Sr Principal AI Engineer; IT Go-To-Market & Customer Experience
Listed on 2026-01-02
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Company Description Our Mission
At Palo Alto Networks everything starts and ends with our mission:
Being the cybersecurity partner of choice, protecting our digital way of life.
Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are.
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 Description Your CareerYou will join a dynamic and fast‑paced team of seasoned fellow engineers designing and developing multi‑tiered applications in a rapidly growing company. As a Sr Principal AI Engineer, you will leverage your extensive experience to act as the trailblazer, helping us build and innovate enterprise‑grade full‑stack systems with a specific focus on Generative AI transformation.
We are looking for a highly hands‑on, extremely technical leader to architect the next generation of our internal and external business applications. You will move beyond traditional software engineering to design intelligent, agentic workflows that revolutionize our Go‑To‑Market (GTM) processes.
Your Impact AI Architecture & Strategy- Architect a Proxy‑First AI Ecosystem:
Lead the design and implementation of an “AI Gateway” intermediary layer to ensure vendor independence, allowing seamless switching between LLMs (e.g., GPT‑4, Llama, Anthropic) without refactoring core application code. - Unified API Design:
Build a single, unified API endpoint that abstracts the complexities of individual LLM providers, providing centralized control for access and security.
- Deep System Visibility:
Implement comprehensive observability pipelines specifically for GenAI to track trace‑level data, prompt inputs/outputs, and model latency. - Cost & Performance Optimization:
Create architecture that optimizes performance and expense by routing simpler queries to cost‑effective models. - Feedback Loops:
Integrate observability data into the development cycle to identify bottlenecks, high‑latency chains, and model drift in real‑time.
- Agentic AI Leadership:
Institute and promote innovative thinking by incorporating agentic AI, designing sophisticated Multi‑Agent Systems and Agent‑to‑Agent (A2A) workflows. - Business Workflow Automation:
Apply GenAI to complex Go‑To‑Market (GTM) business logic, automating workflows such as customer support processes and entitlement platforms. - Evaluation Frameworks:
Pioneer “LLM as a Judge” testing methodologies to automate quality assurance, using capable models to evaluate the correctness, tone, and helpfulness of system outputs.
- AI Safety Implementation:
Build robust guardrails to filter inputs and outputs, ensuring the prevention of PII exposure, offensive content, and prompt injection attacks. - Adversarial Defense:
Develop detection mechanisms including keyword filtering, behavioral analysis, and adversarial training to protect model instructions from manipulation.
- 15 years of overall IT system architecture, design, development, and deployment experience.
- Hands‑On Technical Leadership:
Proven track record leading technical teams in Agile/Scrum environments for large‑scale implementations with aggressive timeline. - Business Process:
Experience partnering with business stakeholders to design workflows for Go‑To‑Market (GTM), sales, or support operations. - Education:
Bachelor’s degree or equivalent in Computer Science or a related field. - Communication:
Strong verbal and written communication skills with the ability to explain complex AI concepts to senior leadership.
- GenAI Stack:
Extensive knowledge in building modern applications using Large Language Models (LLMs) such as Llama 3, GPT‑4, and Anthropic. - LLM Observability:
Deep experience building and maintaining…
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