Agentic AI Engineer

Welcome to the future of cloud networking and security! Cato Networks is the first company to converge enterprise networking and security into one centralized and global service that is delivered by cloud. It is led by networking and security pioneer Shlomo Kramer (Check Point, Imperva) and early investor (Palo Alto Networks, Exabeam, Trusteer and more). Cato’s unique technology inspired a brand-new product category, later named “SASE” by Gartner and a market expected to reach $28.5 billion by 2028. This is your opportunity to get on the rocket ship and join a company that is building a cutting-edge enterprise network and secure cloud platform, and is on a fast track to becoming the worldwide market leader – don’t miss it! We are looking for a Hands-On Agentic AI Engineer (Information Systems Team) to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization. The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end — writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions. Responsibilities: Partner directly with business teams to identify automation and optimization opportunities Design and implement agent-based AI workflows to automate internal processes end-to-end Design and build LLM-powered tools (agents, workflows, copilots) Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations Take solutions from idea → prototype → production Governance, Reliability & Security Ensure AI workflows comply with security, privacy, and compliance requirements Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed Monitor AI performance, errors, hallucinations, and drift Collaboration & Enablement: Partner with business owners and IS teams to identify automation opportunities Translate business requirements into AI-driven solutions Document AI flows, decision logic, and operational runbooks Educate internal teams on AI capabilities and limitations Requirements: 2-3 years of proven experience with AI solutions Strong hands-on software development experience, including writing, maintaining, and delivering production-quality code Strong GenAI development experience with LLMs, SLMs, prompt engineering, context engineering, and agent-based systems Strong Python skills and a production-focused engineering mindset Experience designing and building agentic AI workflows, RAG pipelines, LLM-powered applications, copilots, or intelligent automation solutions Experience bringing AI agents, GenAI applications, or automation solutions into production Solid understanding of APIs, integrations, databases, cloud environments, monitoring, logging, security, and deployment practices Ability to work directly with non-technical stakeholders and translate business needs into technical solutions Experience with AWS AgentCore, n8n, UiPath, Make, Workato, or similar is an advantage Experience with enterprise AI governance, security, compliance, and privacy requirements is an advantage Strong builder mindset: proactive, independent, hands-on, business-oriented, and impact-driven