Sr Principal Engineer Software (AI Enablement & Strategy)

Palo Alto Networks•Seattle, WA

2d•$147,000 - $237,500•Hybrid

About The Position

As we rapidly accelerate our adoption of AI across the organization, we are looking for a highly skilled Senior Principal Engineer to lead our internal AI enablement and developer productivity strategy. In this high-visibility role, you will treat AI enablement as a core Developer Experience and platform challenge. You are a "0-to-1" builder who translates complex ML research and broad business requirements into secure, scalable, self-service software. By treating our internal engineers as your primary customers, you will build the strategy, infrastructure, and agentic workflows that democratize AI across the company. You will champion a culture of practical application, ensuring our AI tools perform reliably in a demanding, real-world enterprise environment. This role is located at our dynamic downtown Seattle office in the office 3 days a week.

Requirements

10+ years of software engineering experience designing large distributed systems, platform architecture, or enterprise-grade internal developer portals.
Software First, AI Second: You are a seasoned distributed systems/software engineer who is fluent in AI. While you may not be building foundational models from scratch, you can interpret ML research code and assess whether a challenge is a software problem or an infrastructure limitation.
Expertise in at least one modern programming language such as Python (type hints, Pydantic, etc.), Go, Java, C#, or C++.
Deep, hands-on experience with foundational LLMs, vector databases, and AI orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen), with a strong focus on taking prototypes into stable production.
0-to-1 Builder: You are comfortable navigating ambiguous environments, defining technical strategy, and writing initial code before scaling it across a large engineering organization.
Demonstrated ability to solve complex security, compliance, and access-control challenges in cloud environments (GCP, AWS, Azure).
Exceptional communication and change-management skills; ability to influence executive leadership on ROI while serving as the approachable "go-to" AI expert for engineering teams.
BS or MS in Computer Science, a related field, or equivalent professional/military experience.

Responsibilities

Democratize AI across the organization. Architect and implement the APIs, SDKs, and platform services that turn complex LLM capabilities and evaluation metrics into simple, self-service building blocks for our forward-deployed software engineers.
Rapidly prototype lightweight AI-enabled utilities and assess whether roadblocks are software-related or infrastructure-related before scaling them for production.
Act as a trusted, neutral arbiter to drive consensus on AI architectures across cross-functional work streams. Drive a "leverage first, build second" roadmap—evaluating existing ecosystem capabilities while designing custom microservices only when necessary.
Push the boundaries of operational automation by designing frontier agents that utilize generative AI, RAG pipelines, and knowledge graphs to transform incident response, DevOps, and daily engineering tasks.
Lower the barrier to entry for teams looking to leverage AI. Package development environments, simplify initial setups, and eliminate the infrastructure friction that traditionally blocks rapid AI adoption.
Solve the complex IT and access challenges required to deploy AI in a highly regulated cybersecurity environment. Partner with InfoSec and Legal to establish robust authentication flows, strict data access patterns, and ethical AI guardrails.
Set the gold standard for AI-assisted development internally. Own technical decisions end-to-end, rigorously balancing cutting-edge AI capabilities with cloud infrastructure costs, latency requirements, and system reliability.