Cato Networks is the converged network and security cloud for the AI era. 

As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI’s potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents. 

Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide. 

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
• Monitor AI performance, errors, hallucinations, and drift
• 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