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're looking for a hands-on Agentic AI Engineer to build practical, high-impact AI solutions for our Product Support organization.
This is not a research role. You'll design and ship real AI systems that improve support workflows and processes - building custom solutions where off-the-shelf tools fall short. The role also requires close collaboration across teams: aligning with different stakeholders' needs and priorities, and building strong, ongoing partnerships across the organization.
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) using frameworks like LangGraph / LangChain
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
Collaboration & Enablement:
Partner with business owners 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:
3 years of hands-on software development experience, including writing, maintaining, and delivering production-quality code
2+ years of GenAI development experience, with strong AI/ML focus - MUST
Strong Python skills and production mindset - MUST
Hands-on and deep understanding with LLMs, SLMs, prompt engineering, context engineering and agent-based systems
Experience with LangGraph, crewAI, Strands or similar orchestration frameworks
Experience in enterprise grade agentic solutions and bringing Agents into production
Experience in AWS Agent Core - Advantage
Solid understanding of ML workflows and MLOps principles
Strong analytical skills and ability to work directly with non-technical stakeholders
Builder mindset: proactive, independent, and impact-driven
Experience with Agentic AI driven applications like n8n, UiPath, Make –Advantage
Experience or familiarity with the Support domain – Advantage
