AI Acceleration Group Manager

Why Join Us?

Why Join Us?

R&D is transforming. Not incrementally — fundamentally. AI is reshaping how software gets built, reviewed, tested, and shipped. Check Point is accelerating that shift from the inside, and this role sits at the center of it.

The AI Acceleration group exists to make Check Point's SASE R&D organization dramatically more productive through AI. We build the platforms, tooling, and enablement programs that turn individual engineers into force multipliers. If you believe the future of software development is agentic, and you want to be the one who makes that real at scale for a world-class security organization — this is the role.

We operate with the urgency of a startup and the resources of a global security leader.

You will lead multiple teams — managing team leads and tech leads — driving adoption across 300+ R&D engineers and operating at the intersection of engineering leadership, platform architecture, and organizational change.

Strategic Objectives

• Be the technical and strategic AI leader for SASE R&D — the authoritative voice on how AI transforms software development within the organization, bringing deep hands-on expertise, shaping direction, setting standards, and influencing leadership decisions.
• Own the AI tooling portfolio — evaluate, select, and govern the tools and platforms developers use, from AI-assisted code review to coding agents and agentic automation.
• Drive measurable improvement in R&D productivity — with clear goals, transparent tracking, and regular reporting to R&D leadership.
• Enable developers at scale through structured learning programs, onboarding paths, and community-based enablement — making AI adoption a default, not an exception.
  
  

• Lead the AI Acceleration Group
• Manage and grow multiple teams — working through team leads and tech leads — responsible for building and running AI tooling and enablement programs across SASE R&D.
• Define the group's roadmap, prioritize quarterly goals, and translate OKRs into executable engineering plans.
• Operate as both a technical leader and a people manager — you stay close to the work and invest in your team's growth.
  

• Partner with SASE product and engineering leadership to identify and drive high-impact opportunities to embed AI and agentic capabilities into the product.
• Lead proof-of-concept initiatives, shape the technical approach, and guide teams from early exploration through to production delivery.
• Serve as the bridge between the fast-moving AI tooling ecosystem and the practical realities of building a large-scale security product.
  
  

• Ensure SASE R&D has the platforms, tooling infrastructure, and architectural standards needed to build and operate AI-native workflows at scale.
• Define standards for agentic integrations, tool connectivity, and developer-facing surfaces — so teams can move fast without reinventing the wheel.
• Ensure all platforms operate within SASE R&D's security and compliance requirements.
• Stay current on the rapidly evolving AI tooling ecosystem and bring informed, opinionated recommendations to leadership.
  
  

• Design and run enablement programs — workshops, onboarding journeys, and learning paths — that make AI tooling a natural part of how SASE R&D engineers work every day.
• Track adoption, measure impact, and use the data to continuously improve — making sure the investment in AI tooling translates into real, visible productivity gains.
  
  

• Qualifications
  
  

• +8 years in software engineering.
• +3 years in engineering leadership roles.
• Demonstrated experience leading cross-functional initiatives with measurable outcomes.
• Experience navigating both fast-moving and large-scale engineering environments — you know how to drive change with urgency and how to make it stick in a complex organization.
• Proven hands-on involvement with AI tooling, agentic systems, or LLM-based products over the past two years — not as an observer, but as a builder or decision-maker.
• BSc/MSc in Computer Science, Software Engineering, or equivalent.
  
  

• Deep, hands-on expertise with AI coding tools and agent frameworks — you've built with them, evaluated them at organizational scale, and have strong, informed opinions on where the space is heading.
• Mastery of LLM integration patterns, agentic workflows, MCP (Model Context Protocol), and coding agent architectures — this is your domain, not a learning objective.
• Strong understanding of CI/CD systems, developer experience infrastructure, and modern software delivery practices.
• Solid experience in cloud-native environments and a clear grasp of the security and compliance constraints that come with enterprise-grade AI tooling.
• Hands-on experience with RAG pipelines, vector stores, and embeddings — building AI systems that go beyond prompt-response into persistent, context-aware intelligence. (Advantage)
• Experience building or integrating AI-powered internal knowledge platforms that make institutional knowledge accessible to developers and agents. (Advantage)
  
  

• Strong communicator — you can translate complex technical decisions into clear business context, from individual contributors to VPs.
• You lead by example — technically sharp, hands-on when it matters, and focused on making your teams better.
• Bias toward outcomes, not activity. You track what matters and cut what doesn't.
  
  

• A mandate to define what AI-native software development looks like inside one of the world's leading cyber security organizations — and the authority to make it happen.
• Direct ownership of SASE R&D's AI strategy: the tools, the platforms, the enablement programs, and the product direction.
• A front-row seat — and a driver's seat — at the intersection of AI agents, developer productivity, and enterprise security engineering.
• The autonomy to move fast, make real decisions, and build something from the ground up — with the resources and reach of a global organization behind you.
• Visibility with senior R&D leadership and genuine influence over decisions that affect hundreds of engineers.
• The chance to work at the edge of what's possible with AI today, in an environment where the stakes are real and the scale is significant.