Why Join Us?

Check Point's Exposure Management group is one of the company's newest and fastest-growing AI-focused teams — built from the ground up to define how AI capabilities are embedded into our security products at scale.

We're looking for an AI Engineer who is equal parts builder, enabler, and visionary.

This is a rare opportunity to join a small, elite team at the ground floor and have outsized impact on how AI is designed, built, and shipped across a globally recognized cybersecurity platform.

If you thrive at the intersection of cutting-edge AI research and real-world production systems and you want your fingerprints on something that matters — read on.

Why Join Us?

• Greenfield opportunity — you're not joining a mature team with fixed patterns, you're helping define them.
• Real impact at scale — your work will influence products used by thousands of organizations worldwide.
• A team of great people — small, senior, and genuinely collaborative.
• Freedom to innovate — we encourage bold ideas, fast experiments, and honest feedback.
• Check Point's AI moment — AI is a company-wide strategic priority, and this group is at the center of it.
• Check Point is an equal opportunity employer committed to diversity and inclusion.
  
  

Key Responsibilities

What You'll Do

• Build AI infrastructure — Design and develop the foundational tools, frameworks, and pipelines that power the group's AI capabilities, with a focus on LLMs and Generative AI.
• Enable AI across the team — Act as the group's AI enablement engine: establish best practices, create internal tooling, and uplift teammates to work effectively with AI systems.
• Own AI agents & agentic workflows — Design, implement, and iterate on autonomous agents and multi-step AI pipelines integrated with a variety of tools and environments.
• Bring AI to production — Take models and capabilities from prototype to production-grade systems — reliable, scalable, and observable.
• Shape the big picture — Contribute to the group's AI strategy, not just its execution. We want someone who asks "why" before diving into "how."
• Stay ahead of the curve — Continuously research and evaluate emerging AI techniques, models, and tools — and bring what's relevant back to the team.
• Collaborate and communicate — Write clearly. Think clearly. Work closely with researchers, engineers, and product stakeholders to align on goals and drive outcomes.
  
  

Qualifications

Must-Haves:

• Strong hands-on experience with LLMs and Generative AI— prompt engineering, fine-tuning, RAG pipelines, evaluation, and beyond.
• Proven ability to build and ship production-level AI systems — not just notebooks, but real, deployed infrastructure.
• Experience building or working with AI agents — tool use, agentic frameworks (e.g., LangChain, LlamaIndex, AutoGen, or similar).
• Excellent written and verbal communication skills — you can explain complex AI concepts to both engineers and non-engineers.
• Strong command-line proficiency and comfort working across diverse tools and environments.
• A growth mindset — you read papers, break things, and love learning.
  
  

Nice To Have

• Experience in AI enablement — building internal tools, templates, frameworks, or training that help others work with AI more effectively.
• Background in cybersecurity or working with security data.
• Familiarity with cloud-based ML infrastructure (AWS, GCP, or Azure).
• Experience with observability and evaluation frameworks for LLM-based systems.
  
  

Mindset & Culture Fit

• Big-picture thinker — you zoom out to understand what the team is building toward and zoom in to execute.
• Team player with ambition — you lift others up while pushing yourself and the work forward.
• Self-driven — in a small team, you own your domain end to end.
• Comfortable with ambiguity— we're building something new; not everything is defined yet.