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