Job Title: Senior Agentic AI Engineer (Palo Alto Networks Ecosystem)
Job Location: Palo Alto CA
Job Type: Contract
Job Description:
- Multi-Agent Orchestration: Design and deploy collaborative agent swarms using frameworks like LangGraph CrewAI or AutoGen to automate complex security remediation workflows.
- Tool & Skill Engineering: Build Agent Skills and reusable toolkits that allow LLMs to interact securely with internal APIs databases and network protocols (BGP IPsec SD-WAN).
- Universal Connectivity (MCP): Implement the Model Context Protocol (MCP) to create standardized plug-and-play interfaces between agents and the PANW ecosystem.
- Context Engineering & Budgeting: Manage the Context Window as a resource-optimizing token usage through advanced RAG (Retrieval-Augmented Generation) and semantic caching.
- Sandboxed Execution: Develop Programmatic Tool Calling environments (e.g. Python sandboxes) where agents can execute code to filter and aggregate data before returning a final response.
- Agentic Validation: Build Evaluation LLM-as-a-Judge frameworks to measure agent accuracy latency and tool-use reliability before production deployment.
Technical Requirements:
- Languages: Expert-level proficiency in Python or Go (for high-performance backend orchestration).
- AI Frameworks: Deep experience with LangChain LangGraph LlamaIndex and Semantic Kernel.
- Model Context: Proven ability to implement MCP for secure agent-to-tool communication.
- Infrastructure: Hands-on experience with Kubernetes Docker and cloud-native architectures (GCP/AWS).
- Database Mastery: Experience with Vector databases (Pinecone Milvus Weaviate) and hybrid search strategies.
- Cybersecurity DNA: Familiarity with SOAR (Security Orchestration Automation and Response) and SASE architectures is a massive plus.
Job Title: Senior Agentic AI Engineer (Palo Alto Networks Ecosystem) Job Location: Palo Alto CA Job Type: Contract Job Description: Multi-Agent Orchestration: Design and deploy collaborative agent swarms using frameworks like LangGraph CrewAI or AutoGen to automate complex security remediat...
Job Title: Senior Agentic AI Engineer (Palo Alto Networks Ecosystem)
Job Location: Palo Alto CA
Job Type: Contract
Job Description:
- Multi-Agent Orchestration: Design and deploy collaborative agent swarms using frameworks like LangGraph CrewAI or AutoGen to automate complex security remediation workflows.
- Tool & Skill Engineering: Build Agent Skills and reusable toolkits that allow LLMs to interact securely with internal APIs databases and network protocols (BGP IPsec SD-WAN).
- Universal Connectivity (MCP): Implement the Model Context Protocol (MCP) to create standardized plug-and-play interfaces between agents and the PANW ecosystem.
- Context Engineering & Budgeting: Manage the Context Window as a resource-optimizing token usage through advanced RAG (Retrieval-Augmented Generation) and semantic caching.
- Sandboxed Execution: Develop Programmatic Tool Calling environments (e.g. Python sandboxes) where agents can execute code to filter and aggregate data before returning a final response.
- Agentic Validation: Build Evaluation LLM-as-a-Judge frameworks to measure agent accuracy latency and tool-use reliability before production deployment.
Technical Requirements:
- Languages: Expert-level proficiency in Python or Go (for high-performance backend orchestration).
- AI Frameworks: Deep experience with LangChain LangGraph LlamaIndex and Semantic Kernel.
- Model Context: Proven ability to implement MCP for secure agent-to-tool communication.
- Infrastructure: Hands-on experience with Kubernetes Docker and cloud-native architectures (GCP/AWS).
- Database Mastery: Experience with Vector databases (Pinecone Milvus Weaviate) and hybrid search strategies.
- Cybersecurity DNA: Familiarity with SOAR (Security Orchestration Automation and Response) and SASE architectures is a massive plus.
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