Agentic AI Engineer - Product Support
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Before you apply
LocationIsrael, Tel Aviv, Tel Aviv District
Work modeon-site
Typefull-time
SeniorityMid
Experience3+ yrs
DepartmentProduct Support
Company size1,001–5,000 people
PostedAug 17, 2026 · 2mo ago
Verified live11h ago
At a glanceSummarised by Seekless from the posting.
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
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 in AWS Agent Core - Advantage
Experience with Agentic AI driven applications like n8n, UiPath, Make – Advantage
Experience or familiarity with the Support domain – Advantage
Skills
Python
LangGraph
LangChain
RAG
LLMs
SLMs
AWS Agent Core
n8n
UiPath
Make
MLOps
About the company
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.
About the role
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