Lead the design and delivery of next-generation scalable services for the Customer Support Tools team in IT at Palo Alto Networks.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus.
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 like LangChain / LangGraph) and A2A protocols to enable seamless interoperability between 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, safeguarding applications against vulnerabilities such as prompt injection through robust input/output validation models.
Principal Software Engineer, Go-To-Market (GTM) and CX Products
Design, build, deploy, and improve scalable, modern full‑stack web applications and associated services for YouTube Business Technology.
Responsibilities
Design, build, deploy, and improve scalable, modern full‑stack web applications using software development tools
Analyze problems and develop solutions, while identifying dependencies and resolving issues to drive implementation
Make technical contributions, including writing and reviewing design documents, tests, and code (e.g., JavaScript, Python, TypeScript, SQL)
Provide subject‑matter expertise and utilize comprehensive knowledge of Google's relevant technologies, principles, practices, and coding standards
Collaborate with cross‑functional users and stakeholders to identify pain points and devise innovative technical solutions
Requirements
Bachelor's degree in Computer Science, Electrical Engineering, Math or related quantitative field, or equivalent practical experience in software development
Design and own the architecture for deploying and operating AI capabilities at scale, including APIs and MCP servers that enable integration with products, agents, and applications.
Develop high-performance Python backend services for LLM inference orchestration, async job handling, streaming responses, and distributed data workflows supporting high-throughput operations.
Establish robust LLMOps and MLOps pipelines on Databricks (AWS) using MLflow, feature stores, prompt evaluation frameworks, model lineage tracking, and continuous retraining workflows to ensure reliable AI delivery.
Apply traditional ML and statistical modeling (regression, clustering, forecasting, ensemble methods) in hybrid architectures alongside LLMs for interpretable, explainability-first decision systems.
Translate R&D outcomes into scalable, reliable production solutions, collaborating with researchers to integrate and validate new models and techniques while optimizing inference latency, throughput, and cost without compromising output quality.
Requirements
Master's or Bachelor's degree in Computer Science, AI/ML, or Engineering
Support the U.S. Cyber Command Chief Artificial Intelligence Officer by providing technical expertise in large language models, generative AI, token economics, AI resource management, and enterprise AI operations.
Responsibilities
Develop strategies to manage, allocate, monitor, and optimize AI token usage across mission workloads.
Highly specialized technical role focused on LLM architectures, generative AI, and token mechanics within U.S. Government and Intelligence Community environments.
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