Mentor senior engineers and researchers; foster a culture of experimentation, responsible AI, and security-first thinking
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Lead strategic external partnerships and technical advocacy, collaborating with major industry partners to shape defensive AI product roadmaps.
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Engage with policy and ethics working groups to ensure responsible and compliant AI deployment, including navigating legal and corporate communications reviews.
Requirements
Your Experience
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10+ years in software/ML engineering, with 2+ years leading applied Generative AI or LLM initiatives at scale.
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Proven expertise in: Large & Multimodal Models: fine-tuning, RAG, alignment, hallucination testing.
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Distributed systems & MLOps: containerized inference, model-versioning, feature stores.
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Programming: Python (required) plus one of Go, Java, Javascript.
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Cloud AI stacks (GCP Vertex, AWS SageMaker, Azure ML) and vector databases.
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Hands-on experience integrating AI into developer tooling (IDE plug-ins, CI/CD, observability dashboards).
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Deep understanding of cybersecurity concepts (attack vectors, threat intelligence, MITRE ATT&CK) and ability to translate them into AI features.
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Strong communication skills; comfortable presenting to VP/C-suite audiences, driving cross-functional alignment, and representing technical strategy at external conferences.
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B.S. or higher in CS, EE, Mathematics, or related field; M.S./Ph.D. or equivalent military experience
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Proven track record of mentorship and technical leadership across organizational boundaries.