Channel Sales Engineer, AI Security
Cato NetworksSingaporePosted 24 March 2026
Tech Stack
Job Description
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 seeking an APJ AI Security Specialist to promote, demonstrate, and deliver training on our AI security capabilities. This position is primarily channel-oriented: Channel SEs across APJ will request support from the AI Security Specialist to keep our partner ecosystem up to date. Additionally, the AI Security Specialist will support Cato Field SEs in conducting large-scale AI security evaluations, demonstrations, and proofs of value if needed.
Responsibilities :
Lead and drive technical validation of Aim Security solutions to EMEA partners and prospects
Deliver compelling product demonstrations and presentations
Become a centre of expertise on AI Security
Respond to functional and technical elements of RFIs/RFPs with partners on AI Security projects
Communicate feedback, requests and technical perspectives on product evolution to Product Management teams
Stay up to date on AI security trends, emerging technologies, and competitor offerings.
Travel throughout sales territory (APJ)
Requirements :
LLM/GenAI internals: Deep understanding of transformers, embeddings/tokenization, context windows, decoding, and limits (hallucinations, calibration). Can explain when to use prompting vs RAG vs fine-tuning and why.
End-to-end AI system architecture: Understands AI application stacks (model gateway, orchestration, tools/function calling, RAG/vector DB, telemetry) and how data/control flows create risk. Able to review designs and spot weak links.
AI threat modelling expertise: Fluent in GenAI attack classes (prompt injection indirect injection, data poisoning, model extraction/inversion, supply-chain risks). Can map threats to concrete mitigations and residual risk.
Security evaluation red teaming: Can build/run adversarial test harnesses for LLM apps (attack prompts, regression suites, grounding checks) and define metrics tied to security outcomes. Comfortable iterating from findings to fixes.
Data and privacy risk reasoning: Strong grasp of data governance for AI (PII/secrets leakage, retention, provenance/lineage, access controls) across training and inference. Knows how data choices impact security and compliance.
Monitoring detection for AI apps: Knows what to log (prompts, tool calls, retrieval traces, policy hits) and how to build detections without collecting sensitive data. Can turn AI telemetry into actionable alerts and guardrails.
Understand Docker and Kubernetes
Familiarity with GO, Python or other programming languages
Experience with Databricks, Bedrock, or Azure AI Foundry is a plus
4+ years experience as a Sales Engineer, Solution Architect, or technical pre-sales role, preferably selling and supporting Cybersecurity SaaS products to Enterprise customers
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Familiar with Value-Selling Methodologies like MEDDIC, MEDDPICC, SPICED
Strong technical background with demonstrated understanding in several of the following areas: SaaS, AI, Machine Learning, Deep Learning, Rest APIs, SSO, SIEM, cybersecurity frameworks, cloud platforms (AWS, Azure, GCP), Kubernetes
Strong presentation skills and written communication in emails, RFPs, and reports
Organised, analytical, creative and adapti ... (truncated, view full listing at source)
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