Professional Services Consultant - AI Security

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!

As a Cato AI Security Professional Services Consultant, you will be a trusted advisor to our customers to help see them through their AI security implementation journey. You will provide technical guidance and direction to ensure the Cato AI security solution's smooth and successful implementation.

Curiosity – You have a desire to truly understand our customers' business needs.

Creativity – You can find a sustainable path to yes.

Empathy – You connect at a human level with our customers, and you genuinely care Responsibilities:

Maintain expert-level implementation proficiency of the Cato Networks AI Security solution while keeping abreast of the dynamic AI security and enterprise IT infrastructure landscape

Develop meaningful relationships with key customer stakeholders and their partners, adopting a consultative and prescriptive approach that inspires trust and confidence

Lead end-to-end customer engagements implementing Cato AI security solution for AI risk management, model security, and data protection so that our customers can realize the total value of their investment in our technology

Work with customer teams to design secure AI architectures and establish governance frameworks aligned to standards such as NIST AI RMF, ISO/IEC 42001, and EU AI Act guidance

Translate technical findings into actionable recommendations for both executive and technical audiences

Serve as a subject matter expert on AI and LLM security across the Cato Networks customer base Contribute to development of internal knowledge sharing, solution playbooks, and enablement materials for partners and customers

Foster collaboration with our product management, support and engineering teams by providing feedback from the field on features and functionality, influencing roadmap priorities based on customer needs and emerging threats

Support pre-sales scoping of professional services for new customer engagements

Identify opportunities to expand customer value through additional AI security services and capabilities

Collaboration with greater professional services team to help synthesize experiences and trends observed in the field into repeatable technical best practices in collaboration with other Cato functions

Operate day-to-day with minimal oversite as a point of technical escalation to provide guidance on and ensure timely resolution of any issues

Qualifications:

5+ years of experience in cloud architecture with a primary focus on AWS or Azure, including hands-on deployment and management of Amazon EKS or ECS, or Azure Kubernetes Service and hybrid connectivity services3+ years of experience in a customer-facing role (e.g., consulting, professional services, pre-sales, managed services) for a high-tech software or technology vendor with a proven track record leading enterprise consulting or professional services engagements

Exposure to implementation of API gateways (e.g., Zuul, Apigee, Kong, Amazon API Gateway, Azure API Management) and AI application specific gateways (e.g., LiteLLM, Portkey, Helicone, True Foundry)
Solid understanding of public cloud networking constructs (e.g., AWS VPCs, Transit Gateway, Direct Connect, Route 53, and Gateway Load Balancer – Azure VNets, VNGs, Express Route, vWAN, Load Balancer, and DNS)
Experience designing and securing AI/ML infrastructure including AWS Sage Maker, AWS Bedrock, Azure AI Foundry, Google Vertex AI, Databricks, GPU-accelerated compute, and model inference…