Principal AI Software Engineer

Palo Alto Networks

1d•$167,000 - $270,500•Onsite

About The Position

As a Technical Leader developing AI applications in the GTM/CX domain, you will define the architectural blueprint for scalable AI/ML and agentic systems that transform our sales and customer experience motion. Demonstrated experience in understanding Sales Domain, Customer Support, and services business processes and operations workflows. Establish standards for safety, guardrails, reliability, observability and performance across all AI/ML/Agentic components. Lead design and implementation of ML/LLM/GenAI-powered agents capable of planning, multi-step execution, self-correction, and collaboration with humans or other agents. Drive end-to-end solution development from prototype to production, ensuring scalability, reliability, safety, observability, and performance. Build, fine-tune, or adapt LLMs, multimodal models, and specialized agent models. Build, evaluate, and integrate traditional AI/ML/Statistical models into agentic workflows. Develop advanced reasoning pipelines, retrieval systems, and knowledge graphs integrations that support autonomous task execution. Ensure production readiness through robust testing, evaluation frameworks, and real-world performance validation. Partner with data engineering to design high-quality datasets and synthetic data pipelines and feedback loops for continual learning. Mentor and guide data scientists and engineers, elevate data science and engineering practices across the organization. Communicate complex technical decisions and trade-offs to executives and cross-functional stakeholders.

Requirements

Masters/PhD in Computer Science, AI, Data Science or related field.
15+ years in data science, software engineering, data engineering, ML or Applied AI experience, including architecting large-scale distributed systems.
Proven experience designing and deploying production ML, LLM-powered applications, including agentic systems.
Deep expertise in developing conversational agents and advanced intelligent multi-agent automation systems
Demonstrated experience with orchestration frameworks like LangChain, LangGraph etc.
Up-to-date with LLM evolution like GPT, Anthropic, Llama models etc.
Demonstrated ability to lead high-ambiguity cross-team technical initiatives.
Hands-on experience in building supervised, unsupervised, and semi-supervised models/solutions.
Strong proficiency in SQL to analyse structured relational databases.
Strong proficiency in at least one core language (Python, Go, Java, or equivalent).
Strong knowledge of distributed systems, microservice architecture, and cloud platforms (AWS/Azure/GCP).

Nice To Haves

Excellent communication skills and the ability to influence at all levels

Responsibilities

Define the architectural blueprint for scalable AI/ML and agentic systems
Establish standards for safety, guardrails, reliability, observability and performance across all AI/ML/Agentic components
Lead design and implementation of ML/LLM/GenAI-powered agents capable of planning, multi-step execution, self-correction, and collaboration with humans or other agents
Drive end-to-end solution development from prototype to production, ensuring scalability, reliability, safety, observability, and performance
Build, fine-tune, or adapt LLMs, multimodal models, and specialized agent models
Build, evaluate, and integrate traditional AI/ML/Statistical models into agentic workflows
Develop advanced reasoning pipelines, retrieval systems, and knowledge graphs integrations that support autonomous task execution
Ensure production readiness through robust testing, evaluation frameworks, and real-world performance validation
Partner with data engineering to design high-quality datasets and synthetic data pipelines and feedback loops for continual learning
Mentor and guide data scientists and engineers, elevate data science and engineering practices across the organization
Communicate complex technical decisions and trade-offs to executives and cross-functional stakeholders