AI Engineer, Agentic Systems (Quality Engineering)
Palo Alto Networks, Inc.Match Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, mid-level experience, metro location and popular AI role increase applicant competition.
Role demands specialized agentic-LLM and enterprise integration expertise, limiting cross-industry interchangeability.
Explicit 1–4 years, mandatory LLM/agent experience and enterprise integration skills tighten filters.
Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain agentic AI features, including multi-step business workflow automation using generative AI tools like LangGraph, LangChain, and AutoGen, integrated with enterprise systems such as Salesforce, SAP, and custom applications.
Build and enhance evaluation suites, safety guardrails, observability metrics, and responsible AI practices to ensure quality, security, and compliance of AI agents interacting across enterprise platforms.
Collaborate cross-functionally with architects, QE leads, product managers, and security teams to deliver reliable AI-enabled automation aligned with business and compliance requirements.
Minimum Requirements
1-4 years of professional software engineering experience or equivalent demonstrable capability.
Strong proficiency in Python or TypeScript/Node.js with experience in REST APIs, relational databases, asynchronous processing, and version control (Git).
Hands-on experience with LLM APIs including prompting, function/tool calling, and building working agent or RAG pipelines end to end.
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related technical field, or equivalent practical experience; Work Visa Sponsorship: Not available for this role.
Ideal Candidate Profile
Experienced in building autonomous AI agents or retrieval-augmented generation systems integrated with complex enterprise IT landscapes.
Skilled at safely integrating diverse APIs (Salesforce, SAP, custom) into automated workflows within secure, scalable enterprise environments.
Comfortable working in a structured SDLC with quality engineering and observability focus, able to translate ambiguous enterprise requirements into reliable, measurable automation solutions.